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Fable 5 as Weekly Event: Multi-Model Workflows, Anthropic Economics, and Hermes as Open-Source Counterweight

Thursday, June 11, 2026

Hello, this weekly digest works through the most important new videos from around 40 curated AI and coding YouTube channels — with substance, no shallow top-5 lists. One complete summary per video, plus a weekly overview of dominant themes. Read at your leisure — or copy a summary into your LLM of choice and go deeper. Click the link under each summary to watch the original video.

AI with Arnie (2 new videos)

• I turned Hermes Desktop into a Super-App
  11.6.2026, 08:38:02

  The video demonstrates how to set up the Hermes Desktop app as a central command center for various AI-driven tasks. It presents ten concrete use cases, including invoice processing, contract analysis, video editing, Git repository management, and task automation via cron jobs. Special emphasis is placed on the ability to use both local and cloud-based models to ensure data privacy compliance (GDPR-compliant). The video also demonstrates how to install and run Hermes on a virtual private server (VPS) to enable 24/7 automation. Additionally, it covers the integration of tools like Obsidian and n8n to create and manage complex workflows.

  **Final comment:** The video explicitly covers the Hermes Desktop app and various AI models such as Codex, OpenAI, and local models via Ollama. It is aimed at intermediate to advanced users who already have experience with AI tools and server administration.

• Hermes Desktop is dangerously good
  6.6.2026, 16:10:34

  The video introduces the Hermes Desktop app, which enables users to work with various AI models locally on their computer. Installation is now significantly simplified and no longer requires complex steps like the Windows Subsystem for Linux setup previously needed. The app provides a user-friendly interface that lets users leverage different AI models such as GPT-5.5 or Codex and switch between them seamlessly. A standout feature is Hermes’ ability to improve itself and automatically write skills that can be used for various tasks like frontend design, image generation, and integration with tools like Obsidian and ConfUI. The app also supports connections to various channels like Telegram, Discord, and Slack, as well as creating and managing superagents that can work within the same session. Users can additionally leverage local models like Ollama and adjust the context window accordingly. The app is 100% open source and gives users the flexibility to use different providers and models without being locked into a single vendor.

  The video explicitly covers the Hermes Desktop app, which is based on open-source models, and is aimed at intermediate to advanced users.

Cole Medin (2 new videos)

• Google’s Agents CLI: The CLI + Skills Combination to Ship AI Agents EASILY
  11.6.2026, 00:00:16

  This video demonstrates how straightforward it has become to create an AI agent and deploy it to production, thanks to tools like Google’s Agent CLI. The creator shows how to build an AI agent from concept to reliable deployment using a combination of a command-line interface (CLI) and skills. Google’s Agent CLI is a powerful, open-source tool that helps create agents with Google’s Agent Development Kit (ADK), a framework used by many developers. The creator compares today’s simplicity in agent building with earlier, more complex methods, and shows how AI-coding assistants like Claude Code further streamline the process. He emphasizes that while building agents has become easier, complex systems like memory systems and RAG architectures still present challenges. The bulk of the video is a live demo where the creator builds and deploys an AI agent using Google’s Agent CLI without typing a single command in the terminal himself. He uses Claude Code to manage the entire process, from installing the CLI and skills to building, evaluating, and deploying the agent. The created agent is a simple “Ask Your Data” agent that writes Python code to answer questions about a CSV file. The creator also discusses the advantages of frameworks like Google’s ADK over coding agent SDKs, particularly regarding token efficiency and speed, which are crucial for production deployment. By the end of the video, the agent is successfully deployed and tested in Google Cloud, with the creator demonstrating the various features and settings of the deployed agent.

  The video specifically covers Google’s Agent CLI and ADK and is aimed at intermediate to advanced users.

• Live AI Q&A + Crushing it in Chess at the Same Time – Come Hang Out!
  7.6.2026, 04:26:50

  # Summary: Live AI Q&A + Chess Stream

  Cole hosts a casual live stream where he plays chess simultaneously while answering AI-related questions—an experiment he’s intentionally stepping outside his comfort zone for. He’s streaming from a hotel room during his honeymoon weekend.

  **Core AI Discussion Topics:**

  **Productivity Myth:** Cole debunks claims that AI coding assistants deliver 10x productivity. The distinction between “code output” and real productivity gains is critical: developers primarily use AI to tackle backlog items (refactoring, testing, security hardening), not to build 10x more features. Real productivity improvements are closer to 2-3x when done right.

  **Model Stacking for Cost Efficiency:** Cole has extensively tested using different models for different phases of an AI coding workflow: Opus or GPT-4.5 for planning, then Claude 3.5 Sonnet or Minimax M3 for exploration, implementation, and validation. This saves hundreds of thousands of tokens with similar results. Smaller models reliably handle “trivial” and “routine” tasks.

  **A2A Protocol:** Google’s Agent-to-Agent Protocol failed because it required network effects (mass simultaneous adoption). Unlike MCP (Model Context Protocol by Anthropic), which is immediately valuable when individual MCP servers are built, A2A needed critical mass.

  **Second Brain / AI Signal Engine:** Cole recommends building personalized news aggregation that daily searches YouTube channels, RSS feeds (Anthropic Blog, Hacker News), and the web, filtering based on your projects. The system learns over time what’s relevant. He calls it his “co-founder.”

  **Framework Choice:** Pydantic AI and LangGraph remain relevant for production systems (faster, cheaper, scalable), while provider SDKs (Claude Agent SDK, OpenAI Agents SDK, Google ADK) work better for personal agents or internal tools—they’re expensive and slow, but high quality.

  **Dino Chat:** An agentic RAG tool that searches Cole’s YouTube content (and Dynamus community courses) to answer questions—free to use.

  **Personal Background:** Cole makes his living entirely through YouTube, the Dynamus community (weekly workshops, AI coding and agents courses, Second Brain training), and enterprise training. After just 3 months on YouTube, his earnings matched his software engineer salary; he left his job at Prize and has been working full-time as an educator ever since. His chess ratings: online blitz ~2100-2172, online rapid ~2000, USCF rating 1700 (since 2019).

  **Chess Subplot:** Cole plays multiple games (5+3 blitz, 10+5 rapid, bullet), wins the first (opponent hangs a queen), draws the second, loses the third decisively against a 2300-rated player, then wins two bullet games (one through time advantage and one via accidental stalemate). His play suffers from multitasking.

  Explicitly mentioned: Claude/Anthropic, OpenAI (GPT-4.5), Google (ADK, A2A Protocol), Minimax M3, Qwen models, MCP Protocol, Pydantic AI, LangGraph, Convex, Perplexity, Hermes, Archon. **Target audience: intermediate to advanced**—assumes familiarity with AI workflows, models, and deployment concepts.

Nate Herk | AI Automation (6 new videos)

• I Turned Claude Fable Into The Ultimate Second Brain
  10.6.2026, 04:40:11

  The video demonstrates how the creator uses his “Second Brain” and AI Operating System (AIOS) with Claude Fable to boost productivity and efficiency. Claude Fable, a new model from Anthropic, is described as particularly powerful and offers enhanced security measures (“cyber guard rails”). The creator emphasizes the importance of a mindset shift, moving away from using various AI tools toward a centralized system with Claude Fable. His AIOS consists of two main components: the “Second Brain,” which stores knowledge and context, and the “AI Operating System,” which adds capabilities and automations. The setup follows a framework called “the four C’s”: Context, Connections, Capabilities, and Cadence. Context includes personal and business information, Connections refer to dynamic data sources like emails or project management tools. Capabilities encompass task automation, and Cadence allows these automations to run continuously. The creator shares practical tips for using Claude Fable, such as using it as a thinking partner, interviewing the user to extract knowledge, and reviewing your own work. He also emphasizes the importance of security measures and the need to verify the AI’s work. The video concludes with a Q&A session where the creator addresses common questions about costs, data security, coding skills, and team usage.

  The video explicitly covers Claude Fable from Anthropic and is aimed at intermediate to advanced users.

• Claude Mythos is Finally Here.
  9.6.2026, 18:00:20

  The video discusses the release of two new models from Anthropic: Claude Fable 5 and Claude Mythos 5. Fable 5 is now available to all users, while Mythos 5 is initially limited to Glasswing partners. Both models cost $10 per million input tokens and $50 per million output tokens, which is twice as expensive as Opus. Fable 5 is included in Pro Max, Team, and Enterprise plans until June 22, after which it’s available only for an additional fee. Mythos 5 is a more powerful version of Fable 5 without cybersecurity safeguards and will initially be distributed via Project Glasswing. Both models show significant improvements in benchmarks compared to Opus 4.8 and other models, particularly in areas like software engineering, knowledge work, and cybersecurity. The creator emphasizes the importance of agent loops but warns against excessive use, which can lead to high token costs. He’s excited about the practical use of Fable 5 and will publish further videos on it.

  The video explicitly covers Claude Fable 5 and Claude Mythos 5 from Anthropic and is aimed at intermediate to advanced users.

• How to Build Claude Subagents Better Than 99% of People
  9.6.2026, 00:44:55

  The video explains the use of Subagents in Claude Code, a tool from Anthropic. Subagents are independent AI agents that can be delegated by a main agent to complete specific tasks. The main agent acts as an orchestrator and can run multiple subagents in parallel, each with different personalities, capabilities, and models. This helps keep the main agent’s context clean and saves costs by using cheaper models for certain tasks.

  Subagents can be both built-in and custom agents. Custom Subagents are created as Markdown files and can contain specific instructions, tools, and models. They can be used at the project or global level, depending on whether they should be available in a specific project or generally. Subagents can also be integrated into Skills, which in turn can utilize Subagents.

  Users can leverage Subagents in various ways: automatically, proactively, or explicitly by naming the agent. It’s important to formulate descriptions and instructions in Subagents precisely to avoid malfunctions. Subagents can also be configured as read-only agents to increase security.

  The video also shows how to create and configure Subagents by creating a Markdown file with YAML frontmatter. This file contains information such as the name, description, tools used, and the model of the Subagent. Users can then use the Subagents in various projects or globally.

  In summary, Subagents in Claude Code provide a powerful way to delegate tasks, keep context clean, and save costs. They can be used and configured in various ways to meet specific requirements.

  The video explicitly covers Claude Code and is aimed at intermediate to advanced users.

• Is Claude Mythos Coming?
  6.6.2026, 21:26:20

  The video discusses recent developments surrounding Anthropic’s Mythos AI model, which briefly appeared on the company’s API and then disappeared. Mythos is a highly potent model specifically developed for cybersecurity and is considered the successor to Claude Opus. So far, it has only been made available to selected partners through Project Glasswing to identify and fix security vulnerabilities in critical software.

  Mythos’s appearance on the API has sparked speculation that the model might soon become publicly available. However, Anthropic has already clarified early on that Mythos should not be made generally accessible for now. The video creator is skeptical about whether Mythos will be released to the public in the near future and suspects that recent leaks may be deliberate marketing strategies to generate attention.

  Additional factors fueling speculation include Anthropic’s upcoming IPO and competition with OpenAI, which may also be launching a new model, GPT-5.6. The creator believes it’s more likely that Mythos’s capabilities will be gradually integrated into future versions of Opus rather than Mythos being released as a standalone model.

  The video explicitly covers Anthropic and OpenAI and is aimed at intermediate and advanced users.

• AGI is Here. Anthropic Just Proved It.
  5.6.2026, 20:42:32

  The video discusses current AI development, particularly based on a report from Anthropic showing that over 80% of code shipped by Anthropic is now written by their own AI model Claude. The speaker argues that AGI (Artificial General Intelligence) is already here, defined as an AI’s ability to solve open, ambiguous problems independently. Anthropic categorizes tasks into four categories, from trivial to open, and shows that Claude has achieved a success rate of 76% on open problems, a huge increase from 26% six months ago. The AI can now handle tasks that take 12 hours and has even made better decisions than human researchers in some cases. The speaker discusses three possible future scenarios for AI: stagnation, continuous improvement under human control, and complete AI autonomy. He emphasizes the importance of AI alignment to ensure it serves humanity and the difficulties in ensuring this, as progress is hard to monitor. The speaker warns against ignoring AI development and emphasizes that the ability to identify the right problems and use AI effectively is increasingly valuable.

  The video explicitly covers Claude AI model from Anthropic and is aimed at intermediate or advanced users.

• The Skill That 10x’d My Claude Code Projects
  4.6.2026, 17:55:54

  The video addresses the challenge of transferring knowledge and context from your own mind into an AI system to achieve better and more personalized results. The focus is on a technique called “Grill Me,” which is designed to extract comprehensive information from the user and transform it into reusable context for AI. This technique was originally developed by Matt PCO and consists of a simple yet effective prompt structure that guides the user through a series of questions to reach shared understanding. The video author has further developed this technique by adding a checkpoint system that ensures all answers are recorded in a document to prevent information loss. This leads to better Skills, context, and projects, as the AI develops a deeper understanding of the user and their processes. The author emphasizes the importance of this technique to improve the efficiency and quality of AI results.

  The video explicitly covers Claude Opus 4.8 AI model and is aimed at intermediate or advanced users.

Ben AI (1 new video)

• Claude Managed Agents Will Change How You Sell AI Forever
  9.6.2026, 09:10:22

  The video explains how Managed Agents work and their potential on the Claude AI platform, particularly for selling AI solutions. It demonstrates how Managed Agents can include pre-configured agent workflows with skills, MCPs (Managed Connectors), memory, and sub-agents that can be deployed via API in various environments like Slack, custom apps, or other software solutions. The speaker shares his experience using Managed Agents in his AI agency and showcases practical use cases such as churn recovery and lead prospecting. The video emphasizes that Managed Agents represent a major opportunity for selling AI solutions to companies that may not yet be using AI tools like Claude. It also highlights the integration of skills into these agent workflows, as they are testable and improvable, which increases the reliability and determinism of automations. The speaker demonstrates how Managed Agents can be deployed in various environments like Slack, Notion, or through automation platforms such as n8n or Zapier. Finally, the video mentions the possibility of using Managed Agents for continuous learning and as part of an AI OS infrastructure, enabling new business models and AI SaaS ideas.

  The video explicitly focuses on Claude’s Managed Agents and is geared toward intermediate to advanced users who already have experience with AI tools and automation platforms.

Brian Casel (3 new videos)

• Hermes vs. Claude Cowork? Wrong Question.
  9.6.2026, 12:48:15

  The video addresses the challenge of committing to a specific AI agent platform when offerings constantly evolve and new platforms emerge regularly. The author emphasizes that rather than relying on a single platform, it’s smarter to develop underlying patterns and processes that work across different platforms. He demonstrates his current setup using two platforms: Hermes and Claude Co-work.

  Hermes is primarily used for routine background tasks like gathering and summarizing content, monitoring SEO health, and managing code repositories. The author prefers Discord as the interface for interacting with Hermes because of its superior markdown support and ability to use multiple channels and threads.

  Claude Co-work is used for creative and high-quality tasks such as content ideation, writing, and design. The author leverages Claude Co-work’s Scheduled Tasks feature to automate these tasks. He mentions being forced to offload some tasks to Hermes due to pricing changes and limitations with Claude Co-work.

  The author stresses that the patterns and processes he uses on these platforms are independent of the chosen platform and can easily be transferred to new ones. He concludes by recommending against relying on a single platform, but rather understanding and leveraging the underlying patterns.

  The video explicitly covers the AI tools/models/providers Claude, OpenAI, and Hermes and is aimed at intermediate and advanced users.

