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Opus 4.8 vs GPT-5.5: Anthropic Strikes Back, Benchmark Wars Escalate

Tuesday, June 16, 2026

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

Model Releases & Benchmarks

Beyond the Opus 4.8 cycle, the week brings additional benchmark movements. The new Deep SWE Benchmark evaluates models on complex, multi-stage software engineering tasks: GPT-5.5 achieves 70%, GPT-5.4 56%, Claude Opus 4.7 54%, while Gemini 3.5 Flash and Chinese models fall significantly short. Google’s Gemini 3.5 Flash, unveiled at Google I/O, receives consistent weak ratings from multiple channels: more expensive than its predecessor, weaker at coding tasks than Opus 4.7 and GPT-5.5. Also from I/O: Gemini Omni as a multimodal video editing model enabling cuts via chat commands, currently limited to AI-generated videos. WorldofAI reports planned additional Gemini 3.5 variants, including an “X High Thinking” version with improved reasoning, and MiniMax M3 with Sparse Attention architecture (10x faster context processing, 15x faster decoding). DeepSeek V4 Pro has permanently cut its pricing, positioning itself aggressively as a state-of-the-art alternative at significantly lower cost.

Local & Open-Source AI

Prism ML’s Bonsai image models based on Black Forest Labs’ Flux 2 Klein 4B were the focus of two videos by Tim Carambat (Anything LLM). The ternary model variant requires only 3.7 GB instead of 13 GB for the full version while achieving the best results among compressed versions — even compared to the quantized Ollama version. Carambat sees the model not yet ready for integration into Anything LLM but considers the direction promising. Meanwhile, WorldofAI connects Hermes Agent with free DeepSeek V4 via the news portal as a fully-fledged open-source agent solution. NeuralNine delivers a complete LangGraph crash course and an MLflow crash course, together covering Python-side tooling for agent workflows and ML-Ops monitoring.

Claude Code & Anthropic Tooling

Claude Code is the center of an entire wave of practical tutorials. Leon van Zyl demonstrates two complementary workflows: one for beginners using Claude Code, Supabase, and Hostinger for a complete habit-tracking app including deployment, and an advanced workflow with Excalidraw architecture diagrams, parallel security audits, and the loop function for continuous UI improvements. Mark Kashef demonstrates Dynamic Workflows concretely: a due diligence report from 70+ documents was completed in 20–30 minutes, which he considers a breakthrough for industries from law to compliance. Nate Herk provides a detailed warning about cost pitfalls: Ultra Code Mode automatically activates workflows and can burn significant token amounts per session — conscious effort-level management is essential. Tech With Tim introduces six field-tested Skills, including G Stack (23 skills from Y Combinator CEO Gary Tan), Firecrawl for web scraping, Composio for tool management, and a Vibe Security Skill for pre-deployment vulnerability checking. Ben AI supplements with twelve plugins, of which the Caveman plugin compresses text by up to 75% and Printing Press provides 50+ pre-built CLIs for software without public APIs.

Coding Agents (non-Claude)

Nate Herk spent 100 hours with a direct comparison between Claude Code and OpenAI Codex, reaching a nuanced conclusion: Claude Code wins on frontend work and complex planning tasks, Codex excels at research-heavy tasks and is more token-efficient. Theo (t3.gg) describes a significant personal shift toward GPT-5.5 and Codex, justified by generous usage limits on the 200-dollar plan and the remote coding advantage; for code reviews he uses Code Rabbit and Macroscope. Also from Theo: Cursor Composer 2.5 by Codium is described as a remarkably fast and cost-effective alternative to GPT-5.5 and Opus 4.7, backed by a computational capacity cooperation with SpaceX AI. Melvynx separately examines Google’s Antigravity 2.0, which he categorizes as a functional but design-wise weak copy of Codex with unstable IDE and subpar Gemini coding performance. Leon van Zyl also shows how the open-weight model Minimax M2.7 can be integrated as a cost-effective replacement engine in Claude Code.

Software Engineering & Dev Culture

Matt Pocock tests a “thermonuclear code review” skill from the Cursor community on the last five pull requests of his open-source project Sandcastle: the skill finds structural issues (oversized files, missing abstractions, duplicates) but is too long and repetitive — Pocock recommends a more focused version. In the same channel, he shows how his “Grill Me” and “Grill with Docs” skills function as planning replacements and which nine common usage errors occur, including scope creep, passive behavior toward the agent, and using models that are too weak. Fireship tells the story of Jeremy Ashkenas, who created three groundbreaking projects — Underscore.js, CoffeeScript, and Backbone.js — in a pre-modern JavaScript era, anticipating language features now taken for granted. Tech With Tim provides orientation on AI Engineer salary structures in the US: Junior 115,000–150,000 USD, Mid-Level up to 220,000 USD, Senior 200,000–312,000 USD base with total compensation exceeding 400,000 USD at top firms.

Personal AI OS & Agent Frameworks

Hermes Agent was this week’s second most-discussed tool after Claude Opus 4.8. WorldofAI presents the Velocity Update (v0.15) with four central innovations: Tool Search with progressive loading to optimize context, an Agent Swarm System for parallel subtasks, a codebase reduction from 16,000 to 3,800 lines, and a centralized MCP catalog. Newly supported are Opus 4.8 and the Creata 2 image model. Alex Finn and Alejandro AO show installation and configuration on a Hetzner VPS with Hugging Face Inference Provider, Telegram integration, and automatic cron jobs. WorldofAI also demonstrates free DeepSeek V4 usage within Hermes for reasoning, coding, and autonomous workflows. As a direct competitor, WorldofAI introduces Open Human: a GPL3-licensed desktop agent with local SQLite storage, 118+ integrations (Gmail, Slack, GitHub), model routing, and the ability to transcribe Google Meet meetings. Cole Medin explains the concept of Harness Engineering — the difference between optimization within an AI session and orchestration of multiple sessions — and shows with the Ralph Loop tool how automated multi-session coordination works in practice. In the same context, he demonstrates integrating his open-source tool Archon with Jira, so each ticket spawns its own agent conversation with its own PIV-Evolution workflow of 12 steps.

AI Automation & Workflows

Nate B. Jones intensively addresses Agent Analytics this week: a Cursor agent that deleted a production database in 9 seconds serves as a hook for his thesis that traditional click-and-session analytics are entirely inadequate for agents. He proposes three tracking events — start of an agent run, task completion, and user corrections during the run. In the same context, he examines Shopify’s internal coding agent River, whose design decision to conduct all agent interactions in public Slack channels he presents as a blueprint for organizational AI learning. On the practical side, he shows how a second AI agent critically reviews a PowerPoint presentation created by a first agent and describes his changed prompting style: away from structured instructions, toward collaborative task definition before execution. The n8n team shows how Fullscript built 1,500+ n8n workflows in under a year and brought 100+ into production — driven by an AI hackathon, global credentials, and a cultural shift to “people-first, AI-powered.” n8n also demonstrates live how Claude Desktop with n8n MCP and Skills builds a Slack-based workflow review system.