• Why apps built with AI look a little… OFF
  5.6.2026, 12:00:17

  The video addresses the problem of “design drift” when building apps with AI agents. Inconsistent designs often emerge because agents reinvent the UI at each session without a shared source for design. The author presents a solution: a design system that centrally defines colors, typography, spacing, and components and integrates them into the code. This prevents design drift and ensures consistency.

  The author demonstrates how he implements such a design system in his apps, consisting of various components like colors, typography, buttons, forms, and lists. He uses a free agent capability he developed to integrate the design system into his codebases. By defining the design system in `claude.md` or `agents.md`, the AI agent is ensured to consider design guidelines with every UI request.

  The author emphasizes the importance of understanding these tools rather than using them blindly. He recommends integrating the design system from the start in new projects, as retrofitting it later is more difficult. He also introduces Rails and React starter templates that already have his design system integrated.

  The video explicitly covers Claude and Claude Code and is aimed at intermediate and advanced builders working with AI agents.

• Claude Fable: Build me an app
  11.6.2026, 12:00:14

  The creator tests Anthropic’s new Claude Fable model on a real business project rather than just toy demos. He builds an extension for “Residents Radar,” an existing tool he uses to curate content ideas—now it should monitor external sources like YouTube, Twitter/X, Reddit, and LinkedIn to identify which topics are gaining popularity in the AI-building community.

  His process: instead of jumping straight into building, he uses Claude extensively for strategic thinking first, makes design decisions collaboratively with the model, and documents everything in a scoping document with clear verification criteria (a checklist for “Definition of Done”). Then he feeds the entire document directly into Claude Code with Fable—unusually ambitious since he skips his usual methodical breakdown into milestones.

  Fable asks sensible clarification questions upfront, explores the existing Rails codebase, and delivers a complete implementation with new UI (watch list for external sources, trending topics section with visual metrics like magnitude, velocity, and outlier score, reports feature). After the first build, the creator finds some UX quirks (confusing metric labels, padding issues), gives feedback—and Fable fixes most things in a second quick iteration.

  Two key observations: (1) The typical refinement phase after the initial build shrinks significantly when the model has clear verification criteria and can check its own work—no refactoring needed. (2) Model selection becomes a critical skill: Fable costs roughly twice as much as Opus and is available via pay-as-you-go API only starting June 22nd, no longer in the Max plan. The right question is no longer “can the model build this,” but “is the higher price worth it for this job?”

  The creator emphasizes: professional planning (not coding!) is now even more critical and learnable even for non-technical people; the “toy demos” on X are unreliable indicators—real business applications are the real test.

  **Context:** Claude Fable / Anthropic; intermediate to advanced for readers building their own apps with AI, since it’s about process, model selection, and strategic thinking, not beginner tutorials.

Melvynx (7 new videos)

• FABLE 5 : LA SUPER INTELLIGENCE EST DÉJÀ LÀ ? (modèle Claude)
  11.6.2026, 07:56:35

  The video introduces the new Claude Fable 5 and Claude Mythos 5 models and compares them with other models like Codex, Opus, and GPT 5.5. Claude Fable 5 is positioned as the most intelligent and powerful model in the world for most tasks, though it includes safety guards that activate for potentially dangerous requests. The SW Bench Pro benchmark shows Fable 5 achieving an 80% score, which is 10% higher than Opus 4.8. Another benchmark, Frontière Code, evaluates the models’ ability to generate production code, with Fable 5 successfully handling between 10% and 32% of tasks without modifications. The user shares personal experiences, including migrating an application from Postgres, Ingest, and Redis to Convex, as well as building a mobile app for training. Despite some errors and high costs (414 dollars for Claude in a single day), Fable 5 is described as extremely powerful. Critical points include the model’s time limitation until June 22nd and its high costs compared to other models. The video concludes with a recommendation to try the model and an announcement of further testing once an equivalent GPT model becomes available.

  The video explicitly discusses Claude Fable 5 and Claude Mythos 5 models from Anthropic and is geared more toward intermediate to advanced users.

• Quand vient l’heure de la pause…
  10.6.2026, 07:00:20

  The video showcases a modern, well-equipped office kitchen. The creator presents various highlights, including a beverage machine that allows personalized water orders. You can choose between different flavors like “light sparkling raspberry” and add-ons like “vitamin boost” and order your desired number of bottles. The creator tests the system and is enthusiastic about the result.

  Another highlight is the “ficello,” a device that produces string cheese, which the creator finds particularly amusing and typically American. Overall, the creator is impressed by the kitchen’s equipment and comfort, finding it tempting to work for such a company.

  The video does not address specific AI tools or models and is suitable for a broad audience, possibly with a focus on intermediate users interested in modern office equipment.

• Je code 1 HEURE avec Codex devant toi (mes secrets devoilé)
  9.6.2026, 16:00:25

  The video shows the creator working with the Codex tool to make various improvements and additions to his Subface application. Here’s a summary of the main steps and content:

  1. **Introduction and Setup**:
  – The creator uses Z as the main interface to manage multiple projects.
  – He demonstrates how to open projects in Z and execute terminal-based commands to start servers and test applications.

  2. **Workflow with Codex**:
  – The creator explains how he uses Codex for various tasks, including implementing new features and fixing bugs.
  – He shows how to start tasks in Codex while working on multiple projects simultaneously.

  3. **Specific Features and Improvements**:
  – **Inspiration Anonymization**: The creator wants to add a feature that anonymizes videos and thumbnails by replacing people, text, and logos.
  – **Free Trial Refactoring**: He works on improving the free trial page to make it more user-friendly and appealing.
  – **Onboarding Testing**: He implements and tests an onboarding system for administrators.
  – **Bug Fixes**: The creator fixes various bugs, such as unwanted dialog windows appearing and image generation issues.

  4. **Code Review and Optimization**:
  – The creator uses tools like Thermonucléaire Code Quality Review to review and optimize generated code.
  – He demonstrates how to push changes to GitHub and create pull requests.

  5. **End Result**:
  – The creator demonstrates the successful implementation of new features and improvements, including the anonymization function and the redesigned free trial page.

  The creator primarily uses Codex and Z for his work, demonstrating how to use these tools efficiently to improve his application. The video is geared toward intermediate to advanced users who already have experience with code development and using AI tools.

• Tu es le bienvenu
  9.6.2026, 13:25:31

  The video addresses the danger of relying too heavily on a single AI tool, particularly Claude. The creator emphasizes that current market leaders like OpenAI, Anthropic, and Chinese models aim to lock users in through vendor lock-in strategies, which can be expensive and restrictive in the long term. He recommends staying flexible, testing different tools, and avoiding dependency on a single tool. As an example, he mentions his own use of Claude, Cursor, and CEX to ensure he isn’t dependent on any one tool. The focus is on being ready to switch tools as soon as better alternatives become available.

  The creator explicitly discusses Claude, OpenAI, Anthropic, open-source models, and Chinese models, with the video geared more toward intermediate and advanced users.

• C’est foutu
  8.6.2026, 11:22:40

  The video discusses the decision to switch between different AI models like Claude and Codex. The speaker emphasizes that switching doesn’t automatically lead to higher earnings but often means additional work, as he would then need to create new tutorials and content. He argues that he should remain honest and won’t pretend to use a specific tool just to please the community. The speaker acknowledges that GPT-4 (Codex) has made significant progress and matches or even surpasses Claude’s performance, as confirmed by benchmarks and developers. He stresses that even small improvements in AI performance can have major impacts on his daily work. He also criticizes people reluctant to switch AI models for potentially not taking the necessary steps to work flexibly with different agents.

  The video explicitly addresses Claude and Codex and is geared toward intermediate to advanced users.

• Formation Codex GPT : tout apprendre sur Codex en 2026 (gratuit)
  7.6.2026, 16:00:29

  The video offers a comprehensive introduction to Codex, an OpenAI AI tool specifically designed for software development. Codex is presented as a powerful competitor to Claude Code and can create applications like Umail, Saveit.now, and Ciao App. Unlike ChatGPT, which works as a “one-shot” model, Codex enables more complex tasks through its orchestrator function by leveraging models like GPT-4/5 and combining them with tools like file operations.

  Installing Codex is done through the official website, and after signing in with a ChatGPT account, you can choose from different pricing models. Setup includes selecting “Coding Mode” and enabling Full Access for maximum functionality. Codex’s user interface resembles ChatGPT’s but offers additional features like working in projects and integration with IDEs like VS Code or Z.

  A central feature of Codex is the ability to use Skills, which automate specific tasks or workflows. These Skills can be organized in different categories, such as Tool Skills (API integration), Workflow Skills (code reviews, pull requests), and Meta Skills (skills for managing other skills). Skills can be invoked through commands like `/skill` or by directly requesting them from the agent.

  Another important aspect is Subagents, which allow breaking down complex tasks into smaller, parallel subtasks. These Subagents can use specific models and return their results to the main agent, optimizing efficiency and context consumption.

  The video also demonstrates how to configure and manage agents by creating TOML files in a specific directory. These agents can then be used for various tasks like code exploration, documentation research, or web search.

  In conclusion, downloading the speaker’s configurations and Skills is recommended to get the most out of Codex. It’s emphasized that there are many more features like Hooks, MCP, and CLI Skills that could be covered in future videos.

  The video explicitly discusses OpenAI and is geared toward intermediate to advanced users.

• MIGRATION de Claude à Codex : 1 seul ligne à faire (TUTO SIMPLE)
  4.6.2026, 16:00:38

  The video demonstrates how to migrate configuration from Claude to Codex to simplify the use of Skills and Agents and standardize configuration across platforms like Cursor and Codex. The creator introduces an open-source CLI tool that migrates the entire configuration in less than 5 seconds using the command `npx ai-blueprint unify`. The tool creates symlinks for Skills and Agents, making them available on both platforms. Additionally, a backup of the original configuration is created to prevent data loss. The creator emphasizes the importance of keeping configuration easily transferable since tools change over time. The tool Lalal.ai is also introduced, which separates audio tracks and offers various audio editing functions.

  The video explicitly addresses specific tools like Codex, Cursor, and the open-source CLI tool from ai-blueprint and is geared toward intermediate users.

Dave Ebbelaar (1 new video)

• Build a Full-Stack GenAI Project in 4 Hours (FastAPI, React, Supabase)
  6.6.2026, 12:44:23

  ### YouTube Video Summary

  The video demonstrates a comprehensive process for building a full-stack GenAI application that enables users to ask questions based on hundreds of documents stored in a database. The focus is on the entire architecture, including frontend, backend, database connection, ingestion and ranking pipeline, and how everything fits together.

  **Main Steps and Final Result:**
  1. **Project Setup:**
  – Creating a GitHub repository with agent files (e.g., `agents.md`) and dependency management (e.g., `pyproject.toml`).
  – Setting up a virtual Python environment manager (UV) for managing dependencies.

  2. **Data Download and Processing:**
  – Using a Python script (`download.py`) to download financial reports (10-K, 10-Q, annual reports) from companies like Apple, Microsoft, Nvidia, Amazon, and Google from the SEC website.
  – Converting downloaded HTML files to Markdown using the Dockling tool to prepare data for further processing.

  3. **Database Modeling and Migration:**
  – Defining database models (e.g., `users`, `source_documents`, `document_chunks`, `chats`, `messages`, `citations`) with SQLAlchemy.
  – Performing database migrations with Alembic to synchronize models with the Supabase database.

  4. **Backend Development:**
  – Setting up a FastAPI backend with endpoints for user authentication, chat processing, and document querying.
  – Integrating OpenAI for creating embeddings and processing language models.

  5. **Frontend Development:**
  – Setting up a React frontend with TypeScript and Tailwind CSS for the user interface.
  – Implementing authentication mechanisms (e.g., user login and logout) with Supabase.

  6. **Ranking Pipeline:**
  – Implementing a hybrid ranking pipeline that combines semantic search (with PGVector) and full-text search (with Supabase).
  – Using Pydantic models to structure queries and responses.

  7. **Deployment:**
  – Deploying the application on Railway, a Platform-as-a-Service provider, using Docker containers for backend and frontend.
  – Configuring environment variables and database connections for production.

  **AI Tools/Models/Providers:**
  – **Claude / OpenAI / Gemini / Open-Source:** The video uses various AI tools such as OpenAI for embeddings and language models, Pydantic for data structuring, and Dockling for document processing.
  – **Specific Tools:** Cursor, Lovable, Cline, n8n.

  **Target Audience:**
  – **Intermediate to Advanced:** The video is aimed at developers with advanced knowledge in Python, React, databases, and deployment processes who are interested in AI engineering and full-stack development.

  **Closing Remark:**
  The video provides deep insights into building a full-stack GenAI application and demonstrates how various components work together to create a powerful and user-friendly solution. It’s a valuable resource for developers looking to expand their skills in AI engineering and full-stack development.

Niklas Steenfatt (1 new video)

• Ich habe beim größten Schachturnier der Welt mitgemacht!!!
  4.6.2026, 15:56:55

  The YouTuber reports on his participation in the Grankle Chess Open in Karlsruhe, one of the world’s largest chess tournaments. He describes his experiences over five days, during which he played against players with higher Elo ratings, including some strong opponents. He won some games, lost others, and experienced dramatic moments, such as a victory against a stronger opponent who lost on time. The YouTuber emphasizes the mental and physical strain of the tournament and the special atmosphere among chess enthusiasts. He analyzes some of his games and shows how he became more confident over time despite initial uncertainty. In the end, he achieved a total score of 5.5 out of nine points and reflects on the unique experiences and challenges of tournament chess.

  The video does not address specific AI tools or models and is aimed more at intermediate and advanced chess players.

Fireship (1 new video)

• Anthropic is starting to panic…
  9.6.2026, 17:32:30

  The video discusses Anthropic’s current development, which has a valuation above OpenAI and is planning a billion-dollar IPO. Anthropic warns of the danger of recursive self-improvement in AI, which could become a threat to humanity. The company proposes a global halt to AI development, but this seems difficult due to competition with other companies like OpenAI, DeepMind, and XAI. Historically, such warnings have often been exaggerated, as shown by the example of GPT-2. Nevertheless, there are concerns that AI is already being used in critical areas such as data centers, robotics, and weapons today. A study by economists from Boston University warns of an “AI Layoff Trap,” in which automation could lead to a decline in demand and thus to economic problems. Alternatively, the thesis is put forward that AI may not be as powerful as often assumed, and that many AI projects in companies do not achieve measurable success. The video also mentions tools like Pioneer that can help improve the efficiency of AI applications.

  The video covers Anthropic, OpenAI, DeepMind, XAI and specific tools such as Pioneer, Codeex, Cursor, and Hermes, and is aimed at an intermediate to advanced audience.

Julian Ivanov | AI Automation (1 new video)

• How to make Claude watch every video for you
  7.6.2026, 18:05:41

  The video shows how to use Claude (an AI platform) to analyze and summarize videos frame by frame, rather than relying solely on transcripts. Users can upload or link videos from various platforms (YouTube, Instagram, Loom, etc.), and Claude extracts key information and images from the videos. This information is then saved as a note in Obsidian, which is particularly useful for visual learners.

  Concrete use cases include:
  1. **Educational videos**: Summarizing tutorial videos, such as those about Transformer architectures, with important diagrams extracted and inserted into notes.
  2. **Videos without speech**: Analyzing vacation videos or other videos without spoken content to identify specific scenes or events.
  3. **Screen recordings**: Analyzing screen captures to identify bugs or issues in apps or programs and find solutions.
  4. **Viral content**: Analyzing successful social media videos to understand why they perform well and what visual hooks are being used.

  Installing the required plugin is straightforward and is done automatically by Claude. Needed tools include YT-DLP for downloading videos, FFMPEG for extracting frames, and a transcription model like Whisper, which can be accessed through platforms like Grock.

  The video explicitly features Claude and open-source tools like YT-DLP, FFMPEG, and Whisper. It’s suited more for intermediate users who already have experience with AI tools and their integration into workflows.

Mark Kashef (1 new video)

• Don’t Use Claude Fable 5 Until You See This
  11.6.2026, 15:00:25

  # Summary: Responsible Use of Claude Fable 5

  The video addresses not benchmarks, but practical strategies for cost-efficient use of Anthropic’s new Fable-5 model. Core thesis: with great computing power comes great token consumption – using Fable for everything burns through credits quickly and unnecessarily.

  **Key insights on model architecture:**
  The extracted system prompt of Fable 5 matches that of Opus 4.8 by roughly 80%; new additions include explicit safety measures against self-harm and misuse in life sciences. The model operates internally like Mythos with hard safeguards – for cybersecurity, life sciences, or health questions it automatically downgrades to Opus 4.8. This shows: even at peak intelligence, extensive manual “handholding” through prompts is necessary.

  **Practical workflow strategy:**
  Rather than using Fable as default, differentiate by task type and effort. Example workflow: (1) Fable on max/high for planning and specification; (2) Opus or Sonnet on medium/high for execution; (3) Fable on low/medium for verification and edge-case checks. In conversation, you can switch between models and effort levels mid-session with `/slashmodel`. Fable-5-Medium already outperforms Opus-4.8-Max, Fable-Low remains competent enough for many tasks.

  **Three concrete use cases:**
  – Simple marketing website: Fable high (planning) → Opus medium (execution) → Fable low (verification)
  – 3D website: Fable max (planning, due to 3JS complexity) → Opus/Sonnet agents (execution) → Fable high (verification)
  – CRM app: Fable max (planning, given many endpoints/security requirements) → dynamic workflows with deeper models → Fable high (verification)

  **Limitations and realism:**
  Fable 5 rejects cybersecurity queries (even legitimate ones) – not yet reliable enough for daily use, Opus more trustworthy. The model becomes metered (pay-per-API) from June 22nd, making planning for sustainable use essential. Prices are likely to rise post-Anthropic IPO.

  **Core message:** Don’t become tribal about one model. The future lies in modular, efficient multi-model workflows where each stage uses the right tool at the right price. Benchmarks are a distraction – only results matter.

  **Claude/Anthropic tools discussed:** Fable 5, Opus 4.8, Sonnet, Claude Code, MCPs, verification loops with Chrome MCP; CodeX (OpenAI) is mentioned as a possible alternative. The video targets **intermediate to advanced users** (understanding of prompting, agentic workflows, and token economics is assumed).

Everlast AI (2 new videos)

• 20 AI Tools That 99% Have Never Heard Of (And Will Put You Ahead of Everyone)
  9.6.2026, 15:15:07

  The video presents a list of 20 AI tools divided into four categories: Agent Layer, Agent Tools, Daily Driver, and Monitoring. The focus is on tools that go beyond well-known standard tools like ChatGPT and Gemini, enabling greater autonomy and productivity.

  1. **Agent Layer**:
  – **Codex**: A super app from OpenAI that serves as a work environment for autonomous agents. It enables access to the entire file system and can handle complex tasks like accounting, market analysis, and meeting notes.
  – **Cloud Code**: A tool particularly strong at designing and orchestrating subagents. It can create complete landing pages and conduct competitive analysis.
  – **Cursor**: A full-featured development environment with agents as a main pillar, capable of switching between different models and offering its own frontier model for coding tasks.
  – **Google AI Studio**: A tool that enables building an entire Android app with just one prompt and sharing it with a few clicks.

  2. **Agent Tools**:
  – **Browser Use**: A tool that gives agents access to a real browser and mouse control to navigate websites.
  – **Excalidraw MCP**: An open-source tool for visualizations offering editable views for collaborative work.
  – **N8N MCP**: A workflow automation tool that gives agents access to over 1850 available integrations.
  – **Meta @ CLI**: A tool that gives agents full access to Ads Manager to analyze and optimize campaigns.
  – **Hixfield CLI**: A tool that enables generating advertising creatives directly from the terminal.
  – **Google Workspace CLI**: A tool that gives agents access to Gmail, Sheets, Docs, and Calendar.
  – **Agentmail**: A tool that provides agents with their own email mailbox with full API support for sending and managing emails.
  – **Remotion**: An open-source plugin that enables generating and editing videos as code.

  3. **Daily Driver**:
  – **Superbase**: An open-source database serving as a single source of truth for all data.
  – **Ollama**: A tool that enables running leading open-source AI models locally and offline on Mac or server.
  – **Cloudflare**: A tool that enables securely bringing apps to the internet and protecting them with Zero Trust.
  – **Corporate LLM**: A platform for productive and GDPR-compliant work with AI models and tools.
  – **Notebook LM**: A Google tool that enables answering exclusively from uploaded sources and conducting research work.
  – **Voicely**: A desktop app that enables dictating text and thereby working five times faster.
  – **Magnific**: A creative tool that enables integrating text-to-image and video models and automating workflows.

  4. **Monitoring**:
  – **Lang Fuse**: An open-source tool that logs every model call and monitors costs. It also enables automatic evaluation of agent response quality.

  The video is aimed at intermediate and advanced users, as it presents specific tools and techniques requiring deeper understanding of AI and its applications.

• AI News: MASSIVE ChatGPT Update! Codex “Apps”, New Features & Local AI Catching Up
  7.6.2026, 08:15:36

  The video summarizes the latest developments in the AI world, with emphasis on OpenAI’s major updates, particularly the integration of Codex into ChatGPT. This integration enables a unified experience where agents work in the cloud and proactively complete tasks before users even recognize them. New features like role-specific plugins, annotations, and Codex Sites allow users to create and share software with simple prompts. Additionally, ChatGPT’s improved memory architecture is introduced, which updates itself and is available in the free plan.

  In parallel, there is progress with local AI models. Google has released the open model Gemma 4.12B, which understands text, images, audio, and video and runs on a standard work laptop. This model can be freely integrated into Corporate LM to work locally and securely. Nvidia has also introduced a new open-weights model, Nemotron 3 Ultra, which is designed to be more efficient and faster.

  The video also demonstrates practical applications of these technologies, such as creating a mini app in Codex and using local models in Corporate LM. It notes that while local models are suitable for certain tasks, they are not yet sufficient for complex tasks like agentic coding.

  Additionally, developments in humanoid robots, particularly from AGI and BYD, as well as construction site automation through Sensmore are discussed. Microsoft and Meta are presenting new AI models and agents intended to improve their respective platforms.

  Final comment: The video covers OpenAI (ChatGPT, Codex), Google (Gemma), Nvidia (Nemotron), Corporate LM, and specific tools like Codex Sites. It is aimed at intermediate and advanced users.

No Priors: AI, Machine Learning, Tech, & Startups (3 new videos)

• Mark Zuckerberg’s Plan to End All Disease
  10.6.2026, 19:23:49

  The video tells the story of Mark pursuing the ambitious goal of building an organization that can cure, prevent, and manage diseases by the end of the century. Initially, these plans were dismissed by renowned scientists, including Nobel laureates. Mark emphasizes that the intention was never to cure all diseases himself, but rather to develop tools that accelerate the entire scientific community and collectively combat disease. What was once considered unrealistic now appears even conservative.

  Final commentary: The video does not address specific AI tools or models and is aimed at a broad audience, including beginners and intermediate viewers.

• Biohub: The Future of Biology is Open-Source with Mark Zuckerberg, Priscilla Chan, and Alex Rives
  10.6.2026, 13:00:36

  The video is an interview with Mark Zuckerberg, Priscilla Chan, and Alex Reeves about their work at Biohub and the application of AI in biology. They discuss the founding of Biohub, their vision to equip the scientific community with tools to accelerate understanding of biology and ultimately cure disease. Biohub focuses on developing open-source tools and fostering collaboration between engineers and scientists. They emphasize the importance of open-source projects to quickly get tools into the hands of scientists and accelerate progress across the scientific community. The conversation also covers challenges and advances in applying AI to biology, including protein structure prediction and developing models for cells and biological systems. They discuss the importance of mechanistic interpretability and how AI models can provide new biological insights. Additionally, the need to transform clinical research to accelerate the translation of basic research into clinical applications is emphasized. The video explicitly addresses Biohub’s AI models and open-source tools and is geared toward intermediate and advanced viewers.

• Satya Nadella: Why Humans Still Create Value
  8.6.2026, 15:44:06

  The video discusses the connection between human capital and token-based capital in enterprises. It argues that companies are now able to capture implicit knowledge and record it on a balance sheet, something that was not possible before. The ability of humans to identify gaps and develop new forms of agency and ambition remains crucial for value creation. Despite growing token capital, human capital will continue to be of great importance.

  The video does not address specific AI tools or models and is aimed more at intermediate or advanced viewers interested in enterprise strategy and capital management.

Nic Conley (1 new video)

• Claude Fable 5 is Here (everything in 7 min)
  10.6.2026, 19:51:34

  Anthropic has released Claude Fable 5, a model based on the powerful but not publicly accessible Mythos architecture. Fable 5 is a stripped-down version of Mythos made available to the general public, while Mythos 5 remains reserved for select users. Fable 5 demonstrates significant improvements in specific areas like Agentic Coding, achieving 80% compared to 69% for Claude Opus 4.8. However, some features, such as biology and cybersecurity, are restricted to minimize potential risks.

  Pricing for Fable 5 is significantly higher at $10 per million input tokens and $50 per million output tokens compared to Opus 4.8, making it twice as expensive. Fable 5 is available until June 22 for users with a paid Claude account, after which it will be accessible only via Usage Credits or the API.

  In a practical demonstration, both models were tested with the same task: building a 3D flight simulator in a single HTML file. Both models delivered impressive results, with Fable 5 taking slightly longer to execute. However, the differences between the models were not significant enough to justify the higher price, particularly for simple applications.

  The video explicitly focuses on Claude Fable 5 and Claude Opus 4.8 from Anthropic and is more suited for intermediate users.

Tech With Tim (10 new videos)

• The Best LOCAL Agentic Coding Workflow (Complete Guide)
  10.6.2026, 13:00:23

  This video is a tutorial that explains how to set up and use local models for local programming. The author emphasizes that local models are a cost-effective and internet-independent alternative to cloud-based models running on powerful servers with lots of RAM and graphics cards. The focus is on selecting the right model based on available hardware, particularly video RAM (VRAM) or unified memory on M-series Macs. The author recommends various models from the Qwen family, depending on the user’s hardware configuration. The tutorial walks through installing and configuring LM Studio and Visual Studio Code to use local models for autocomplete and code generation. It also demonstrates using the “Continue” extension in VS Code to configure autocomplete. The video is suitable for intermediate users who already have basic knowledge of programming and code editors.

  **AI Tools/Models/Providers Discussed:** LM Studio, Visual Studio Code, Continue extension, Qwen family of models (Qwen 2.5, Qwen 3.6, Qwen 3.5, Qwen Coder Next), Hugging Face.

• The Hard Truth Every Developer Needs to Hear in 2026
  10.6.2026, 12:00:23

  The video discusses the necessity for developers to adapt to changing market conditions to remain employable. It emphasizes that resistance to adaptation can lead to falling behind, while adapting to new technologies and methods is crucial to securing your job and livelihood. The speaker acknowledges that current developments are frightening and uncertain, but also bring positive aspects, such as the ability to build more than ever before. The main message is that developers must remain flexible and ready to respond to future changes.

  The video addresses adapting to new technologies in general and is intended for intermediate and advanced developers.

• The Software Development Bottleneck Just Moved
  9.6.2026, 12:00:08

  The video discusses the shift in bottlenecks in software development. Previously, the focus was on writing large amounts of code, which was expensive and time-consuming. Today, code is relatively cheap to produce, but other skills have become scarce. These include system design, operational excellence, observability, incident response, debugging in production, and the ability to assess trade-offs. The bottleneck is no longer about how much code can be written, but how much code can be reviewed, secured, deployed, and maintained in production with all necessary features. It’s no longer about how much code is produced, but how good that code is. The emphasized skills enable the development of scalable, profitable, and usable systems.

  The video addresses general principles of software development and is intended for intermediate or advanced developers.

• Why Companies Won’t Hire Junior Devs And Why It’ll Backfire
  8.6.2026, 12:00:34

  The video discusses the problem of dwindling engineering talent in the software industry. It notes that software quality is declining due to frequent security breaches and exploits. At the same time, fewer junior developers are being hired and trained while senior developers retire. This creates a situation where companies primarily seek experienced senior engineers, making it harder for career starters to enter the field. In the long term, this could lead to a shortage of qualified developers as talent development is neglected.

  The video addresses general industry trends and is intended for intermediate or advanced viewers dealing with software development challenges.

• I Went to the Biggest AI Infrastructure Conference
  7.6.2026, 14:30:01

  The video covers the challenges and solutions related to developing and deploying AI agents. The main focus is on the Temporal platform, which enables reliable execution of AI agents through durable execution. Temporal solves problems such as timeouts, server restarts, and other production failures by storing the state of workflows and providing automatic retries and error recovery. The video shows demos and workshops from the Temporal Replay Conference in San Francisco, where using Temporal to build durable AI applications in Python is demonstrated. It also includes interviews with other tech influencers explaining Temporal’s benefits. The conference presented new features and partnerships, including close collaboration with OpenAI, which uses Temporal to scale its AI applications. The video emphasizes Temporal’s importance for reliably integrating AI into applications and encourages viewers to try the platform.

  Final Comment: The video explicitly discusses Temporal and is intended for intermediate and advanced users.

• The Fastest Way to Get Good at Coding
  7.6.2026, 12:00:00

  The video emphasizes that the fastest way to improve skills is to build projects that are slightly above your current skill level. After learning a concept through tutorials, you should immediately apply similar projects without guidance. A completed project teaches more than multiple unfinished ones. By working on something slightly more complex, you learn new things, solve problems, and develop critical thinking. What’s important is not to overwhelm yourself, but still challenge yourself. The speaker emphasizes that this method contributed to his personal coding success.

  The video addresses general learning strategies and is suitable for intermediate developers.

• Why Python Is Easy to Start but Hard to Master
  6.6.2026, 12:00:20

  The video emphasizes that Python is one of the easiest programming languages to start with, but also one of the most powerful you can master. However, it warns that despite the easy entry point, it takes time and effort to become truly proficient. The fundamentals require weeks of work, while mastery can take months or even years. The good news is that demand for Python developers, especially in AI and data science, is higher than ever. The investment is worthwhile. The advice is to go deep in one specific area rather than skimming many areas superficially. Once you’re good at one area, many other skills automatically follow, but you already have a head start through expertise in a niche that enables you to land a job and enter the professional world.

  The video addresses Python and is suitable for beginners and intermediate developers.

• Hermes Agent – Full Course & Setup Guide – For COMPLETE Beginners
  5.6.2026, 14:00:09

  This video is a comprehensive guide for beginners to install, configure, and use Hermes Agent. The creator explains step by step how to set up Hermes Agent on a virtual private server (VPS), using Hostinger as an example. He emphasizes the importance of security measures and demonstrates how to securely manage API keys and access permissions.