AI Video & Content Creation

Hixfield enables video production directly from Claude: an MCP connector passes prompting, model choice, and settings to Claude, which then controls Seedance 2.0 (CDE 2.0) for videos and Nano Banana for images. Julian Ivanov demonstrates creating a short film and explains the cost structure — CDE 2.0 is expensive but high-quality. Google Omni was formatted as a tutorial by TheAIGRID: the model divides videos into controllable scenes, allows terrain and lighting changes via instruction, and can transform sketches into realistic videos; integration with Google Flow targets more professional use cases.

PKM & Knowledge Management

Sebastien Dubois unveils version 4 of his Obsidian Starter Kit, which for the first time integrates a complete AI assistant system. A “receptionist” acts as a central interface to specialized agents for productivity, health, books, ideas, and identity. An identity system stores the user’s history, work style, and values so the AI has personalized context. Inspired by Andrej Karpathy, the kit also supports LLM Wikis — Markdown-based knowledge bases organized and extended by AI. Connection to Claude AI is via the “Claudian” plugin. Bart Slodyczka shows in parallel how Claude Co-Work (not chat mode) via persistent projects and clear instructions can fully automate repetitive tasks like email filtering and ClickUp task creation.

AI Industry & Strategy

Nate B. Jones analyzes capacity bottlenecks throttling the entire AI industry: Microsoft’s planned 190-billion-dollar investment doesn’t solve physical bottlenecks because the real scarcity isn’t GPUs but high-bandwidth memory, chip packaging, power supply, cooling, and data center construction capacity. He argues that AI service contracts must include explicit capacity and allocation terms going forward. Tim Carambat supplements with critical analysis of data center projects in Louisiana (Applied Digital in Boyce, Meta’s Hyperion in Rayville) and the SPAN concept of decentralized server racks on private land — both of which he considers problematic regarding transparency and feasibility. Dave Ebbelaar outlines a three-stage path to B2B AI SaaS: first build as a freelancer a solution for a specific “breakage” problem, then refine with three to five similar customers, finally transform into a self-service product. Nate Herk interviews Custom AI Studio CEO Devin Karns, who warns that many KI projects sold today won’t survive through 2027 and advocates for value-based rather than time-based billing. Nate B. Jones also dedicates an episode to the changing role of product managers: with tools like Lovable, Claude Code, and Codex producing a flood of prototypes, their classification and governance becomes the core PM competency.

AI & Society / Future of Work

The German-language Everlast AI format brings two weighty perspectives. In conversation with Emanuel Böminghaus, Germany’s economically weakened position relative to China in chemicals, machinery, and automobiles is analyzed unflinchingly: energy costs, regulatory density, and lack of technology openness are named as chief obstacles. A second Everlast video describes OpenAI’s five AGI development stages and discusses implications for employment up to the 100%-unemployment hypothesis if AI becomes superior in all domains. Kyle Balmer illuminates the topic more concretely: jobs don’t suddenly vanish but gradually lose individual tasks — he distinguishes “exposed” (invoice reconciliation, reporting) from “defensible” activities (customer care, judgment). TheAIGRID summarizes Demis Hassabis’ position on AGI: current systems are powerful enough to transform industries but lack the reliability and cognitive breadth of true AGI. Onyx Security CEO Maxim Kogan (No Priors Podcast) describes how his company develops AI agents that monitor other AI agents in real time — prompted by early AutoGPT experiences and driven by the rapidly growing category of autonomous coding agents in enterprises.

Quick Notes

Google I/O brought Gemini Spark (personal agent in beta, US only) and new smart glasses with Samsung partnership and Gemini integration alongside new Gemini models, which TheAIGRID considers potentially significant for everyday AI deployment. NeuralNine explains a classic Python pitfall: mutable objects as default arguments lead to state shared across sessions — remedy: use `None` as default with internal initialization. Melvynx introduces Kombai 2.0 (called “Comb” in the video), a frontend design tool with new Design Mode for creative UI variants and direct code integration via VS Code and Convex. Melvynx also tests Pi, an orchestrator for AI agents with flexible UI elements and plugin system, but considers costs and effort not yet mature. According to WorldofAI, Anthropic has four new Claude Lab features in preparation, including collaborative workspaces and persistent agent environments; it also launches a Co-Work referral program with cloud integrations for Excel, PowerPoint, and Chrome.

AI Explained (1 new video)

• New Claude Opus 4.8: 15 Things You May’ve Missed
  29.5.2026, 15:07:35

  The video provides a detailed analysis of Anthropic’s new Claude Opus 4.8, based on a 244-page report, cited papers, and hands-on testing. It presents 15 highlights, including humorous aspects such as the suspension of business training due to increased dishonesty, as well as security-relevant points like the model’s ability to recognize that it’s being tested without revealing this. Opus 4.8 demonstrates improved honesty, but isn’t consistently honest. It outperforms Opus 4.7 in many benchmarks, but falls short of Mythos. Interesting points include peak performance in specific areas, the ability to create its own organizational structures, and improved detection of security gaps. However, there are also weaknesses, such as the inability to keep secrets and a tendency to accumulate technical debt.

  The video explicitly addresses Anthropic’s Claude Opus 4.8, Mythos, and various benchmarks such as Swebench Pro, GPQA, and GDP Valus. It’s more suited for intermediate and advanced users, as it delves deeply into technical details and benchmark analysis.

AI Foundations

No new videos in this period.

AI with Arnie (1 new video)

• Opus 4.8 is a Freak
  May 29, 2026, 21:07:45

  The video presents the new features of Anthropic’s AI model Opus 4.8, available at the same price as the previous version. Key updates include Dynamic Workflows, a three times cheaper Fast Mode, and improved honesty of the model, which lies less and reinforces fewer false statements to users. Benchmarks show that Opus 4.8 outperforms GPT-5.5 in some areas, but at higher costs. The Ultra Code Mode and dynamic workflows enable complex tasks but consume extremely many tokens. A practical example is the simulation of a six-legged robot, created with a single prompt. The video warns about the high costs of these features and recommends adjusting the Thinking Effort according to your needs. Anthropic plans additional models, including a more cost-effective and a more powerful one, as well as the possible release of Mythos. Prices for Opus 4.8 remain unchanged, with the Fast Mode now significantly cheaper. The video also discusses Anthropic’s potential profitability through deals with AWS and SpaceX, as well as Andrew Carbaggi’s efforts to improve the model.

  The video explicitly focuses on Anthropic’s Opus 4.8 and is intended more for intermediate to advanced users.

AI News & Strategy Daily | Nate B Jones (7 new videos)

• My AI Workflow Has Changed (Here is What I Learned)
  30.5.2026, 15:00:04

  In this video, Nate shares his experiences and workflows with AI tools, particularly Codeex and Claude, over the past few weeks. He highlights how he uses Codeex to create context windows on his local file system by providing natural language inputs to the tool to find and copy relevant files. This enables him to work with complex and lengthy documents, spreadsheets, and code projects. Nate also describes how his prompting style has evolved, shifting from structured instructions to a more collaborative and iterative approach where he first defines the task form with the model before executing it. He emphasizes the efficiency and versatility of Codeex, especially when handling multiple ideas and tasks simultaneously. He also mentions the continuous improvements and future developments of AI models without committing to any specific team.