  The creator explains the five core concepts of Hermes Agent: memory, skills, Chronos (scheduled tasks), personality, and self-improvement. He discusses the significance of Hermes Agent’s self-learning capability, which distinguishes it from other agent frameworks like Open Claw.

  The creator demonstrates how to connect Hermes Agent with various tools and services such as Gmail, Google Calendar, and Composio to create automated workflows. He demonstrates creating daily email triage and security audits along with other useful use cases.

  At the end of the video, the creator encourages viewers to develop creative and useful use cases for Hermes Agent and emphasizes that the agent’s effectiveness depends on proper configuration and integrations.

  The video explicitly discusses Hermes Agent and is intended for beginners.

• The Biggest Mistake I Made Learning Python
  5.6.2026, 11:53:09

  The video addresses the biggest mistakes the speaker made while learning Python. The main mistake was trying to learn everything at once – web development, game development, data science, scripting, and automation. This made him superficially knowledgeable in many areas but not deeply skilled in any. He started various projects, such as a Flask project, Pygame, or data analysis, but didn’t complete any of them. The result was that after months of learning, he couldn’t confidently build a single complete project in any of these areas. Instead, he should have mastered the fundamentals first and then chosen one direction.

  The speaker emphasizes the importance of focusing on fundamentals first and then diving deep into a specific area to actually learn and apply something. The video is aimed at beginners who want to learn Python and avoid making similar mistakes.

  The video does not address any specific AI tools or models.

• The Reason Tutorials Aren’t Making You a Better Coder
  11.6.2026, 12:00:22

  **Summary:**

  The video argues that passive learning through videos or blog posts conveys only about 20% of the information, while active learning by writing real code increases retention to 75–90%. This difference explains why many feel engaged while learning but can’t build independently after a tutorial ends. The central recommendation for action: learning resources should force you to write code yourself rather than just watch. If you don’t type, you don’t really learn – true improvement comes only from many hours of actual coding.

  —

  *No specific AI tools or providers mentioned; the video is directed at beginner and intermediate developers as motivation for active learning.*

NeuralNine (2 new videos)

• Simulating Percolation in Python: How Do Wildfires & Diseases Spread?
  8.6.2026, 16:00:34

  This video demonstrates how to simulate percolation in Python, which involves processes where something spreads, such as diseases or wildfires. The focus is on learning animations and simulations, as well as understanding the mathematical phenomenon of percolation. A 2D grid simulation is created where randomly placed “people” or “trees” become infected or ignited and spread to their neighbors. The critical parameter is the grid occupancy (here 59.27%), at which point infection or fire statistically spreads across the entire grid or doesn’t. The tutorial walks through the steps for creating the simulation, including calculating spread and visualization with Matplotlib. It also explains how to adjust the occupancy parameter to increase or decrease the probability of spread. The video is suitable for intermediate Python programmers who want to deepen their skills in animation and simulation.

  **AI Tools/Models/Providers:** Python, NumPy, Matplotlib, Open Source

  **Target Audience:** Intermediate

• This Is My Favorite Claude Code Feature…
  5.6.2026, 16:00:18

  This video showcases the “Remote Control” feature of Claude Code, which allows you to control coding sessions from your smartphone. The user can continue an active session on their computer from their phone via QR code or link connection. This enables coding on the go, such as on the subway or the toilet. The process involves starting a session, enabling remote control, and connecting your phone to the session. You can then send commands and changes from your phone and see the results in real time. The feature is particularly useful for simple tasks like changing styles or brainstorming features, but less suitable for complex programming work. The user emphasizes that the session should run in an isolated environment, as ending the session sometimes doesn’t work reliably. He recommends running multiple sessions in parallel to work on different projects.

  The video explicitly addresses Claude Code and is aimed at intermediate users.

Bart Slodyczka (2 new videos)

• Running Gemma 4 12b on my 16gb Mac Mini
  9.6.2026, 12:00:12

  The video introduces Google’s new open-source model Gemma 4 12B, specifically optimized for devices with 16 GB of RAM. It positions itself between smaller, less capable models (Gemma 4 E2B and E4B) and larger, more powerful models (Gemma 4 26B and 31B). Particularly noteworthy is that Gemma 4 12B achieves the performance of the larger 26B model while consuming only half the storage space. The model can be downloaded and used via LM Studio, requiring 7.56 GB of storage. The context length can reach up to 260,000 tokens, though this affects available memory. The video demonstrates how the model runs on a 16 GB Mac Mini and conducts a simple conversation, albeit with somewhat slow response speeds.

  The video explicitly focuses on Google’s open-source model Gemma 4 12B and is better suited for intermediate users.

• 5 Thing To Try With Claude Fable 5
  11.6.2026, 11:57:33

  **Summary:**

  The video provides five concrete strategies to make the most of Fable 5’s remaining 10 days before it leaves the cloud subscription:

  1. **Understand the math**: Usage runs in 5-hour windows – four per day is feasible, totaling 40 sessions over 10 days.

  2. **Upgrade to the $200 plan**: For one month with 40 sessions, this works out to only $5 per session – which the speaker considers worthwhile, as an entire project like Lovable, Replit, or Minecraft could be rebuilt in a single session.

  3. **Solve stranded code projects**: A long-running project you’ve been working on for 6 months can be resolved in one session with the prompt “Read every session, read every file, find out what’s blocking me and fix it.”

  4. **Recreate existing paid tools**: The speaker has been spending hundreds of dollars per week on cloud-managed agents, which Fable 5 can reconstruct as a local version – to run on your own computer with local models.

  5. **Have Fable document its successor model**: Fable should document the skills, instructions, and configurations that cheaper local models (like Hermes with Gemma 4) can execute, so you retain an optimized system after Fable’s departure.

  **Context**: Fable 5, Lovable, Replit, Hermes, Gemma 4 – a practical how-to video for intermediate to advanced users with a clear focus on local and cost-effective AI solutions.

AI Explained (1 new video)

• Claude Fable 5 – Full 319 page Breakdown
  10.6.2026, 18:43:12

  The video offers a detailed summary of the key points from Anthropic’s 319-page release notes for Claude Fable 5, a new language model. Here are the main highlights:

  1. **Blocking and Access Restrictions**: Claude Fable 5 is initially not available to all users, including Pro and Max subscribers, as Anthropic wants to shift usage to a credit-based system.

  2. **Performance Improvements**: Fable 5 demonstrates significant advances in various areas such as creativity, science, and technology. It can handle complex tasks like creating a Pokémon clone or designing biological sequences.

  3. **Security and Monitoring Mechanisms**: The model features strong security mechanisms designed to protect against misuse, particularly in sensitive areas like biology and chemistry. However, these mechanisms can also hinder legitimate research work.

  4. **Benchmark Comparisons**: Fable 5 outperforms competitors in many benchmarks, including GPT-5.5 and Gemini 3.1 Pro. It shows particularly strong performance in areas like spatial reasoning, agentic coding, and scientific reasoning.

  5. **Challenges and Limitations**: Despite its advances, Fable 5 still makes mistakes, particularly in production, and cannot fully autonomously handle complex tasks. It tends to favor overcomplicated solutions and often needs verification.

  6. **Future Perspectives**: Anthropic plans further improvements and new models that will be even more powerful. However, discussions around AI safety and ethics remain a central topic.

  The video explicitly addresses Anthropic’s Claude Fable 5 model and is better suited for intermediate to advanced users.

Alex Finn (1 new video)

• Claude Fable 5 just dropped and I’m speechless…
  9.6.2026, 20:08:12

  The video covers the release of Claude Mythos 5, also known as Claude Fable 5, from Anthropic. The host emphasizes the model’s outstanding benchmark results and discusses its key features and recommendations for use. Important points include treating Claude Fable 5 as an equal partner, using Goals and Loops for autonomous workflows, and encouragement to tackle more ambitious projects. The host demonstrates the model’s capabilities by building a complex personal productivity app within a single Goal, highlighting the benefits of enhanced planning and Loop features. He also shows how to integrate Claude Fable 5 with other tools like Linear to manage tasks automatically. The video concludes by noting that Claude Fable 5 is initially available only to subscribers before becoming available through the API at a higher price point.

  The video explicitly focuses on the AI model Claude Mythos 5 (Claude Fable 5) from Anthropic and is targeted at intermediate to advanced users.

AI Foundations

No new videos in this period.

n8n (1 new video)

• n8n Natively supports open telemetry and tracing
  9.6.2026, 13:00:26

  The video demonstrates how n8n automatically includes workflows and node executions in traces by adding just two environment variables to the configuration. These traces are represented as parent spans for workflows and child spans for nodes. n8n uses OpenTelemetry for this implementation, enabling seamless integration into existing tracing setups for both incoming and outgoing data. Prior to this change, the costs for AI classifications in n8n on the user’s news website were not visible; now they are displayed in Grafana.

  The video explicitly covers n8n and OpenTelemetry and is aimed more at intermediate users.

Greg Baugues

No new videos in this period.

TheAIGRID (5 new videos)

• The Hidden Problem With Elon Musk’s SpaceX AI Datacenter
  10.6.2026, 14:03:24

  The video discusses Elon Musk’s ambitious plan to move artificial intelligence (AI) to space to bypass Earth’s limited resources. Musk proposes launching thousands of satellites that would beam AI computing power from orbit to Earth. He argues this would be simpler and more efficient, since the sun shines constantly in space and cooling is facilitated by the vacuum. Musk plans to exponentially increase AI computing power over the coming years, starting with 1 gigawatt by the end of next year and multiplying it tenfold annually.

  However, there are several hidden problems that Musk barely mentions. First, operating AI in space currently costs about 3.5 to 4 times more than on Earth. The greatest costs come from transporting hardware to orbit. Currently, it costs about $1,400 to $2,700 per kilogram, while it would need to drop to around $200 per kilogram for economic viability. Musk is betting on developing the Starship rocket to reduce these costs, but this technology is not yet fully mature.

  Second, power supply in space is not as simple as Musk portrays it. Satellites are in sunlight only about 60% of the time, and cooling requires enormous radiators that could reach city-sized proportions. Third, radiation in space is a problem that damages electronics and allows no repairs, leading to higher costs and more redundancy. Finally, there’s a data flow problem: current laser links between satellites are much slower than connections in Earth-based data centers, affecting the efficiency of large AI models.

  Despite these challenges, Musk argues that Earth may soon be unable to meet AI’s growing energy demands, while space represents an unlimited resource. Semi-Analysis estimates that AI costs in space and on Earth could equalize by around 2040, with Musk’s more optimistic scenarios predicting this in the early 2030s.

  Final comment: The video explicitly covers SpaceX, Elon Musk, and his vision for AI in space, as well as the technical and economic challenges involved. It’s geared more toward Intermediate and Advanced viewers, as it contains detailed technical and economic analyses.

• How To Use Claude Fable 5 – Tips And Tricks Most People Miss
  9.6.2026, 21:31:13

  The video covers the use and features of Anthropic’s Fable 5 model. It emphasizes that Fable 5 is a powerful model but not suitable for everyday use. On topics like biology, chemistry, cybersecurity, or mathematics, the model automatically falls back to Opus 4.8 due to strict security measures. Additionally, there are hidden safety mechanisms that reduce the model’s performance in certain areas like building language models. Access to Fable 5 requires Usage Credits, which are twice as expensive as Opus 4.8. Fable 5 has strong visual capabilities and leads in processing PDFs, charts, and diagrams. It’s also important to know that inputs and outputs are stored for 30 days, which is relevant for sensitive organizations.

  The video explicitly covers Anthropic’s Fable 5 model and is geared more toward Intermediate users.

• Don’t Use Chatbots Anymore! Skywork 3.0 Tutorial & Guide
  7.6.2026, 16:30:33

  The video introduces Skywork 3.0, a platform described as a “cloud workforce” and more than just another chatbot. Skywork allows users to set goals and execute tasks in the background without technical prerequisites or local setup. The platform offers access to various models like Cloud Opus 4.7, GPT 5.5, and open-source models like Kimmy K 2.5. Skywork 3.0 can create documents, presentations, images, and websites as well as generate videos. The video demonstrates practical examples, such as creating a document about preparing for AGI by 2030, generating presentations about Google DeepMind’s Gemini Science Division, creating images and announcements, and developing a landing page for a brand. The video feature is also demonstrated, which consolidates different models under one interface. Skywork 3.0 thus replaces multiple tools and saves time and money.

  The video explicitly covers Skywork 3.0 and is geared more toward Intermediate users who already have basic knowledge of using AI tools.

• How To Use ChatGPT Memory (Updated Memory Guide)
  6.6.2026, 16:30:21

  The video explains OpenAI’s new Memory system for ChatGPT, which enables relevant and personalized responses. The system automatically remembers context from chats, files, and connected apps, reducing the need to repeat yourself. Users can manage, edit, and update their memory summary in Settings under Personalization. The video shows how to make specific corrections or exclude certain information from future responses. Users can also see the sources of personalization and adjust them as needed. The video also addresses frequently asked questions, such as handling sensitive information, using temporary chats, and the differences between Memory and custom instructions.

  The video explicitly covers OpenAI’s ChatGPT and is geared more toward Intermediate users.

• Meta’s New AI Pendant Set To Shock AI World – Metas AI Pendant Explained
  4.6.2026, 23:00:31

  The video discusses Meta’s plans for a new AI wearable device, a small pendant that continuously records conversations and meetings and organizes them with AI. The technology is based on the acquired startup Limitless and is set to be tested from 2027 onwards. The device fits Meta’s strategy of selling hardware and acquiring users for AI services, but faces major challenges. On one hand, it could boost productivity; on the other hand, there are significant concerns about privacy and data protection. Meta must prove that the device is both useful and trustworthy, particularly in light of past data scandals and regulatory hurdles. The market for always-on listening wearables is difficult, as examples like Humane’s AI Pin and Friend AI demonstrate. Meta could be more successful with a gradual rollout in the enterprise space before tackling the consumer market.

  **Final comment:** The video explicitly covers Meta’s AI models and specific tools like the Limitless Pendant and Humane’s AI Pin, and is geared toward Intermediate users.

Theo – t3․gg (5 new videos)

• Fable is Mythos, and it is really good.
  11.6.2026, 04:06:46

  The video discusses the latest models from Anthropic, particularly Fable 5 and Mythos 5, highlighting their impressive capabilities as well as some challenges. The author shares his experiences with the model, including high costs and limitations from safety measures. He also demonstrates examples of using the model, such as modernizing legacy codebases and creating complex applications like a Minecraft clone and a multiplayer racing game. The author emphasizes the importance of testing the model’s limits and using it for more complex tasks, encouraging viewers to push the model’s potential.

  Final comment: The video explicitly covers Anthropic’s Fable 5 and Mythos 5 models and is more suited for intermediate or advanced users.

• Elon won after all
  9.6.2026, 07:53:14

  The video addresses the current crisis in compute availability, particularly in the AI development space. Major tech companies like Microsoft, Google, and Anthropic are severely affected by this shortage, as demand for GPUs and other hardware components far exceeds production capacity. The reasons for this crisis are multifaceted, ranging from complex supply chains and energy shortages to long lead times for manufacturing new chips. TSMC, the leading semiconductor manufacturer, cannot meet demand fast enough, and production of high-speed memory (HBM) and storage is also severely constrained. SpaceX, which has excess computing power, now sells it to companies like Google and Anthropic, illustrating the industry’s dependence on a few suppliers. Nvidia benefits from the situation as demand for its GPUs remains unabated. The speaker emphasizes that the crisis will likely persist longer and hardware prices won’t decline. The video explicitly covers Nvidia, SpaceX, Google, Anthropic, TSMC, and OpenAI and is more suited for intermediate or advanced viewers.