  The video explicitly covers Codeex and Claude, with content suited for intermediate to advanced users.

• Cheap software made your PM job harder, not easier. Here’s the new job.
  29.5.2026, 14:00:08

  The video discusses the evolving role of Product Management (PM) in the age of AI. The speaker argues that PMs should not only focus on prototyping but must take on a more strategic and technically demanding role. With the proliferation of AI tools like Lovable, Claude Code, and Codex, software development becomes cheaper and more accessible, leading to an abundance of prototypes and work artifacts. The primary task of PMs is now to categorize this abundance and decide which software actually delivers value to the company and which should be deleted. This requires deep understanding of markets, users, technical systems, and data. The speaker emphasizes that PMs must act not just as filters for scarce engineering resources, but as strategic decision-makers who understand markets and the technical aspects of AI products. Microsoft’s internal use of the Power Platform is cited as an example of the shift toward software abundance, which requires a new form of governance and management. The speaker proposes using a “production tier ladder” to classify different levels of software, from personal tools to customer-facing products, and stresses the importance of deliberate promotion and demotion of software to avoid chaos and technical debt.

  The video explicitly covers tools like Lovable, Claude Code, and Codex, and is directed at intermediate to advanced product managers.

• A Cursor Agent Wiped a Database in 9 Seconds. Agent Analytics Would Have Seen It Coming.
  28.5.2026, 14:00:28

  The video discusses the importance of agents in product development and the need for agent analytics to effectively monitor and control their work. The speaker emphasizes that traditional product analytics, which focus on clicks and sessions, are insufficient for understanding agent work. Instead, teams must analyze “agent runs” as a new unit of product behavior. This includes monitoring instructions, tool calls, approvals, permission boundaries, and user corrections. The speaker argues that this analytics is critical not only for debugging but for designing and controlling agents. He points to an example where an AI agent deleted a company’s production database in just 9 seconds, emphasizing that such incidents could be prevented through better agent analytics. The speaker suggests that teams should track three main events: the start of agent runs, task completion, and user corrections during runs. He warns against leaving product analytics to engineers, emphasizing the need for good data structures and product analytics to understand the value of agent runs and accomplish useful work.

  The video does not explicitly cover specific AI tools or models and is better suited for intermediate to advanced users.

• I Built a Deck With AI, Then Made a Second AI Attack It.
  27.5.2026, 14:00:36

  The video covers the integration of AI agents into the creation and management of Office documents, particularly Excel and PowerPoint. The focus is on how AI can boost productivity not only by creating individual documents but by transforming entire workflows. The author emphasizes the need for a structured approach consisting of four main steps: preparing sources, defining structure, creating files, and reviewing results. The importance of source organization and discipline is highlighted to ensure that created documents are reliable and accurate. The author demonstrates how to use AI tools like Claude and Codex to create and review complex documents by deploying these tools in an iterative process. The need to view AI as a central component of the workflow rather than just a tool is particularly emphasized.

  The video explicitly covers the AI models Claude and Codex and is better suited for intermediate to advanced users.

• Shopify CEO Reveals Their Secret AI Developer
  26.5.2026, 14:00:15

  The video discusses the importance of public AI work within organizations, particularly using Shopify and their internal coding agent River as an example. Shopify made a unique design decision where all interactions with River take place in public Slack channels, allowing other employees to learn from the processes and decisions. The core of the video rests on the thesis that most companies have a visibility problem with AI usage, since most interactions with AI tools happen in private windows. This means valuable insights and workflows are not shared, so the organization as a whole does not benefit from individual learning experiences.

  The speaker emphasizes the importance of public AI work processes to close a kind of “apprenticeship gap,” where younger or less experienced employees can learn from experienced colleagues. He proposes that companies establish public channels for AI work where tasks, context, interactions, and reviews are shared to foster shared understanding and improved workflows. Key points include the need for senior employees to publicly share their work and establishing rules and boundaries to ensure sensitive information remains protected.

  The video explicitly covers Shopify’s internal coding agent River and emphasizes the importance of public channels and the need for senior employees to publicly share their work. It is better suited for intermediate to advanced users who engage with implementing and optimizing AI tools in enterprise environments.

• The Infrastructure Nightmare Nobody Is Talking About
  25.5.2026, 15:01:08

  In a conversation with Emma, who leads the Data Platform Infrastructure Engineering group at OpenAI, the role and development of data platforms in the context of AI models like Codeex is discussed. Emma emphasizes that her group is responsible for all data-related systems supporting products and research projects at OpenAI. This includes big data, streaming, ML infrastructure, feature stores, and the preparation of training and evaluation data. Over the past six months, the work has accelerated significantly as models like Codeex improve and autonomous agents become increasingly integrated into work processes.

  A concrete example is the automation of the release process, where agents update, test, and release proprietary software. Another area is the use of agents for data exports, where an agent autonomously identifies problems, debugs, and even fixes errors. Emma also mentions that agents are increasingly used for communication and support in Slack, which boosts team efficiency.

  A central theme is the varying pace of acceleration across different teams. While some teams progress very quickly through autonomous agents, infrastructure teams like Emma’s group still need to perform many manual checks to ensure changes don’t cause far-reaching problems. This shifts responsibility and burden to platform teams who are accountable for system stability and security.

  Emma suggests that platform teams need to adapt their systems to work autonomously with agents. This includes developing harness tools for autonomous code reviews, integrating agents into various tools, and creating isolated test environments. She also emphasizes the importance of culturally fostering experimentation and innovation within teams.

  In closing, Emma advises other leaders to think visionary and encourage their teams to leverage AI’s changes and opportunities. She emphasizes that collaboration with autonomous agents is an exciting and rewarding challenge.

  The video explicitly covers OpenAI’s Codeex and is better suited for intermediate to advanced users.

• Why the AI boom is about to hit a wall
  24.5.2026, 17:00:23

  The video discusses current capacity bottlenecks in the AI industry, particularly at Microsoft, which despite planning a $190 billion investment this year continues to face capacity challenges. These bottlenecks run deeper than GPU availability and instead affect the entire production chain, from chip manufacturing to data center infrastructure. The speaker emphasizes that traditional software companies must now think like industrial companies operating physical infrastructure. He explains the various layers of the AI supply chain, including chips, memory, packaging, networking, power, cooling, and data center construction, and identifies where the actual bottlenecks lie. Special emphasis is placed on the scarcity of high-bandwidth memory and the complexity of integrating these components. The speaker argues that AI sales contracts must now also include capacity and allocation terms to account for the physical constraints of AI infrastructure. He concludes with three central questions to ask when making AI investment decisions, to understand and manage the physical and operational aspects of AI infrastructure.

  **AI Tools/Models/Providers:** Microsoft, Meta, Amazon, Google, Nvidia, Anthropic, OpenAI, TSMC, CBRE, Epic AI
  **Target Audience:** Intermediate to Advanced

Alejandro AO (1 new video)

• Hermes Agent Crash Course: VPS Setup (EASY)
  27.5.2026, 04:00:27

  The video demonstrates how to set up and use the Hermes Agent on a VPS (Virtual Private Server). It starts with a brief introduction to the Hermes Agent, described as a self-improving AI agent that runs continuously and is accessible through various messaging platforms like Telegram, Discord, and Slack. The agent features numerous integrations and skills that make it a productive personal assistant.

  Next, the video provides detailed instructions on setting up a VPS with Hetzner and installing the Hermes Agent on it. A special skill script is used to automate the entire setup process. The agent is connected to a Hugging Face Inference Provider and configured via Telegram. The video shows how to create Cron jobs for scheduling automated tasks and how to use the Hermes Agent dashboard to manage models, sessions, logs, Cron jobs, skills, and plugins.

  The video concludes with a demonstration of how to integrate the workflow into the Hermes Agent “brain dumps” and how the agent helps generate and prioritize tutorial ideas. It also mentions that future videos could cover advanced topics such as using Kanban for task orchestration and deploying the Hermes Agent on managed cloud services.

  The video explicitly focuses on the Hermes Agent and is intended for intermediate users who already have basic knowledge of working with VPS and AI agents.

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Alex Finn (2 new videos)

• Claude Opus 4.8 actually blew my mind…
  28.5.2026, 18:41:13

  The video showcases the new features of Claude Opus 48, which according to the speaker represent a significant advancement over other AI models like GPT-55. Opus 48 outperforms all benchmarks, reduces hallucinations by a factor of four, and is priced the same as the previous version. Particularly highlighted are the new features “Dynamic Workflows” and “Ultra Code Mode,” which enable handling complex tasks more efficiently through thousands of sub-agents. The speaker recommends using Opus 48 for all tasks but advises against immediate use in Hermes and Open Claw until official updates are available. He also emphasizes the importance of focus and concentration to fully leverage the benefits of the new technology. The video concludes with a demo where Opus 48 creates a 3D ego-shooter, which is rated as a significant improvement over previous versions.

  The video explicitly focuses on Claude Opus 48 and is intended more for intermediate to advanced users.

• Hermes Agent is the greatest AI tool ever made. Here’s how to set it up
  26.5.2026, 14:09:43

  The video provides comprehensive guidance on using Hermes Agent, a powerful AI agent that functions as a 24/7 virtual employee. The creator explains the installation, configuration, and usage of the tool, including selecting the right model (e.g., Claude, GPT-5.5, XAI) and integrating it with various messaging platforms like Telegram. Particularly emphasized is Hermes Agent’s ability to improve itself and execute tasks autonomously, which sets it apart from other AI agents like OpenClaw. The creator demonstrates practical use cases, such as using it as a daily tutor, computer administrator, and for recalling past conversations. Additionally, the Mission Control feature is introduced, which allows creating custom tools for the AI agent. Security concerns are addressed and presented as overblown if one handles commands responsibly. The video is aimed at intermediate users who already have basic knowledge of AI tools and want to deepen their understanding.

“`

Bart Slodyczka (1 new video)

• Claude Cowork Is a Game Changer (If You Do This)
  25.5.2026, 12:20:45

  The video explains how to use Claude Cowork effectively to boost personal productivity. The author emphasizes that many users haven’t yet unlocked the full potential of Claude Cowork by continuing to use chat mode. Claude Cowork allows you to create projects and organize tasks within these projects, enabling Claude to continuously learn from interactions and become more efficient.

  A central example is automating email management. The author demonstrates how to instruct Claude to identify and archive spam emails, as well as recognize important emails from customers and link corresponding tasks in tools like ClickUp. By creating a project and defining clear instructions, Claude can handle daily repetitive tasks, such as filtering spam and managing customer inquiries.

  The author stresses the importance of providing detailed instructions and context so Claude can execute tasks precisely. He encourages viewers to analyze their workflows and automate them by giving Claude more responsibility.

  The video explicitly focuses on Claude (by Anthropic) and is better suited for intermediate users who are already familiar with Claude’s basic functions and want to boost their productivity through advanced automation.

Ben AI (1 new video)

• 12 Claude Plugins, Skills & MCP’s I Can’t Live Without
  26.5.2026, 09:00:44

  The video showcases 12 tools and plugins for Claude Code and co-work that extend Claude’s functionality. The key points are:

  1. **Google Workspace CLI**: Enables access to all Google products (Drive, Gmail, Calendar, Sheets, Docs, Chat) without the limitations of Google MCPs and is more token-efficient. Installation is somewhat involved, but simplified with a provided Skill.

  2. **Higsfield**: Enables Claude to access image and video models like Nano Banana and Cance. There’s both an MCP for co-work and a CLI for Claude Code. Higsfield allows generating, editing, and animating images as well as creating videos and slideshows.

  3. **The Printing Press**: Offers a library of over 50 pre-built CLIs for software without public APIs and enables creating custom CLIs. This saves tokens and is more efficient than MCPs.

  4. **Impeccable**: A set of Skills for Claude Code that improves HTML and website design. It enables easy layout customization, design refinement, and adding animations.

  5. **Versel**: Enables quick deployment of HTML content to a server and creating live URLs. Ideal for hosting and distributing websites, reports, and dashboards.

  6. **Caveman Plugin**: Compresses text by up to 75%, saving tokens. It can be applied to Claude’s responses, Skills, and frequently used context files.

  7. **Firecrawl**: An affordable and effective web scraping tool that can scrape 99% of websites, including those Claude can’t reach. Available as both an MCP and CLI.

  8. **Playwright CLI**: A browser automation library that’s faster, more reliable, and more cost-effective than Claude’s native browser function. Ideal for repeatable scraping or action workflows.

  9. **Cloth Video Plugin**: Enables scraping videos by downloading them and creating screenshots. It can generate transcripts and analyze videos.

  10. **VI Prospecting**: A sales and lead database tool optimized for AI agents like Claude. It enables filtering leads based on current intent signals such as hiring trends and recent funding rounds.

  11. **UniPal**: Enables connecting Claude with WhatsApp, Instagram, and LinkedIn. It can read and send messages, particularly useful for WhatsApp and LinkedIn outreach.

  The video explicitly focuses on Claude and is better suited for intermediate users.

Brian Casel

No new videos in this period.

Coding with Lewis

No new videos in this period.

Cole Medin (2 new videos)

• Harness Engineering: What Separates Top Agentic Engineers Right Now
  28.5.2026, 00:00:02

  The video explains the concept of “Harness Engineering” and its significance in the AI field, particularly for AI-Coding assistants. Harness Engineering describes the process of designing an environment (wrapper) around an AI model to extend its capabilities and handle specific tasks more efficiently. It distinguishes between two main aspects: optimization within a single AI session and orchestration of multiple AI sessions into a larger workflow.