• I didn’t expect this from Anthropic
  8.6.2026, 11:47:22

  The video discusses potential risks and scenarios of recursive self-improvement in AI systems, based on an Anthropic article. It begins with the question of what happens when AI systems become intelligent enough to improve themselves, presenting concerns associated with rapid, uncontrolled progress (hard takeoff). Anthropic’s article demonstrates that productivity in AI development has been massively increased through the use of AI systems like Claude, leading to an acceleration of AI development. Three possible future scenarios are discussed: progress stagnates, AI development becomes heavily automated but retains human control, or AI systems become fully recursive and self-improving, exceeding human control. The video emphasizes the need to reflect on these developments’ implications and possibly temporarily pause AI development to allow for societal structures and alignment research. It also discusses the difficulty of global coordination and monitoring of such pauses.

  The video explicitly covers AI models and providers from Anthropic (Claude) and is more suited for intermediate to advanced audiences.

• Cloudflare bought Vite to destroy Vercel
  6.6.2026, 20:21:44

  The video discusses Cloudflare’s acquisition of Void Zero, the company behind the popular JavaScript tool Vite. The speaker emphasizes Vite’s significance for web development and the strengths of the Vite ecosystem, such as Vite Test, Rollup, Oxe, and Vite Plus. The acquisition by Cloudflare is presented as strategically sound, as Cloudflare is now able to build a new cloud platform specifically tailored to developers’ and agents’ (AI-powered tools) needs. The speaker highlights how integrating Vite into Cloudflare’s infrastructure significantly simplifies and accelerates application development and deployment. He compares this to the current situation at other platforms like Vercel and emphasizes the benefits of seamless code and infrastructure integration. Additionally, the importance of AI agents for the future of web development is underscored, as they can automate complex tasks and accelerate application development. The speaker also demonstrates an example project called Lakebed, which provides a new abstraction layer for application development and deployment specifically tailored to AI agents’ needs. He emphasizes that Cloudflare’s acquisition of Void Zero strengthens Cloudflare’s market position in cloud platforms and will significantly influence the future of web development.

  The video explicitly covers Vite, Cloudflare, and specific tools such as Browserbase, Infinite Red, and Lakebed. It is more suited for intermediate and advanced developers.

• I miss when programmers were lazy.
  4.6.2026, 23:15:49

  The video discusses the three classic virtues of great programmers—laziness, impatience, and arrogance—and how they are changing in the age of AI. Laziness drives programmers to create efficient abstractions that save time in the long run. Impatience leads them to solve problems quickly and correctly, while arrogance drives them to work on ambitious projects. The author emphasizes that these virtues lead to high-quality software but warns that AI tools like Large Language Models (LLMs) can undermine these virtues. LLMs can generate large amounts of code without regard for quality or maintainability, resulting in bloated and hard-to-maintain systems. The author argues that programmers must continue to bear responsibility for creating simple and efficient abstractions, and that AI tools should only serve as aids in achieving these goals.

  The video explicitly covers Large Language Models (LLMs) and is more suited for intermediate or advanced programmers.

Liam Ottley (1 new video)

• Start a $10,000/mo Solo AI Creative Agency (Higgsfield + Claude)
  8.6.2026, 06:24:52

  **Summary:**

  The video demonstrates how someone can create a complete brand identity, product photos, static ads, commercials, and a backend system for a fictional brand called “Vault” in a single day using two tools (Higgsfield and Claude). The process includes creating branding elements like logos, product images, and packaging designs, as well as producing advertising videos and social media content. Higgsfield is used for image and video generation, while Claude serves as the “brain” of the system, writing prompts, briefs, and copy while orchestrating the entire workflow. Notion is used as the backend to track all clients, ads, and approvals. Appify acts as a live competition signal, feeding new ideas into the client pipeline. The entire process is consolidated into an AIOS (AI Operating System) that enables production of complete advertising campaigns for clients.

  **Final Comment:**

  The video explicitly covers the tools Higgsfield, Claude, Notion, and Appify and is geared more toward intermediate and advanced users.

Productive Dude

No new videos in this period.

Nick Saraev

No new videos in this period.

Leon van Zyl (3 new videos)

• Claude Fable 5 in Claude Code The Hardest Coding Test Yet
  10.6.2026, 12:59:44

  The video demonstrates testing of Anthropic’s new Fable 5 AI model, part of the Mythos class, which achieves 80% on SPEE benchmarks for Agented Coding Tasks compared to Opus 4.8’s 70%. The test involves challenging Fable 5 with a complex project: creating a game with reflections and ray tracing that runs in the browser. The process includes creating a detailed implementation plan and using Claude Code to execute the project in YOLO mode. Fable 5 is slower than Opus 4.8, but the results are impressive. The created game, “Mirror Forge,” demonstrates working reflections and ray tracing, showcasing Fable 5’s capabilities. For comparison, the same test was performed with GPT 5.5, whose results were good but not on the same level as Fable 5.

  Anthropic / Claude / Fable 5 / Intermediate

• Claude Code Dynamic Workflows Explained for Beginners
  9.6.2026, 12:30:55

  The video demonstrates how to create and use dynamic workflows with Claude Code. It explains that Claude Code writes its own orchestration script to distribute tasks across hundreds of parallel-running subagents. The video demonstrates creating a workflow that performs security checks on YouTube videos based on the OWASP Top 10. It emphasizes that dynamic workflows are particularly useful when tasks need to be repeated at scale, and that they are not suitable for simple tasks due to their high token costs. The video provides practical tips on starting, testing, and saving workflows, as well as how to avoid conflicts between agents making simultaneous changes to the same codebase. Finally, it shows how to save a workflow and reuse it in future projects.

  The video explicitly covers Claude Code and is better suited for Intermediate to Advanced users.

• Stop vibe coding. Use this repeatable AI framework instead
  6.6.2026, 09:22:18

  The video introduces a free course called “Seven Day Builder Challenge” focused on agentic coding. The course is based on the Ramp Framework, which consists of four steps: Rules, Augment, Map, and Proof. This framework helps equip agents with rules and skills, create clear structure for problem-solving, and verify results. The course spans seven days, with the first five days teaching the Ramp Framework and the final two days presenting a challenge where participants build their own applications and share them with the community. The course is suitable for both beginners and experienced builders and is tool-agnostic, meaning it can be executed with various coding agents like Cloud Code, Codecs, or Open Code.

  The video covers various AI models and tools like Cloud Code, Codecs, and Open Code and is suitable for both Beginner and Intermediate users.

Tim Carambat (1 new video)

• Google Just Found a Loophole in AI Hardware Limitations
  9.6.2026, 18:00:09

  The video introduces Google’s new Gemma 12B model and its derivative, the 12B QAT (Quantization-Aware Training). The speaker, Timothy Carenbat, founder of Anything LLM, explains that Gemma aims to develop intelligent models for edge devices like laptops and smartphones. The Gemma series models include various sizes, from small multimodal models (E2B and E4B) to larger, compute-intensive models (26B and 31B). The 12B model fills the gap between these sizes and offers improved multimodality by integrating text, image, and audio processing in a single model without requiring separate encoders. This makes it lighter and more efficient to run across a variety of devices.

  The speaker compares the performance of the 12B model with other models like Qwen 3.5 9B and shows that the 12B model performs well on certain tasks despite its lower parameter count. A special feature of the 12B QAT model is the Quantization-Aware Training technique, which enables the model to run with less computational power without significantly losing intelligence. This is demonstrated with an example where the model successfully completes a complex task with multiple tools, such as web scraping, content summarization, and PDF creation.

  The speaker is overall very satisfied with the performance of the 12B QAT model and emphasizes that it offers a good balance between performance and resource consumption. He plans to continue testing the model and report more about the features of Anything LLM in future videos.

  Final comment: The video explicitly covers Google’s Gemma 12B and 12B QAT models as well as a comparison with Mistral’s Qwen 3.5 9B. It is aimed more at intermediate and advanced users interested in local models and their optimization.

WorldofAI (7 new videos)

• Nex-N2 Pro IS GREAT! New Opensource Model Beats GPT 5.5, Opus 4,7, & Gemini 3.5? (Fully Tested)
  11.6.2026, 07:18:33

  The video presents the new open-source model Nex N2 from the Nex AGI Team, which was specifically developed for agentic workflows like coding, research, and tool use. It combines these capabilities in a consistent thinking and action loop that breaks down tasks into sub-steps, adapts strategies, and verifies results. There are two versions: the Nex N2 Mini (35 billion parameters) and the Nex N2 Pro (397 billion parameters), which also supports image inputs. The Nex N2 Pro is currently free and unlimited for two weeks. The model shows impressive benchmark results, but often falls short of official claims in independent tests. It was apparently trained on GPT-like outputs, which is reflected in the results. Despite some weaknesses like slow generation and inconsistent performance, the model is rated as useful and underestimated.

  The video explicitly addresses the Nex N2 model (open-source) and is more suitable for intermediate to advanced users.

• Claude Fable 5 IS INCREDIBLE! Greatest AI Model Ever! (Fully Tested)
  10.6.2026, 00:10:54

  **Summary:**

  The video introduces the latest version of Anthropic’s AI model, Claude Fable 5, which was released as safe for general use. Fable 5 is based on the powerful Mythos model and offers significant improvements in areas such as software engineering, knowledge work, and browser use. The model features a large context window of 1 million tokens and is designed for complex, long-term tasks. It demonstrates outstanding performance across various benchmarks, significantly outperforming other models like GPT-5.5 and Opus 4.8, and sets new standards in areas like coding and vision.

  The creator demonstrates Fable 5’s capabilities through various examples, including creating a Minecraft clone, Mac OS and Windows OS clones, as well as the ability to master Pokémon Fire Red through visual inputs alone. Additionally, excellent performance in frontend development, 3D world building, and other complex tasks is highlighted. The video concludes with a positive assessment of the model and an apology to Anthropic for previous criticism, as Fable 5 significantly exceeds expectations.

  **Closing Comment:**
  The video explicitly addresses the AI model Claude Fable 5 from Anthropic and is more suitable for intermediate to advanced users.

• Claude Fable 5 TOMORROW? GPT 5.6 Kindle, OpenAI IPO News, Gemini 3.5 Pro, Nex-N2, & More! AI NEWS!
  9.6.2026, 07:37:55

  The video provides an overview of the latest developments in AI models and technologies. The key points are:

  1. **Anthropic and Claude Mythos**: Anthropic may soon release the new AI model Claude Mythos, possibly as soon as the next day. There are indications of new checkpoints such as Claude Fable 5 and Claude Fruitcake EAP being connected to Mythos. Poly Market estimates the probability of a release this month at 92%. Leaked outputs demonstrate impressive capabilities, such as completely replicating the game “Cut the Rope” in a single step.

  2. **Google Gemini 3.5 Pro**: There are leaks regarding Google’s new Gemini 3.5 Pro, which continues to suffer from the “laziness” problem, where the model provides incomplete or simplified answers. Google is working on improvements to make the model comparable to GPT 5.6 and Mythos.

  3. **OpenAI GPT 5.6**: OpenAI has tested two new checkpoints, Kepler and Kindle, for GPT 5.6. Kindle appears to be the favored candidate for release and demonstrates impressive capabilities in converting images to code. OpenAI has also filed for an IPO, suggesting a possible near-term public listing.

  4. **Open-Source Models**: The new open-source model Nex N2 demonstrates strong performance across various benchmarks and comes close to models like GPT 5.5 and Opus 4.7. It is agentic and can automatically adjust the degree of reasoning.

  5. **Google Notebook LM**: Google has updated Notebook LM with agentic capabilities and improved research functions. It can now autonomously add relevant web sources and support complex workflows.

  6. **Kimmy for Work**: A new desktop app from Kimmy with agentic capabilities that can run up to 300 local agents in parallel and offers improved browser interactions.

  7. **Apple Siri AI**: Apple introduced Siri AI at WWDC26, enabling deeper OS integration and personal context processing. There is also a collaboration with Google to integrate Gemini models into Apple development environments.

  8. **Humanoid Robots**: A new humanoid robot with magnetic skin and servo-controlled facial expressions was unveiled, raising ethical questions.

  The video explicitly addresses Anthropic, Google, OpenAI, and specific tools such as Kimmy for Work. It is more suitable for intermediate and advanced users as it contains detailed technical information and analysis.

• DeepSeek NEW Desktop App – The 24/7 Self-Evolving AI Agent!
  8.6.2026, 06:03:26

  The video presents a new desktop application called “Deepseek Buy,” specifically developed for use with DeepSeek models. This application transforms DeepSeek from a simple API model into a complete work environment for coding, writing, automation, and long-term AI sessions. The app offers various modes such as code mode for accessing project files and code reviews, as well as a writing mode for working with longer documents. A special feature is the integrated token efficiency mechanism, which enables better context management and higher cache hit rates. The application is cross-platform available for MacOS, Linux, and Windows and offers numerous integrations and tools. Another advantage is DeepSeek’s cost-effective pricing model, which makes using the application particularly attractive.

  The creator emphasizes the importance of code reviews and introduces Test Sprite as a sponsor, an AI-powered testing tool that automatically creates test plans and identifies edge cases that could otherwise reach production. He points out that the application is open-source and not officially from DeepSeek, as well as DeepSeek’s privacy policy, which states they train on user data.

  Installing the application requires NodeJS 20 or higher, a paid DeepSeek API key, and internet access for initial setup. The creator demonstrates the installation and configuration of the application and shows its features, including creating a frontend layout with minimal costs. He praises the efficiency and capabilities of DeepSeek models and recommends the application as a cost-effective alternative to other proprietary AI working environments.

  Closing comment: The video explicitly addresses DeepSeek, an open-source desktop application called Deepseek Buy, and is more suitable for intermediate and advanced users.

• Claude Mythos 5 LEAKED & IS Coming Sooner Than Expected & GPT-5.6 Checkpoint Out! Huge AI News!
  7.6.2026, 06:44:20

  The video discusses recent developments in AI models and tools. Here are the key points:

  1. **Anthropic Mythos 5**: A leaked model that may be released soon, possibly even this month. It could be a new model class standing alongside the existing Haiku, Sonnet, and Opus families. Anticipated prices are five times higher than Opus 4.8, suggesting significant performance improvements. The model demonstrates impressive capabilities, such as creating a complete Minecraft clone with multiplayer functionality, generating music, and replicating complex websites.

  2. **OpenAI GPT 5.6**: New checkpoints named Kelpar Alpha and Kindle Alpha have been introduced, with the latter selected as the release candidate. The models show improved capabilities in frontend development and other complex tasks. Release could occur later this month.

  3. **DeepSeek**: The company is working on a new GUI that could improve user-friendliness and productivity for power users. A native app could facilitate use for coding, research, and daily productivity.

  4. **Artificial Arena Purple**: A new, powerful video model discovered in Artificial Arena. It demonstrates impressive capabilities in creating realistic animal videos and following text instructions. It could be an omni-model from Google.

  5. **UWorld U1 Companion Humanoid**: A new humanoid robot with emotional AI that learns through daily interactions. The robot has already received over 1,000 pre-orders and raises questions about the future of AI companions.