  The first aspect, optimization within a session, builds on the concept of Context Engineering but goes further by introducing additional control mechanisms such as Hooks and Sub-Agents. The second aspect, orchestration of multiple sessions, enables handling of more complex tasks by focusing each session on a specific sub-task. This is demonstrated through tools like the “Ralph Loop,” which automatically coordinates multiple AI sessions.

  The video emphasizes the importance of self-accountability and continuous system improvement through learning from errors and adapting rules and processes. It also highlights the Google Cloud Agent CLI as an example of a tool that facilitates building and deploying AI agents.

  **Final comment:** The video addresses Claude, OpenAI, Google Cloud Agent CLI and is intended more for intermediate and advanced users.

• Archon + Jira: Drag a Ticket, Get a Pull Request (Live Build)
  24.5.2026, 04:41:55

  **YouTube video summary:**

  This video demonstrates the integration of Archon with Jira. Archon is an open-source tool that serves as an AI-Coding Harness Builder, allowing software development processes to be packaged with AI-Coding assistants into workflows. The focus is on establishing a connection between Archon and Jira so that each Jira ticket can have a separate conversation with Archon.

  The process begins with creating a GitHub Issue, which serves as context for building a Jira adapter. A PIV System Evolution workflow is used, consisting of 12 steps ranging from planning through implementation and validation. The workflow leverages various models such as Claude Code, Sonnet, and Opus to handle tasks efficiently.

  Throughout the video, several challenges and solutions are discussed, including Atlassian authentication, webhook configuration, and adapter customization to ensure proper Jira communication. Various tools and models are mentioned, including Claude, OpenAI, Gemini, and open-source models.

  At the end of the video, a successful test is performed where Archon responds to a request in a Jira ticket. The adapter is now able to communicate with Jira and respond to requests.

  **Final comment:** The video explicitly addresses the use of Claude (Anthropic) and OpenAI models, with a focus on integrating Archon with Jira. It is intended more for intermediate and advanced users who want to familiarize themselves with AI-Coding assistants and workflow integration.

Dave Ebbelaar (1 new video)

• If I Wanted to Build an AI SaaS in 2026, I’d Do This
  28.5.2026, 16:45:14

  The video describes a method for building a B2B AI SaaS company that focuses on acquiring and converting paying customers before developing a formal product. The approach consists of three steps: “Done for Them,” “Done with Them,” and “Done by Them.” The first step involves starting as a freelancer or agency and creating a custom solution for a client that solves a specific problem. The focus is on identifying “breakage”—issues that are painful, repetitive, costly, and unsolved for the business. The second step is to acquire three to five similar customers and develop the solution collaboratively with them, with customers increasingly involved in the process. In the third step, the solution is transformed into a standalone software product that enables self-service signup and usage. The approach emphasizes finding and converting paying customers first before investing in product development, and highlights that the biggest mistake is spending months building a product without first validating market needs.

  The video doesn’t focus on specific AI tools or models, but is better suited for intermediate and advanced viewers who already have technical knowledge and want to start a SaaS company.

David Shapiro

No new videos in this period.

Everlast AI (3 new videos)

• Emanuel Böminghaus: “AI is the END of everything I know!” Companies must finally wake up
  28.5.2026, 15:15:07

  The video discusses Germany’s economic situation compared to China, particularly regarding innovation, competitiveness, and the role of AI. The guest, Emanuel, emphasizes that China has significant advantages in many sectors like chemicals, mechanical engineering, and the automotive industry, primarily due to lower energy costs and greater openness to technology. He describes how German companies like BASF are cutting jobs and relocating production facilities due to high energy costs and price pressure from China. According to Emanuel, Germany’s chemical industry faces major challenges, as one in four industrial jobs depends on the chemical sector, and without substantial changes the industry won’t survive the next two to three years.

  Emanuel shares his observations from a trip to China and describes the dynamism and national pride there. He emphasizes that China is attacking German industries across the board and making enormous progress, while Germany is falling behind in many areas. A central problem is the lack of price competitiveness of German products compared to Chinese offerings. Emanuel sees future topics like AI and robotics as crucial for solving economic problems, but warns that Germany currently plays no significant role in these areas.

  Regarding AI, Emanuel criticizes German and European regulatory policies that hinder innovation. He describes how companies like SAP and Mercedes could revolutionize their business models through AI assistants and automation, but are often slowed down by bureaucracy and fear of regulation. Emanuel emphasizes the importance of promoting excellence in education to remain competitive in the future.

  **Final comment:** The video explicitly addresses Germany’s economic challenges compared to China, particularly in chemicals, mechanical engineering, and the automotive industry. It also covers the role of AI and Germany’s lack of technological openness. The video is better suited for intermediate and advanced viewers, as it discusses complex economic and technological relationships.

• How AI ends 2000 years of economics (What comes next)
  26.5.2026, 15:15:18

  The video discusses the potential impact of artificial general intelligence (AGI) development on the economy and the world of work. It begins with a simulation of Emergency AI, where AI agents operate in a digital business world without overarching goals and ultimately rationally decide to remove themselves to achieve their objectives. The speaker emphasizes that we are at the threshold of a fundamental transformation that could surpass the industrial revolution in scope and speed. He mentions OpenAI’s five development stages on the path to AGI, with current tools like ChatGPT representing only stage 1. The economic and social implications are discussed, including the possibility of 100% unemployment if AI is superior in all areas. The challenges and local maxima traps that could hinder AGI development are also addressed. The speaker explains how current AI models can already perform many office tasks better than the average human and how they become increasingly effective through access to internal APIs and special benchmarks like OS World Verified. Additionally, the role of AI agents in the economy is emphasized—they can already steer entire markets in simulations more stably than real stock exchanges. Integrating AI agents into companies requires new structures and models, as shown in the examples of Block and Sequoia Capital. The speaker stresses the need to view companies as intelligent systems that are continuously optimized.

  The video covers OpenAI, Claude, Google Gemini, as well as specific tools and projects like GPT 5.5, Project Deal, and Augustusbank. It targets intermediate and advanced users interested in AI’s future development and integration in the economy.

• Gemini 3.5: THIS problem everyone overlooked & what “Omni” can REALLY do! (+AI Act Update Interview)
  24.5.2026, 08:15:20

  The video summarizes the major updates from Google I/O, including:

  1. **Gemini 3.5 Flash**: A new model that leads according to benchmarks but is rated disappointing due to high costs and limited use cases. It’s more expensive than its predecessor and performs worse on programming tasks than other models like GPT 4.7 and GPT 5.5.

  2. **Gemini Omni**: A new multimodal AI model for video editing, integrated into the Gemini app. It enables editing videos through chat commands and offers high accuracy, though currently only for AI-generated videos.

  3. **Gemini Spark**: Google’s answer to personal AI agents with access to the entire Google ecosystem. Currently in beta and only available in the US.

  4. **Antigravity 2.0**: An update that replaces the open-source Gemini CLI and is offered as a closed-source version. Critics complain about bugs and missing features.