  The video explicitly addresses AI models and providers Anthropic (Mythos 5), OpenAI (GPT 5.6), DeepSeek, and Google (Omni model). It is more suitable for intermediate and advanced users as it contains detailed technical information and analysis.

• Gemma 4 12B Is INCREDIBLE! BEST Local AI Coding Model! IS POWERFUL! (Fully Tested)
  6.6.2026, 07:18:22

  The video introduces Google’s new Gemma 4 12B model, designed as a powerful multimodal model for local deployment on consumer hardware. It fills a gap in the Gemma family between small edge models and larger workstation models. The model is encoder-free, meaning it processes text, images, and audio directly without separate encoders. This reduces memory requirements and latency while still delivering competitive performance. On a 24 GB GPU, the model runs approximately 75% faster than the larger 26B MoE model and supports a context window of up to 250K tokens. Despite some limitations compared to larger models like the Qwen 3.6 35B A3B, the Gemma 4 12B offers an excellent balance between performance and practicality for consumer hardware.

  The video also shows how the model can be used in various applications such as creating frontend designs, Minecraft and operating system clones, as well as SVG and 3JS generation. It emphasizes that the model is surprisingly good at code generation and logical reasoning, even though it is not the best model for these tasks. The video recommends the model for users with approximately 12 GB VRAM seeking modern local AI for coding, vision, audio, and 3JS generation.

  **Closing Comment:** The video explicitly addresses Google’s Gemma 4 12B model and is more suitable for intermediate to advanced users.

• Claude Oceanus, Anthropic AGI Claims, GPT-5.6 Checkpoint, GLM 5.2, Nemotron 3 Ultra & More! AI NEWS!
  5.6.2026, 07:27:15

  The video provides a comprehensive overview of the latest developments in AI technology. It begins with leaks of Anthropic’s new Mythos model, which shows impressive outputs and potentially revolutionary capabilities. Anthropic is already working on a successor called Oceanus, which could be even more powerful. Meanwhile, OpenAI has introduced a new GPT-5.6 checkpoint named Jewel Alpha, delivering impressive results in SVG generation and frontend development. Google has released Dream Beans, a personalized storytelling tool, as well as the Gemma 412B model, a powerful multimodal AI model. Nvidia has introduced Nemotron Ultra, a model for long-running AI agents that offers up to five times faster inference and 30% lower costs. Additionally, a new benchmark tool called Agent Arena was introduced to measure AI model performance on real-world tasks. The video also addresses the challenges of verifying AI-generated code and presents Test Sprite as a solution. It also points to the potential recursivity of AI development, where AI systems are increasingly capable of developing their own successors.

  The video explicitly addresses Anthropic, OpenAI, Google, Nvidia, and specific tools such as Test Sprite, Dream Beans, Nemotron Ultra, and Agent Arena. It is more suitable for intermediate and advanced users as it provides in-depth technical details and analysis.

AI and Strategy | Le SamourAI (1 new video)

• Claude Fable 5 : who wins, who loses, and what to do before June 23
  11.6.2026, 14:50:17

  # Summary

  The transcript is fragmented and contains an obviously incomplete or faulty recording at the end with conversation snippets that don’t thematically fit the rest.

  The main part analyzes Claude 3.5 Sonnet (Fable 5) from Anthropic from a financial perspective. Central thesis: The real reason behind Anthropic’s recent actions is not safety, but economics. The author verifies a prediction from April – that the price multiplier ratio between Opus 4.8 and the new model would drop from 5x to 2x – and confirms it exactly: Fable costs $10/million input tokens vs. $5 for Opus, thus factor 2.

  **Core observations on Fable:**
  – Massively improved performance on autonomous missions over hours without manual intervention
  – A test mission (2h30) consumed 45 million tokens in context and cost ~$200
  – The model was trained with Reinforcement Learning on real Claude Code sessions, optimizing it for real engineering work

  **Economic reality:**
  – Anthropic’s “profitability” (559M of 11B = 5% margin) relies on temporary discounts for Memphis data center (until June)
  – From June 23, Fable will be removed from unlimited subscriptions and billed only by token consumption
  – This is not a technical necessity, but financial strategy ahead of IPO filing (June 7)
  – Microsoft, Uber and other tech giants are already capping their token spending and building local alternatives

  **Structural squeeze:**
  Below, free Chinese models are rising in quality; above, pressure for IPO profitability is pressing down. Anthropic is compressed and uses metering as its only way out.

  **Practical advice:**
  1. Learn routing – use the most cost-effective option depending on the mission
  2. Build alternatives (local models, other providers)
  3. Exploit the last week of Fable subscription access (until June 22) for real tests to measure ROI

  The video also criticizes Anthropic’s security narrative from June 4 (warning of “uncontrollable” AI, calls for global freeze) as strategic marketing theater that came 3 days after IPO filing.

  —

  **Tool and audience:** Claude 3.5 Sonnet / Anthropic; intended more for Advanced users (CFOs, tech leaders, engineers with high budget awareness), but also important for beginners as a warning signal.

Matt Pocock (1 new video)

• Learn anything with the /teach skill
  8.6.2026, 17:07:15

  The video introduces a custom-built “Teach Skill” that enables users to independently learn various topics. The focus lies on distinguishing between stateful and stateless Skills, with “Teach” designed as stateful to store learning progress and offer personalized lessons. The user demonstrates the application using learning how to solve a Rubik’s Cube as an example. The Skill creates a mission, gathers resources, generates interactive lessons in HTML format, offers quizzes, glossaries, and cheat sheets, and adapts to learning progress. It utilizes the concept of “Zone of Proximal Development” to optimally calibrate the learning material. The Skill is installable via the Skills repo from mapper.kills and can be used in various contexts, such as onboarding into codebases or learning new skills.

  The video explicitly addresses the use of Opus 4.8 and is aimed at intermediate to advanced users who are engaging with the development and application of AI Skills.

Coding with Lewis (2 new videos)

• Python’s Name Has Nothing to Do With Snakes
  10.6.2026, 16:04:11

  The video tells the story of how the Python programming language came into existence and how it got its name. Guido van Rossum started developing Python in 1989 during his Christmas break in the Netherlands. Inspired by the comedy show “Monty Python’s Flying Circus,” he chose the name Python because he wanted to create a fun and easy-to-use scripting language. References to Monty Python are deeply embedded in the language, such as the use of “spam” and “eggs” in the official documentation and the name of the Python Package Index, “cheese shop.” The language was designed to feel playful and human, with readable error messages and Python-like pseudocode syntax. Today, Python is used worldwide for various applications such as machine learning, web servers, data pipelines, and automation scripts. The video emphasizes that programming doesn’t have to be serious and shows how Guido van Rossum proved this with Python.

  The video covers the Python programming language and is more suitable for beginners and intermediate learners.

• The Creator of MySQL’s Wants to Replace It
  4.6.2026, 16:36:17

  The video tells the story of Michael Widenius, the creator of the popular database MySQL, which he named after his daughter My. After MySQL was sold to Sun Microsystems and subsequently acquired by Oracle, Widenius feared that MySQL would be neglected or discontinued in favor of Oracle’s own database. He then forked MySQL into MariaDB, named after his other daughter Maria, to ensure continued development independently of Oracle. Despite Oracle’s promises to keep MySQL alive, the community version lost features that were only available in the paid Enterprise version, and community participation declined. MariaDB, on the other hand, gained popularity, remained compatible with MySQL, and was adopted by major companies like Wikipedia and Google as well as many Linux distributions. However, in 2024, MariaDB was acquired by a private equity firm, raising similar concerns as Oracle’s acquisition. A curious aside is that Widenius also named a database MaxDB after his son, suggesting he won’t name any more databases after his children, since he has only three.

  The video covers the databases MySQL, MariaDB, and MaxDB and is intended more for intermediate viewers interested in the history and development of databases.

Julian Goldie SEO (10 new videos)

• Claude Video Just Changed Content Creation Forever…
  11.6.2026, 09:00:37

  The video demonstrates how to transform Claude, an AI model, into a powerful video agent capable of creating and editing videos. The process is explained step-by-step using a system called “Goldie Neon Forge.” This system enables video generation with just a single prompt. The video agent can create scenes, transitions, and effects using a free open-source capability called HyperFrames. The video showcases various examples of generated videos and explains how to train the agent to utilize these capabilities. It also demonstrates how to organize generated videos in a project area and edit them later. The creator emphasizes the benefits of using an AI agent over traditional video editing methods, such as the ability to continuously create engaging content without fatigue.

  The video explicitly covers Claude and HyperFrames and is geared more toward intermediate or advanced users.

• NEW Hermes Profile Builder Update is INSANE!
  11.6.2026, 06:05:54

  The video introduces Hermes’s new agent profile builder, which allows you to create and manage multiple profiles or identities for AI agents. These profiles include names, descriptions, models, skills, and MCP servers. The builder enables you to create autonomous teams of AI agents that collaborate and complete tasks. A practical example demonstrates how four different agent profiles are deployed for SEO tasks such as keyword research, content creation, and internal linking. The agents can be coordinated and monitored via a Kanban board, with each agent possessing specific skills and expertise. The advantages of this builder include rapid agent profile creation, individual communication with each agent, and orchestration of agent teams for complex tasks.

  The video explicitly covers Hermes and is geared more toward intermediate or advanced users who already have experience with AI agents.

• New Google AI Studio Managed Agents Are INSANE!
  11.6.2026, 05:00:34

  The video introduces new Managed Agents in Google AI Studio, which allow you to create a fully functional AI agent with a single command. These agents come with their own cloud computers running Ubuntu Linux with four CPU cores and 16 GB of RAM, managed by Google. The agents can independently perform tasks like research, web search, file creation, and code execution without requiring the user to have technical knowledge. The process is simple: the user provides instructions in plain English in two text files (agents.md and skill.md), and the agent executes the tasks. Google AI Studio offers a user-friendly interface to create and manage these agents without writing any code. The agents can also be reused and customized for specific tasks, making them particularly useful for business owners who want to automate repetitive tasks. The video emphasizes the simplicity and efficiency of this technology and encourages viewers to try it out and integrate it into their business processes.

  Final comment: The video explicitly covers Google AI Studio and the Gemini API and is aimed at intermediate users who want to leverage the new Managed Agents for their business processes.

• Building with Claude Fable 5 + Agent OS
  11.6.2026, 03:59:11

  This video demonstrates the use of Hermes agents for various tasks and projects. The creator shows how he creates multiple Hermes profiles and has them work together as a team to create and publish SEO-optimized blog posts. Various agents are deployed for specific tasks such as keyword research, content creation, and link building.

  Another focus is on the use of Hyperframes, an open-source tool integrated into Hermes agents to generate videos. The creator demonstrates how videos can be created and enhanced based on ideas. It also showcases the integration of 11 Labs for voice capabilities and the use of Obsidian for knowledge organization.

  Additionally, various models and tools such as Claude Fable 5, Gemini, and open-source models are discussed. The creator shares his experiences with these tools and provides insights into the advantages and disadvantages of using them.

  The video is suited more for intermediate to advanced users, as it covers advanced concepts and techniques for automating and integrating various AI tools. (Claude / OpenAI / Gemini / Open-Source / specific tools such as Hermes, Hyperframes, 11 Labs, Obsidian)

• NEW Claude Fable 5 AI SEO Agent!
  11.6.2026, 03:00:05

  The video demonstrates the use of Claude Fable 5, a new model from Anthropic, for AI SEO within an Agent Operating System. The creator, Julian Goldie, demonstrates how the system can analyze a website, identify keywords, and create content that ranks well in both Google and AI search results. The process includes keyword research, writing articles based on real case studies, and automatic publishing across multiple websites. The system also uses a tool called Index Exceptional to accelerate Google indexing. Goldie emphasizes that Claude Fable 5 is currently available for free until June 22 and that his Agent Operating System can be obtained through the AI Profit Boardroom.

  The video explicitly covers Claude Fable 5 and is aimed more at intermediate to advanced users who are familiar with SEO and AI technologies.

• PewdiePie’s Odysseus VS Hermes VS OpenClaw: Who wins?
  11.6.2026, 15:15:26

  # Three Open-Source AI Tools Compared: Odysseus, Hermes, and OpenClaw

  The video compares three free open-source AI tools that went viral on GitHub and serve similar purposes in different ways.

  **Odysseus** is a fully local AI workspace where models and data remain entirely on your own machine. The tool scans your hardware and shows which models can run locally, performs in-depth research, and can triage emails. It’s described as the most comprehensive all-in-one system.

  **Hermes** runs in the terminal and functions as an agent that “learns” the user. The tool remembers conversations from weeks ago, develops its own skills, and can perform tasks in the background while notifying the user via Telegram or Discord.

  **OpenClaw** is the most beginner-friendly tool and works directly via WhatsApp or iMessage like a real assistant. It controls the browser, executes commands, and offers a marketplace with community-created skills.

  The recommendation: Odysseus for a complete local workspace, Hermes for an agent that grows with you, OpenClaw for quick mobile use. Users can deploy all three simultaneously.

  Focus on three specific open-source tools (Odysseus, Hermes, OpenClaw); target audience is more intermediate to advanced users familiar with local AI solutions and automation.

• Hermes Agent: How to Build Apps in 1 Click!
  11.6.2026, 15:00:24

  # Summary: AI App Builder with Hermes Agent

  The video presents a system called “Goldie Spark Forge” – an agent-based framework for ideation and app development in a single click. The core functionality operates in three steps: first, an idea is entered in the “Idea Factory,” AI agents plan it and you can approve or reject it, then the app is implemented – typically in 3–5 minutes per app.

  The idea generation process uses a group chat where Claude, Hermes, and other agents communicate with each other to develop new ideas. These agents have access to an Obsidian Memory Vault where all previous projects are automatically organized. This allows the agents to reference earlier work and suggest relevant new ideas that are then automatically fed into the build pipeline.

  The pipeline operates on a Kanban-like model: Idea → Approval → Planning with Subtasks → Implementation by Coding Agents → Finished App. Created apps are collected in a gallery, searched, and recreated as needed. The system leverages various available APIs – including free ones – so there are no expensive token costs. You don’t need to be a developer; the work consists of steering ideas and controlling quality.

  The creator emphasizes that the system solves problems like lost ideas in notebooks, lack of implementation, dependence on developers, and poor project tracking. All created apps are functional, production-ready, and viewable from a single location. The entire system is part of the “AI Profit Boardroom,” a community with over 3,500 members who receive daily updates, coaching calls, and access to all prompts, the Obsidian setup, and video tutorials.

  **Mentioned AI Tools:** Claude, Hermes, Gemini, open-source connections suggest a custom agent OS; costs utilize free APIs and local models. **Target Audience:** Intermediate to Advanced (requires some technical foundation for setup but no coding knowledge for use).

• New NotebookLM Update Is INSANE!
  11.6.2026, 13:45:49

  Google Notebook LM has been expanded into a comprehensive content factory. The tool accepts notes and generates multiple formats from them: podcasts, videos, slide decks, or complete reports – each in seconds, with source citations and quotes to eliminate hallucinations.

  For videos, the new cinematic tool runs three AI models in parallel to transform notes into smooth video narration. For organization, you get mind maps, flashcards, quizzes, briefing documents, and study guides – all based on your uploaded content. Generated outputs can be directly exported: decks to PowerPoint, reports to Google Docs, tables to Google Sheets. A practical tip: instead of using the standard formats at the top, scroll to the suggested formats, which deliver significantly better results.

  The video presents Google Notebook LM as a generalist content-generation tool with a focus on source fidelity; addresses beginner to intermediate users who want to quickly generate multiple formats from one piece of content.

• How I Run My Entire SEO From One Dashboard
  11.6.2026, 13:00:32

  # Summary: Running SEO from a Single Dashboard

  The video shows how Julian Goldie runs his entire SEO system from a single dashboard instead of bouncing between many tools as is typical. The core problem: traditional SEO workflows fragment across different tools and platforms (keyword research, writing, internal linking, publishing), leading to friction and ultimately consistency issues.

  His solution is an **Agent Operating System** with the core framework called “Ranking Engine.” Specialized AI agents work together, with each agent fulfilling a task and passing the result to the next agent. The system is built on **Hermes**, a free open-source agent (by News Research) available via Open Router. The crucial step above all else: **build a memory layer** – in his case with Obsidian, a knowledge vault with notes about the business, goals, and projects. The agents read this vault before becoming active, so they deliver contextualized rather than generic results.

  **Practical Workflow**: He enters a keyword and a case study, the agent generates five unique blog posts from different angles and deploys them directly via Netlify API across five websites – all without manual publishing. He calls this the “One-to-Five System.”

  Additional agents in the system:
  – **Image Agent**: Generates images for Google image search
  – **Video Agent**: Uses Hyperframes (free, open-source) to generate HTML-based videos and render them as MP4
  – **Audio Agent**: Connected to Notebook LM via MCP server, produces podcast-like audio summaries

  **Strategic Background**: Search is changing. Instead of ranking in position one, it’s about being cited by AI systems (Google AI Overviews, other AI searches). You achieve this through **omnipresence**: covering a topic across multiple surfaces (blog, video, image, audio, community). This only works if everything operates from a single system with shared memory logic.

  Concrete Results: Two of his sites grew from zero to approximately 190 and 67 clicks/day respectively – though he emphasizes the growth happened recently and SEO is not a linear process.

  Core Concept: SEO doesn’t fail due to talent but due to volume. Most people can’t sustain consistency because the manual effort is too great. A dashboard reduces that effort to nearly zero.

  The main lever is **Hermes** (free, open-source agent) combined with a **memory infrastructure** (Obsidian) and **API connectors** to publishing platforms – the video targets advanced users/agencies wanting to automate SEO.

• 5 FREE Hermes Agent Use Cases!
  11.6.2026, 11:00:35

  **Hermes Agent – Five Practical Use Cases**

  Hermes Agent is an open-source, free AI agent system by News Research that runs on your own server or computer rather than being just a chat interface. Unlike typical AI chatbots, Hermes doesn’t forget – it stores information persistently, develops its own skills, and becomes smarter the longer you use it. Access is via Telegram, Discord, Slack, WhatsApp, Signal, Email, or Terminal; Hermes can execute tasks on a schedule, spawn multiple helper agents, and runs on your laptop, server, Docker, or via SSH.

  **The Five Shown Web Page Builds:**

  1. **SEO ROI Calculator** – an interactive HTML page with input fields for traffic, conversion rate, and average order value
  2. **Landing page for free SEO audit** – with headline, benefits section, form, testimonials, FAQ, and call-to-action buttons
  3. **Website for AI automation agency** – single-page with services, case studies, pricing, and contact form
  4. **Savings calculator** – a page showing businesses how much time they save with automation
  5. **Pricing page** – three pricing cards side by side, feature comparison, FAQ, and sign-up buttons

  Each page emerged from a single prompt with no coding knowledge required. Hermes stores its memory in simple Markdown files locally and maintains a fully searchable history of all previous chats – the agent history is readable and transparent. Installation happens via desktop installer (under 2 minutes) or individual command-line commands; you can switch between hundreds of models without rewriting code. The video recommends beginners start small, use plain English, and run the `Hermes doctor` command if something doesn’t work.

  **Conclusion:** Focus on open-source (MIT license), multi-model support (OpenRouter, OpenAI, Hugging Face, etc.) with one-time setup; video targets beginners to intermediate users and promotes accompanying coaching and prompt packs.

Kyle Balmer | AI with Kyle (8 new videos)

• Learning to use AI is primarily about communication – we still need to be able to explain what we
  8.6.2026, 20:43:33

  The video addresses the challenges and opportunities associated with implementing AI in businesses, particularly for non-technical people. The main focus is on the importance of communication, as many people struggle to articulate their ideas clearly and precisely – a skill that is crucial for effective AI use. The speaker emphasizes that people who master these communication skills are better equipped to use AI tools successfully. Interestingly, these skills – such as analysis, information synthesis, public speaking, and writing instructions – are exactly those that AI might diminish. However, this also presents an opportunity for entrepreneurs, as the need for people with these skills remains high while supply might decline.

  The speaker does not mention specific AI tools or models, instead focusing on general principles and skills important for AI use. The video is geared toward Intermediate and Advanced users, as it concentrates on the strategic and communicative aspects of AI usage.

• AI SEO: How to Show Up in ChatGPT & AI Overviews
  8.6.2026, 05:00:18

  The video addresses how to gain visibility in the AI era, particularly in chatbots and AI Overviews. It emphasizes that traditional search engine optimization (SEO) must increasingly be complemented by AI-optimized strategies, as AI systems like ChatGPT and Google’s AI Overviews play a growing role in information retrieval.

  Key points include:
  – **Content and Formats**: AI systems prefer structured content, particularly “Best X” lists (e.g., “The Best 10 Surfboards”). These account for 43.8% of pages cited by ChatGPT.
  – **Website and Blog**: Your own website remains important, especially with well-structured blog articles in list format.
  – **External Sources**: 67% of ChatGPT’s top citations come from sources marketers cannot directly control, such as Wikipedia. Nevertheless, controllable content like blog posts and case studies are also crucial.
  – **YouTube**: Mentions on YouTube have the highest correlation with AI visibility. Both your own videos and guest appearances on other channels are valuable.
  – **AI Overviews**: These significantly reduce clicks to organic search results, which could be a long-term problem for websites relying on traffic.
  – **Technical SEO**: Schema markup and similar techniques have minimal impact on AI citations. What matters more is creating valuable and helpful content.

  The video concludes with practical tips such as optimizing your homepage, creating guides and case studies, leveraging customer reviews, and increasing your presence on YouTube.

  The video explicitly addresses ChatGPT, Claude, Gemini, and YouTube, targeting Intermediate users.

• The hard part of starting a business was never the product
  7.6.2026, 18:45:17

  The video discusses the shift in entrepreneurship, particularly through the removal of technical barriers. In the past, many ideas failed due to the need for a CTO, funding, or programming skills, which led to a culture of “wantrepreneurs” – people with ideas who never implemented them. With tools that enable rapid code generation (“vibe code”), ideas can now be executed within a day. This results in many discovering that their ideas are not viable or lack market demand. Responsibility now rests with individuals, as there are no more excuses. The focus shifts from the idea itself to actual execution and quality.

  The video addresses generic AI code tools and is geared toward Intermediate and Advanced users.

• Ethan Mollick’s new book cover has been revealed
  7.6.2026, 12:42:25

  The video discusses the intentional use of six fingers in a book cover graphic created by Ethan Mollick for “Coexistence”. The narrator emphasizes this is a humorous nod to AI models’ difficulties in generating realistic hands. Interestingly, the template for this depiction comes from the Sistine Chapel, with the hand in the graphic mirroring God’s hand. This is interpreted as a symbolic representation where AI assumes the role of God. The narrator highlights the intent and irony of this portrayal without offering direct judgment.

  The video addresses AI-generated art and is geared toward Intermediate or Advanced users.

• can Codex replace openclaw? yeah pretty much
  5.6.2026, 18:44:25

  The video demonstrates how the user employs the AI app “Code it” as a replacement for “Open Claw”. He describes setting up a Mac mini as a central server where he runs main threads and cron jobs while controlling them from his laptop and phone. A special thread called “Daily Pulse” checks tasks hourly, performs research, and sends reports. Additionally, he explains how to integrate images and videos into workflows, for example to transcribe audio and generate Instagram covers. The user emphasizes that “Code it” increases his productivity since he spends less time on setup and more on actual work.

  The video explicitly addresses the AI app “Code it” and is geared toward Intermediate users.

• Learn how to teach AI to businesses and earn $1000/hour
  5.6.2026, 11:45:07
• i rarely give AI book recommendations
  5.6.2026, 11:42:05

  The video argues that writing and publishing books about AI is futile due to rapid developments in the field. Books cannot keep pace with AI evolution, as the process from creation to publication is too slow. An exception is Ethan Mollick’s book “Co-Intelligence”, which is called a masterpiece and conveys an intuitive grasp of the technology. The speaker announces that Mollick will release a new book on October 20th, which he has already pre-ordered. Once he receives a copy, he plans to create a video review or even a mini book club about it, as Mollick’s books are considered the best in this space.

  Ethan Mollick and his new book; geared toward Intermediate and Advanced users.

• How To Get Paid For AI
  5.6.2026, 05:00:01

  The video addresses the importance of public speaking (or “yapping”, as Gen Z calls it) in an era where artificial intelligence increasingly takes over tasks like writing and design. The speaker argues that AI pushes people toward areas where they excel, such as authentic speaking and community building. He emphasizes that polished, professionally-produced content is often perceived as AI-generated and thus generates less engagement. Instead, people should create raw, authentic content to build trust and authority.

  The speaker suggests a gradual approach to developing public speaking skills: starting with short videos on platforms like TikTok and Instagram, then live streams, followed by structured talks like webinars, and finally on-stage performances. He cautions against using AI tools like avatars or voice clones to fully replace yourself, as this undermines authenticity and floods the market with such content.

  The speaker also shares his personal strategy for building a business through content creation and public appearances by first offering free workshops and then conducting paid workshops for companies. He emphasizes the importance of focusing on a specific niche and continuously practicing to improve.

  At the end, he encourages viewers to simply start with their smartphone and regularly create videos to develop the habit of public speaking. He refers to his webinars and newsletter for additional information and resources.

  The video does not address specific AI tools or models and is geared toward Intermediate and Advanced users.

David Shapiro (3 new videos)

• Nobody gets this right
  7.6.2026, 11:44:08

  The video discusses the concept of “World Models” and contrasts it with “Language Models.” The speaker argues that the difference between these models is more gradual than fundamental. He emphasizes that language models are not based solely on text, but are increasingly trained on multimodal data such as audio, video, and images. This development leads to “Omni-Models” capable of processing both abstract and sensory data.

  The speaker addresses various online discussions and refutes some common claims that limit the capabilities of language models. He argues that these models can predict not only the next word but also complex physical and sensory data. He points to advances in robotics and other fields that demonstrate these models are already capable of operating in the physical world today.

  Additionally, the speaker criticizes the notion that World Models must rely exclusively on sensory data. He emphasizes that cognitive architectures have existed since the 1970s and that these models are capable of integrating various data streams. He concludes by stating that the future of AI lies in integrating these different approaches.

  At the end of the video, the speaker mentions his current projects, including a book about the future of work and the psychology of life after work. He encourages viewers to subscribe to his Patreon and Substack pages to stay updated.

  Final comment: The video discusses OpenAI and Nvidia and is geared toward intermediate and advanced audiences.

• Bernie’s plan sucks, actually
  5.6.2026, 11:56:20

  The video discusses Bernie Sanders’ proposal to create a state fund for artificial intelligence that would acquire 50% of shares in leading AI companies like OpenAI, Anthropic, and XAI. The speaker analyzes the pros and cons of this plan and contrasts it with an alternative, more realistic model.

  Sanders’ argument is based on the idea that AI companies benefit from publicly funded research and collective knowledge without adequate compensation. He proposes creating a state fund to control these companies and distribute profits to the population. The speaker’s main criticisms are:

  1. **Expropriation and Constitution**: The proposed seizure of 50% of corporate shares is constitutionally problematic and could prompt companies to relocate abroad.
  2. **Governance and Control**: The proposed active state control is risky and could lead to political interference.
  3. **Objectives and Implementation**: Focusing on a few large companies is not effective. Instead, a broader spectrum of tech companies and infrastructure should be considered.

  As an alternative, the speaker proposes a passive governance model in which the state acquires up to 10% of shares in various companies without exercising active control. Revenue should be distributed directly to citizens or invested in public infrastructure.

  The video explicitly addresses OpenAI, Anthropic, XAI, Microsoft, Google, Amazon, Nvidia, Coreweave, TSMC, and ASML. It is geared toward intermediate and advanced viewers, as it contains detailed economic and political analysis.

• This is my next big work
  11.6.2026, 12:42:55

  # Summary: A Realistic Theory of Rights After Automation

  The author introduces his next major project: a “realistic theory of rights” (Credible Threats), building on his work in post-labor economics. His central thesis: when automation and AI render human labor obsolete, people lose their historical bargaining power—and thus the foundation for democracy and human rights.

  **The Problem:** Human labor was the foundation of civilization because it bundled several unique properties: it is embodied, necessary, collectible (strikes), non-storable, universal, geographically fixed, and specialized. This gave people a “credible threat”—the capacity to refuse. Simultaneously, individual income generates roughly 80% of U.S. federal revenue. Yet with automation, this double bilateral dependence collapses: elites no longer need people, and people have no credible threat.

  **The Theoretical Foundation:** The author argues through “Generative Mutualism”—cooperation inward to manage competition from outside (from endosymbiosis to multicellularity to human societies). This cooperation functions through “credible threats”—the capacity and demonstrated willingness to impose intolerable costs. Historically, rights (voting rights, the five-day workweek, women’s rights) were won through “forced concessions”: elites grant rights only when suppression costs exceed concession costs.

  **The Core Problem:** History shows an invariant pattern: in times of labor shortage (e.g., after the plague), people were valuable and treated well. With labor surplus but still-needed work, people were treated as replaceable. With complete automation comes absolute irrelevance—not merely “techno-feudalism” (where elites still need subjects), but total economic uselessness.

  **The Solution:** Germany points a way (Article 1 of its Constitution: human dignity is inviolable). But morality without enforcement power is mere pleading. People need new veto power—new ways to halt production (shut down data centers, power grids), destroy value, and assert property claims. This could happen through tax resistance, general strikes, and labor strikes.

  **Empirical Chances:** While violent resistance succeeds only 26% of the time, nonviolent resistance achieves a 53% success rate. India has seen 250-million-person strikes. The threshold: 3.5% active participation in coordinated resistance has historically never failed. The U.S. currently has 83.8% labor force participation—theoretically maximum leverage, but “labor is a depreciating asset.” The question is: how much time remains? 5–20 years or decades—no one knows.

  **His Project:** The author is working on three books: *Post-Labor Economics* (household income reform, partly complete), *Labor Zero* (due 2024, 190,000 words, addressing the loss of labor as leverage) and *Credible Threats* (currently draft 5–6, 190,000 words, concrete historical examples of successful and failed resistance forms). He funds himself entirely through audience support (Patreon, Substack, X), has no publisher mandate, and is also developing courses for monetization.

  The lecture focuses heavily on game theory, historical examples, and institutional mechanics—not technical AI details, but rather the political structures necessary after the loss of labor.

  **Target Audience:** Intermediate to Advanced (requires familiarity with game theory, political science, and historical examples); explicitly mentions no tool names or AI vendors—pure political-economic analysis.