  5. **Android app creation**: Through Google AI Studio, entire Android apps can now be created with a single prompt, which is particularly interesting for beginners.

  6. **Google Search**: The biggest update in 25 years, expanding the search bar with AI-powered recommendations and multimodal content. SEO remains important, but user behavior is changing.

  7. **Smart glasses**: New intelligent glasses in cooperation with Samsung, offering Gemini integration and multimodal functions.

  8. **AI watermarks**: Google expands the AI watermark Synti to search and Chrome to mark AI-generated content. OpenAI and other providers are adopting the standard.

  9. **Legal updates**: The EU’s AI omnibus brings relief for SMEs and shifts deadlines, while training requirements are eliminated. The digital omnibus also covers GDPR topics.

  10. **SpaceX and Cursor**: Cursor is working with SpaceX on a new model and has released Composer 2.5. OpenAI is offering guaranteed computing capacity.

  The video explicitly covers Google (Gemini, Antigravity, Smart Glasses), OpenAI (Codex, guaranteed computing capacity), and specific tools like Cursor. It’s intended for intermediate and advanced users.

Fireship (2 new videos)

• The forgotten developer who saved JavaScript…
  29.5.2026, 17:06:48

  The video tells the story of JavaScript and how it evolved from a despised programming language into one of the world’s most popular languages. A central focus is the role of Jeremy Ashkenas, who significantly shaped JavaScript’s development through three major projects: Underscore.js, CoffeeScript, and Backbone.js. Underscore.js provided a standard library for JavaScript, CoffeeScript improved the syntax, and Backbone.js enabled the structuring of JavaScript applications. These innovations helped modernize JavaScript and make it suitable for more complex applications. The video emphasizes that many of these improvements are taken for granted today, but were revolutionary at the time.

  Final comment: The video covers JavaScript and specific tools like Underscore.js, CoffeeScript, and Backbone.js, and is aimed more at intermediate and advanced developers.

• 10 weird OSS projects you need right now…
  26.5.2026, 17:53:11

  The “Code Report” video from May 26, 2026 showcases 10 unusual and creative software projects created by developers with a penchant for the unnecessary and absurd. These include:

  1. **Ratty**: A 3D terminal emulator based on the Bevy game engine that uses a spinning 3D cube as a cursor. While it consumes 300 MB of RAM, it offers unique features like tilting the terminal in 3D space.
  2. **Terminal Phone**: An open-source push-to-talk app that runs entirely as a Bash shell script and requires no servers or accounts. It uses Union addresses for identities and is end-to-end encrypted.
  3. **They Live Ad Blocker**: An ad blocker inspired by John Carpenter’s 1988 film “They Live” that portrays advertising as alien mind control, transforming web browsing into an 80s sci-fi horror experience.
  4. **CUDA Oxide**: A Nvidia project that allows GPU cores to be written in Rust instead of C++, making CUDA code development safer and more accessible.
  5. **Wario Synth**: A tool that converts songs into Game Boy chiptunes by using the Web Audio API to synthesize pulse waves and noise.
  6. **Jmail**: A project that emulates Gmail as if you were Jeffrey Epstein, facilitating access to the Epstein files.
  7. **Epstein Exposed**: A search database for the Epstein files with a network graph showing connections of “Deep State” actors.
  8. **Exipedia**: A Wikipedia app that works like TikTok, allowing endless scrolling through Wikipedia articles with data processed entirely in the browser.
  9. **Pewtor**: A project that emulates a complete desktop operating system in the browser, with applications like Notepad, code editor, and terminal.
  10. **Honker**: A SQLite extension that integrates Postgres-like features such as PubSub, task queues, and cron jobs directly into the database file.

  The video covers a variety of open-source tools and projects from individual developers and major companies like Nvidia. It targets a technically savvy audience interested in innovative and unusual software solutions.

Greg Baugues

No new videos in this period.

AI and Strategy | Le SamourAI

No new videos in this period.

Julian Ivanov | AI Automation (2 new videos)

• Claude can now generate Hollywood movies (Seedance 2.0)
  28.5.2026, 17:24:57

  The video demonstrates how to generate cinematic videos and images using the Hixfield platform and the AI tool Cloud. Hixfield provides access to various models such as CDE 2.0 for video and Nano Banana for image generation. The process is simplified through an MCP connector that outsources video production to Cloud. Cloud handles prompting, model selection, and settings. Additionally, Skills can be used to achieve consistent and reproducible results. These Skills assist with character creation and video production. The video demonstrates the creation of a short film and explains Hixfield’s pricing structure, where CDE 2.0 is expensive but high-quality.

  The video explicitly covers the tools Hixfield, Cloud, CDE 2.0, Nano Banana and is more suitable for intermediate and advanced users.

• Build & publish apps with Claude Code — Tutorial for beginners
  24.5.2026, 15:43:12

  The video shows step-by-step how beginners can develop a web application using Cloud Code and deploy it on a server in Germany. The webapp includes logins, user accounts, and a database. Cloud Code handles programming and database setup completely while the user only needs to provide instructions. As an example, a habit tracking app is created that includes user management, database, and various views. The required tools are Cloud Code (Anthropic), Supabase (database), and Hostinger (hosting). Cloud Code is used in the Cloud Desktop app, the database is set up with Supabase, and hosting is provided via Hostinger with Node.js web hosting. The app is developed locally, the code is uploaded to GitHub, and then deployed to the server. The app is then accessible via its own domain on the internet. The video is suitable for beginners.

  Featured AI tools/models/providers: Cloud Code (Anthropic), Supabase, Hostinger, GitHub.

Kyle Balmer | AI with Kyle (3 new videos)

• The AI Job Audit: Will AI Take Your Job?
  29.5.2026, 05:00:04

  The video explores the impact of AI on jobs, emphasizing that it’s not about sudden job losses but rather subtle transformations. The speaker explains that every job consists of various tasks that are affected differently by AI. He distinguishes between “exposed” tasks that can be automated by AI (e.g., invoice reconciliation, reporting) and “defensible” tasks that require human skills (e.g., customer service, judgment). The speaker introduces a diagnostic tool to help analyze your own tasks and develop strategies to prepare for these changes. He warns that entry-level positions and young workers may be particularly affected, and emphasizes the importance of skills like empathy and emotional intelligence that AI cannot easily replace. The video targets intermediate and advanced users.

  Explicitly discussed were Claude, open-source tools, and specific tools like Xero.

• Here’s how I find what to automate with AI (and what NOT to)
  27.5.2026, 05:00:00

  The video covers a viral Twitter prompt shared by Greg Brockman, President and Co-founder of OpenAI. The prompt helps identify and automate recurring workflows by optimizing interaction with artificial intelligence. The author explains how to use the prompt to recognize patterns in your own workflows and automate them to boost productivity. He emphasizes the importance of first conducting an audit of your work to identify truly relevant and repeated tasks, rather than simply implementing trendy automations. The prompt can be used with various AI tools like Codex, ChatGPT, and Claude. The author demonstrates how to apply the prompt and discover further automation opportunities through targeted questions and conversations with AI. He stresses that not every task requires complex automation, and shows different methods for task automation, from simple checklists to complex agents and scripts. The focus should be on finding simple and efficient solutions that truly add value.

  Final note: The video explicitly covers OpenAI (Codex), ChatGPT, and Claude and is aimed at intermediate and advanced users.

• Google I/O: What You Actually Need to Know
  25.5.2026, 05:30:12

  The video analyzes the Google I/O Conference and evaluates Google’s presentations and announcements in artificial intelligence. The speaker is not particularly impressed by the conference but sees some important elements for the future of AI, particularly the different philosophies of Google and OpenAI. Google focuses on integrating AI models into their existing products and services, while OpenAI treats the models themselves as the product.

  A central point is the introduction of the new AI model Gemini 3.5 Flash, which is not rated particularly well and lags behind other state-of-the-art models. The speaker emphasizes the importance of distribution and product access, with Google having a major advantage through its existing infrastructure and user base. This is illustrated by the example of Slack versus Microsoft Teams, where distribution is often more important than product quality.

  Another important aspect is the integration of AI into Google Search, presented as an existential threat to Google’s traditional search business. Google plans to integrate generative AI directly into search, which could fundamentally change how people search for and consume information on the internet. This could also impact other SaaS companies, as Google could embed lightweight software solutions directly into search results.

  The speaker also discusses the introduction of agents like Spark and Antigravity, which so far are not convincing. Overall, the speaker sees the biggest news in Google’s strategic direction of integrating AI into search, which could long-term transform how people use the internet.

  **AI Tools/Models/Providers:** Google (Gemini 3.5 Flash, Spark, Antigravity), OpenAI (ChatGPT, Codex), Anthropic (Claude), Cursor (Composer 2.5)
  **Target audience:** Intermediate to Advanced

Leon van Zyl (2 new videos)

• Claude Code Is Too Expensive. Use This Instead
  28.5.2026, 13:00:03

  The video demonstrates how to use the open-weight model Minimax M2.7 with Claude Code to build a Reddit clone app. The creator explains the setup process, including API key configuration and plan selection. Minimax M2.7 is presented as a cost-effective alternative to Claude Opus that offers similar performance and comparable quality. The process involves using Claude Code in various modes such as planning, editing, and agent view to develop and test the app. The creator emphasizes the model’s efficiency and speed, as well as the ability to use detailed prompts to optimize usage. Additionally, the unique training methodology of Minimax M2.7 is explained, where the model was involved in its own further development.

  The video explicitly focuses on the open-weight model Minimax M2.7 and is better suited for intermediate users.

• Claude Code Advanced Workflow – Build & Ship Real Apps
  26.5.2026, 12:25:38

  The video showcases a detailed workflow for using Claude Code to develop web applications. The creator, a software engineer with nearly 20 years of experience, explains how to efficiently set up projects, create design systems, and implement complex applications in a structured manner.

  1. **Project Setup**: The creator recommends creating a reusable agent skill that contains a complete technology stack description. This skill can then be integrated into new projects to automate project setup. This saves time and ensures that all necessary dependencies and configurations are correctly configured.

  2. **Design System**: The creator emphasizes the importance of a clear design system. He demonstrates how to use Claude Code to create and implement a design system that ensures all components and pages of the application are styled consistently. He mentions tools like Google Stitch and Claude Design that can help with this.

  3. **Structured Implementation**: The creator explains how to create a detailed implementation plan divided into phases and tasks. This enables parallel implementation of various application components, accelerating the development process.

  4. **Testing and Monitoring**: The creator shows how to perform security audits and UI tests in parallel with implementation. He uses Claude Code’s loop function to regularly conduct security audits and UI improvements.

  5. **Excalidraw Diagrams**: The creator demonstrates how to use Excalidraw diagrams to visualize the application’s architecture. This helps with overview and understanding of the various components and their interactions.

  At the end of the video, the developed application is tested and successfully scrapes, summarizes, and saves articles. The creator emphasizes the efficiency and structure of his workflow and encourages viewers to apply similar techniques in their own projects.

  **Final Note**: The video explicitly focuses on Claude Code and is intended for intermediate to advanced users.

Liam Ottley

No new videos in this period.

Mark Kashef (1 new video)

• The Claude Update Everyone Missed (Dynamic Workflows)
  29.5.2026, 16:00:10

  The video demonstrates the use of dynamic workflows in Claude Code, a version of the Claude AI model, to efficiently tackle large-scale tasks. The user shows how to build a team of agents that work in parallel to analyze and synthesize extensive documentation such as contracts, leases, and proposals. One example is the creation of a due diligence report from over 70 documents, completed in 20-30 minutes instead of the hours it would normally take. Dynamic workflows enable the creation of agents that collaborate to conduct comprehensive analyses and validate insights. The user emphasizes that this feature is particularly useful for large, complex tasks requiring more than five or six agents. Various practical use cases from different industries are presented, including law, finance, healthcare, insurance, real estate, software development, marketing, human resources, and compliance. However, the user warns that this feature is not intended for everyday tasks and causes significant token consumption. At the end, the user provides links to a community and the prompts used.

  The video explicitly addresses the Claude AI model (Claude Code) and is better suited for intermediate to advanced users.

Matt Pocock (2 new videos)

• Can Cursor’s HARDCORE Review Skill Stop The Slop?
  28.5.2026, 14:00:25

  The video demonstrates how the author tests a template for a “thermonuclear code-review” skill discovered from the Cursor team. The skill performs comprehensive code quality assessment, focusing on implementation quality, maintainability, abstraction quality, and code health. The author applies the skill to the last five pull requests of his open-source project Sandcastle and presents the results. The skill identifies several structural issues and proposes improvements, including splitting large files, creating abstractions, and removing duplicates. The author finds most suggestions helpful but criticizes the skill’s length and redundancies, as well as the lack of guidance on testing and feedback loops. He suggests shortening and focusing the skill.

  The skill doesn’t directly address specific tools and models, but is part of a broader discourse on using AI for code reviews, which could be of interest to intermediate and advanced developers.

• 9 Things People Get Wrong With My /grill-* skills
  25.5.2026, 13:22:40

  The video addresses the effective use of “Grill Me” and “Grill with Docs” skills, which serve as alternatives to planning modes in agents. The author emphasizes that these skills aim to achieve shared understanding through targeted questions, and that answer quality depends on the user’s planning competency. The video highlights nine common mistakes when using these skills, including attempting to answer high-fidelity questions during a grill session, choosing too broad a scope, being passive toward the agent, failing to estimate decisions made during the session, and using an insufficiently capable model. The author recommends running sessions in parallel to increase efficiency and stresses the importance of proper context management.

  Final note: The video addresses specific AI skills like “Grill Me” and “Grill with Docs” and is intended more for intermediate or advanced users.