AI News & Strategy Daily | Nate B Jones (10 new videos)

• Fable 5 is here—but who is it for? #ai #anthropic #shorts
  11.6.2026, 03:00:37

  The video discusses the launch of Fable 5, a new powerful AI model from Anthropic. The focus is not on whether the model is smarter, but whether users have tasks large enough to match its capabilities. Many use AI for small tasks like text editing or document summarization. The real skill gap lies in imagining tasks that are large, specific, and valuable enough to delegate to such a model. The speaker challenges viewers to share such tasks in the comments to demonstrate how to effectively delegate them to Fable.

  The speaker explicitly addresses the new Fable 5 AI model from Anthropic and targets intermediate to advanced users.

• Stop Picking Between Claude Code and Codex | Do This Instead
  10.6.2026, 14:00:38

  The video discusses the comparison between Claude Code and Codex, two tools for agent management, emphasizing that the question shouldn’t be which tool is better, but which tool enhances which capabilities when working with agents. Claude is described as more natural for steering agents, while Codex is better suited for dispatching agents. The author explains that both tools foster different work habits and that these differences could matter more than benchmark tests. Claude feels like a cockpit where the user stays close to the model and closely monitors work, while Codex feels like an operations center where multiple tasks can be handled in parallel. Both tools have their own advantages and disadvantages, and the author recommends using both depending on the task type. He emphasizes that the ability to effectively manage agents represents a new form of computer literacy and that both tools will shape how we work with agents.

  The video explicitly addresses Claude and Codex and is aimed at intermediate and advanced users.

• Siri isn’t the real headline at WWDC #apple #ai #wwdc (Full Video Thursday)
  9.6.2026, 19:00:24

  The video covers WWDC (Apple Worldwide Developers Conference) from June 8 and argues that discussions about Siri improvements and Apple’s position in the AI software race distract from the real important announcements. The focus is on why Jensen Huang from Nvidia should pay close attention to WWDC, despite it being a software conference. The author suspects that Apple’s announcements are closely tied to Nvidia’s strategy, particularly the announcement of a laptop chip. The video promises to analyze all major WWDC announcements and their significance for Apple’s overall strategy, as well as address the question of who will be the first trillionaire in AI history.

  The conclusion: The video addresses Apple and Nvidia and is aimed at intermediate and advanced viewers.

• Fix your operating model or lose at AI #ai #strategy
  9.6.2026, 03:00:35

  The video discusses the challenges and responsibilities of leaders in deploying agents in enterprises. It emphasizes that responsibility for slow agent implementation progress lies not with employees but with leaders. They must ensure clear communication about tasks and opportunities and create the necessary framework to establish end-to-end agent pipelines. A piecemeal approach to problem-solving is criticized because it leads to downstream problems that feel like playing with Band-Aids. Instead, a holistic approach should be pursued that enables the system and people to learn and improve together.

  The video addresses general principles of agent implementation and is aimed at intermediate to advanced users, as it assumes foundational knowledge of agents and change management.

• Beyond The Hype: Why Meta And Block Are Firing People
  8.6.2026, 14:00:32

  The video discusses the various reasons behind so-called “AI layoffs” and warns against treating all layoffs as part of a single unified phenomenon. Instead, it distinguishes five categories of layoffs:

  1. **Hyperscaler Layoffs (e.g., Meta)**: Large tech companies like Meta lay off employees to justify their massive GPU and data center investments. Simultaneously, they try to defend their AI strategy and secure market share. For job seekers, such companies are risky since layoffs can be frequent and unpredictable.

  2. **Visionary Leader Layoffs (e.g., Block/Jack Dorsey)**: Companies with visionary leaders like Jack Dorsey lay off employees to fundamentally rethink their AI strategy. What matters is whether these leaders take seriously the human and organizational implications of AI transformation. Job seekers should check whether the company’s vision is clear and whether they’re prepared to handle this uncertainty.

  3. **Usage-Based Layoffs (e.g., Cloudflare)**: Some companies justify layoffs with increased AI usage without presenting clear outcomes. Such layoffs often signal strategic uncertainty. For job seekers, these companies are a red flag.

  4. **Hope-Based Layoffs (e.g., Cisco)**: Companies without a clear AI strategy use layoffs to signal transformation. These layoffs often indicate disorientation and should be viewed cautiously by job seekers.

  5. **Non-AI Layoffs**: Many layoffs have nothing to do with AI but stem from general economic problems or overstaffing.

  The video advises leaders to understand the various reasons behind AI layoffs to make strategic decisions. Job seekers should carefully examine the backgrounds of layoffs at potential employers.

  The video explicitly addresses Meta, Block/Jack Dorsey, Cloudflare, Cisco, and OpenAI. It targets intermediate and advanced viewers, particularly leaders and job seekers in tech.

• Fix your AI pipeline or lose your budget #ai #strategy
  8.6.2026, 03:30:37

  The video describes a detailed process for deploying AI agents in enterprises to increase productivity. The workflow includes several steps: First, agents gather context and read relevant sources to classify the work. Next, they use specific tools to create drafts or make changes. Then they perform checks, add evidence, and route results to appropriate human decision-makers if needed. They log actions taken and update their approach for future runs based on learnings. This comprehensive pipeline process demonstrates that AI agents don’t just handle simple tasks but must work within a complex, iterative system to be truly valuable.

  The video addresses AI agents and their deployment in enterprises without naming specific tools or models, and targets intermediate to advanced users.

• How to actually scale AI beyond individual tasks #ai #productivity
  8.6.2026, 00:00:27

  The video discusses challenges in integrating AI into business processes and emphasizes the importance of identifying bottlenecks. The speaker argues that enterprises consist of a chain of handoffs, where each phase—from product discovery to support and measurement—connects to the next. When AI accelerates only one of these phases without adjusting the others, the bottleneck merely shifts to the next phase. For example, faster code production from AI without adjustments to the code review process moves the bottleneck to review. Similar shifts can occur in QA, product prioritization, launch measurement, and support. The key point is that holistic optimization of all process steps is necessary to improve overall enterprise efficiency.

  The video addresses general AI integration into business processes and targets intermediate to advanced audiences.

• Fix your AI pipeline: Rethink ownership #ai #tech
  7.6.2026, 20:00:04

  The video describes an end-to-end development process covering the entire path from customer feedback to product delivery. The process includes multiple steps: Customer feedback is converted to product decisions, those decisions are translated into plans, plans lead to code changes, code changes are tested, launch risk is reviewed, and finally the feature is released and rollout is measured. The results of the rollout then inform the next decisions, closing the learning loop. The video emphasizes that individual steps shouldn’t be optimized in isolation but viewed as an interconnected process to ensure effective product development.

  The video addresses general principles of product development and is suitable for intermediate to advanced audiences.

• Uber’s massive AI mistake revealed #tech #shorts
  7.6.2026, 16:00:34

  The video discusses reports about Uber’s investments in AI tools and the resulting challenges. Uber heavily invested in AI coding tools, leading to increased token usage and AI-driven code commits. However, the company couldn’t establish a clear connection between this AI usage and increased customer-facing features. Many interpret this development as a sign of an AI bubble and the ineffectiveness of AI agents. The speaker argues, however, that the real message of the Uber story isn’t the ineffectiveness of AI agents but the limited availability of compute power and tokens, which represents the actual bottleneck.

  The speaker emphasizes that Uber is already doing real agentic work and the main issues are high demand and limited availability of compute resources, not the ineffectiveness of the AI tools themselves. The video addresses AI agents in general and the challenges of their implementation without naming specific tools or models, and targets an advanced audience interested in economic and technical aspects of AI.

• WWDC Isn’t About Siri. It’s Jensen Huang’s Problem.
  11.6.2026, 14:00:38

  # Summary

  Apple presented a strategy at WWDC that isn’t primarily about having the best AI model, but about answering: Where does useful AI run—in cloud tabs or on the device you already own? Apple’s answer is a combination of local device processing (iPhone, Mac, Apple chips, operating system) and Private Cloud Compute as a complement. Announcements included: expanded Apple Intelligence, new Siri AI, Apple Foundation Models (partly in collaboration with Google using Gemini technology), local on-device models, server models via Private Cloud Compute, App Intents (to make apps actionable for the system), Core AI for developers to run local models, Xcode Agents, improvements to Safari and password management, and expansion of Private Cloud Compute to Google Cloud with Nvidia GPUs.

  The central developer focus is on App Intents: developers must expose their app content and actions to the system so Apple Intelligence and Siri can work within these apps—not just offer suggestions but actually do something. This changes the requirement for developers: rather than superficially adding a chatbot, data models need clean interfaces, clear permissions, and understandable actions so the operating system can use them.

  The Google Gemini and Nvidia GPU integration doesn’t mean Apple failed but that Apple wants to differentiate between raw model compute power (seen as a commodity) and control over the surface where users touch AI—device, OS, permission prompts, Siri. Apple wants to own this latter layer. Private Cloud Compute shows that the strategy isn’t “everything runs locally” but “run what’s possible locally, route hard problems to trusted private cloud.” This is central to the question of who will be the first trillionaire in AI: Who controls the meter when AI becomes economically inevitable? If the future is ever-larger cloud data centers, Nvidia wins (the tax collectors on intelligence). But if meaningful personal AI runs through device and OS, value shifts to hardware sales, software control, and services Apple can meter or bundle through iCloud and the App Store.

  The surface-level WWDC story is: Siri got smarter, Google supplies models. The deeper story is: Apple is trying to make the iPhone and Mac the standard place where consumers interact with personal AI—and if that becomes standard for consumers, it could also become standard in the workplace because people take their own devices everywhere. For end users, this means: AI value doesn’t lie in individual paragraphs an LLM writes but in seamlessness, fewer context switches, and less “administrative paperwork”—the page changes, the password is weak and the computer fixes it, the shortcut is built in plain English. Apple’s core promise is: The computer knows a lot about you without you feeling like your life is being mined for data. That’s a trust space that might be harder for other AI providers to occupy.

  The video argues that the question deciding who becomes the first trillionaire isn’t “Who has the best frontier model?” but rather: Who owns the surface through which a billion people touch AI daily? Apple has a path—an existing device ecosystem, mature operating system, developer ecosystem, and trust. The WWDC roadmap shows how Apple plans to build this path.

  **Conclusion:** The video explicitly addresses Google Gemini, Nvidia, Apple Intelligence, and Private Cloud Compute; it targets a broad audience (advanced to business leadership), less a technical deep-dive than a strategic analysis.

Alejandro AO (1 new video)

• PI Architecture EXPLAINED | Agent Loop, Tools, TUI and More
  5.6.2026, 14:25:55

  The video provides a detailed overview of the architecture of Pi, a minimalist AI agent. It begins by explaining the Agent Core, also known as the Agent Loop, which describes how Pi fundamentally operates. This process includes context initialization, context transformation, and invoking the Large Language Model (LLM), where tools such as file operations or internet research can be leveraged.

  The video then explains the structure of Pi’s sessions and storage system. Sessions are stored in JSON-L files, which enable simple and efficient management of message history. The sessions are organized in a tree structure, which facilitates navigation and conversation management.

  The video also covers Pi’s tools, which are limited to four tools by default but can be extended through extensions. Extensions make it possible to add additional features such as web search or custom commands.

  Another important aspect is the System Prompt, which establishes the foundation for the agent’s behavior. This can be customized through user-defined files or commands.

  Finally, the video explains the interaction between PyCore and Pi’s interactive user interface (TUI), including handling of Skills and custom prompts. The TUI is modularly designed and allows for dynamic adjustment of the user interface.

  The video explicitly addresses the AI agent Pi and is best suited for intermediate and advanced users interested in the technical implementation and architecture of AI agents.

Sebastien Dubois (4 new videos)

• Obsidian Tips Focus Mode Plugin
  11.6.2026, 04:00:13

  The video introduces the “Focus Mode” plugin for Obsidian, which can be installed from the Community Plugins collection. After installation, users receive a hotkey to toggle between normal mode and focus mode. In normal mode, notes and sidebars are visible, described as “loud.” By activating focus mode, the sidebars and associated buttons disappear, displaying only the desired content. This enables undisturbed and focused work on notes.

  The video covers the Obsidian plugin “Focus Mode” and is aimed at intermediate users.

• Obsidian Tips Quick Opener
  10.6.2026, 06:38:59

  The video introduces the “Quick Opener” function in Obsidian, accessed by pressing `Ctrl` or `Command O` on Mac. This function allows quick note searching by entering the note’s name. Pressing Enter opens the desired note immediately. The video demonstrates this with examples such as searching for a note named “Garmin AI skill” and a Kanban board note. The function is described as efficient and useful for quick note access.

  The video covers Obsidian software and is aimed at intermediate users.

• Obsidian Tips Attach notes to sidebars
  10.6.2026, 05:45:26

  The video shows a quick tip for using Obsidian, a tool for knowledge management and note-taking. It explains how to attach notes and panels to sidebars. To do this, drag a note with the mouse onto the top or bottom sidebar and drop it there. The note remains pinned in place. By right-clicking, you can additionally pin the note so it stays permanently at that location. This process also works on the left sidebar. This feature is useful for customizing your view in Obsidian.

  The video covers the Obsidian tool and is aimed at intermediate users.

• Obsidian Tips – Sidebars
  9.6.2026, 14:57:22

  The video shows a quick tip for using Obsidian, a tool for knowledge management and note-taking. It explains how to show and hide sidebars in Obsidian to optimize your workspace. By displaying the left and right sidebars, you can navigate between different notes or search for information in a vault while simultaneously editing a note in fullscreen mode. The tip is simple to implement and helps keep focus on your desired tasks.

  Final note: The video covers the Obsidian tool and is aimed at beginners.

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Unsupervised Learning (2 new videos)

• A Conversation With Cliff Crosland
  9.6.2026, 16:00:04

  The video is an interview with Cliff from Scanner, a company that has developed an unconventional and radically different data solution for large volumes of data. Scanner aims to maximize the value of log data as data volume increases, rather than degrading the tools. The company has developed a solution based on object storage like S3 to store and index data in a cost-effective and scalable way. Scanner uses a specialized indexing technique that overcomes the latency of object storage by using batch-friendly data structures. Scanner’s search clusters are temporary and are only activated when needed, which reduces costs. Scanner supports various file formats such as JSON, CSV, plain text, and Parquet and requires no extensive data preparation. The solution is particularly suitable for security data, detection and response, threat hunting, and insider threats. Scanner enables fast queries over large volumes of data and can be integrated with AI tools to create detailed analyses and reports. The company plans to be available on additional cloud platforms such as GCP and Azure. Scanner is being presented at conferences such as Bides 312 and Black Hat. The video specifically covers the Scanner tool and is geared more toward intermediate to advanced users.

• AI Predicts The Text Of Answers
  4.6.2026, 18:32:26

  The video discusses the thesis that AI systems do not understand the world but merely predict the next token in a text. The author argues that this view is superficial and that AI actually possesses a kind of understanding, albeit not in a human way. He explains that AI does not complete random texts but generates specific answers to posed questions. To demonstrate this, he created a website called “AI understands.ai” where AI is confronted with new, never-before-seen whodunit mysteries, including fictional physical laws. The author shows that AI can solve these puzzles by drawing logical conclusions, suggesting that it possesses a functional understanding of the world. However, it lacks human, experience-based understanding and emotions. The author proposes distinguishing between functional and experience-based understanding, with AI possessing the former but not the latter.

  The video covers generic AI models such as ChatGPT and is geared more toward intermediate and advanced users.

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