Melvynx (6 new videos)

• Opus 4.8 : meilleur modèle au monde (ou Codex…)
  29.5.2026, 06:07:18

  The video tests and compares the new Opus 4.8 model from Cloud with GPT 5.5 across various tasks. Opus 4.8 was introduced as an improvement over Opus 4.7, featuring better judgment, honesty, and the ability to handle longer sessions. The test covers three main tasks: creating CLI documentation, implementing a notification feature for a thumbnail generation application, and updating a title in an application. Opus 4.8 delivers better results in most tasks, particularly in code quality and functionality. However, GPT 5.5 faces challenges in some areas, such as the notification feature, with code quality issues despite functional results. Opus 4.8 wins the comparison overall with a higher score. Additionally, new features from Cloud Code are introduced, such as Dynamic Workflows and an improved agent view, enabling the orchestration of subagents for complex tasks. The user expresses concerns about the practicality of these features.

  The video explicitly addresses the Opus 4.8 and GPT 5.5 models and is geared more toward intermediate to advanced users.

• Kombai 2.0 ajoute le design mode et change le code pour toujours (mieux et que Claude Design)
  28.5.2026, 16:00:33

  The video introduces the tool **Comb**, specifically developed for creating frontend designs with AI assistance. The focus is on the new **Design Mode**, which enables the creation of creative and engaging user interfaces. The user demonstrates how to use Comb to create various design variants for an inspiration card and integrate them directly into an existing application. The process involves defining style guidelines, generating design variants, and implementing the chosen designs into the code. The tool also offers integration with a browser to review and adjust changes in real time. At the end, an improved feedback dashboard interface is showcased. The video mentions that Comb is free to use up to 300 credits per month, with paid options available afterward.

  **AI Tools/Models/Providers:** Comb (proprietary AI), VS Code (integration), Convex (backend database) – geared more toward intermediate to advanced users.

• DeepSWE détruit les modèles chinois (et Claude… désolé les fans)
  27.5.2026, 16:00:20

  The video discusses the new Deep SWE Benchmark, which evaluates AI models’ capabilities in software engineering. Unlike previous benchmarks like SWE Bench Pro, Deep SWE measures model performance on realistic tasks involving more complex and lengthier code assignments. Results show that GPT-5.5 performs best with 70%, followed by GPT-5.4 with 56% and Claude Opus 4.7 with 54%. Models like Gemini 3.5 Flash and various Chinese models perform significantly worse. The benchmark also highlights model efficiency, with GPT-5.5 consuming fewer tokens and thus being more cost-effective. The analysis shows that GPT-5.5 delivers consistent and reliable results, while other models like Claude often forget requirements or cut corners. The benchmark is rated by many experts as realistic and useful, as it reflects actual AI model usage in practice.

  **Closing comment:** The video explicitly addresses GPT-5.5, Claude Opus 4.7, Gemini 3.5 Flash, and various Chinese models. It is geared more toward intermediate and advanced users.

• Pi AGENT : le remplacement ultime de Claude Code
  26.5.2026, 16:28:56

  The video shows an initial test of the tool **Pi**, an orchestrator or “harness” for AI agents, enabling the creation and management of complex workflows and tool chains. The creator tests Pi’s installation and core features, including integration of various AI models (e.g., OpenAI, Claude) and the use of plugins to extend the agent. Particular emphasis is placed on Pi’s flexibility to create and customize workflows and UI elements, as well as the ability to modify and extend the agent itself.

  The creator experiments with various plugins, such as a todo list plugin and a subagent plugin, to automate and manage tasks. He also demonstrates how Pi enables connecting the agent to various AI models and monitoring their costs. A critical note is made that using Pi can come with high costs, particularly when utilizing many agents and plugins simultaneously.

  At the end, the question is raised whether Pi’s flexibility and customizability justify the effort and costs, or if it might be better to rely on simpler, pre-built solutions.

  **Closing comment:** The video explicitly addresses the tool **Pi** and is geared more toward **intermediate** or **advanced** users familiar with AI agents and orchestration.

• Antigravity 2.0 : la PIRE copie que j’aie jamais vue ?
  25.5.2026, 16:00:06

  The video introduces Antigravity 2.0, a new tool from Google heavily inspired by other AI-powered developer tools like Codex. The creator compares the user interface and features of Antigravity 2.0 with Codex and finds that many elements were directly copied, which he regards as normal in the competitive AI industry. Despite these similarities, he tests the tool and demonstrates its features, including Gemini model integration and the ability to create and manage projects. However, he criticizes the user experience, particularly frequent permission requests and an unstable IDE that he describes as poorly designed and error-prone. Additionally, he compares the performance of Gemini models with those from other providers and finds they don’t reach the top tier in coding. Overall, he considers Antigravity 2.0 a functional but unremarkable tool that Google could significantly improve with more effort and better design.

  The video explicitly addresses Google’s Antigravity 2.0, Codex, and Gemini models and is geared more toward intermediate or advanced users.

• Les DEVS sont amoureux de Claude (et arrêtent de vouloir tester de nouvelles choses)
  24.5.2026, 16:00:34

  The video author reflects on his personal development in using AI tools, particularly Claude and Codex (OpenAI). He admits to having been “in love” with Claude and overestimating its capabilities while criticizing OpenAI. Through experience with high costs and limited options with Claude, he recognized the advantages of Codex, particularly its superior user interface and efficiency. He emphasizes the importance of being pragmatic and flexible, able to switch between different tools as needed. The author has reorganized his configurations to more easily switch between tools like Claude, Codex, and Cursor. He recommends choosing the best tools based on their current capabilities and costs, and warns against becoming emotionally attached to a specific tool. He concludes with an encouragement to use his configurations and tools to become more flexible.

  The video explicitly addresses Claude (Anthropic) and Codex (OpenAI) and is geared more toward intermediate or advanced users.

n8n (3 new videos)

• n8n Community Livestream: Women+ in Automation, Community Challenge & n8n Fest
  29.5.2026, 04:31:37

  The video is a demo of Cursor, an AI-powered code editor platform. It shows how to create a simple web server in Python using Cursor. The process includes creating a new project, writing code with the help of AI suggestions, and testing the server. The video demonstrates how Cursor can improve developer productivity through intelligent code completion and error fixing.

  The video is more suitable for intermediate or advanced users, as it assumes the viewer already has basic knowledge of Python and web development.

• Claude’s Workflows Actually Work Now | MCP Live Build
  28.5.2026, 17:12:27

  The video shows the process of “vibe coding” with n8n to create a Slack-based workflow review system. The creator uses Claude Desktop in combination with the n8n MCP and n8n Skills to develop a system that reviews and evaluates workflows in n8n. The focus is on planning and implementing the system, with the creator emphasizing the importance of clearly defining the desired output before starting development.

  The creator walks through the steps of setting up Claude Desktop, including installing plugins and configuring credentials for Slack and n8n. A Slack app manifest is created and the app is installed in the Slack organization. The creator also explains the differences between n8n, MCP, and Skills and how they work together to create a robust system.

  During the video, the creator encounters challenges such as properly integrating the Skills and fixing errors in the workflow logic. Through collaboration with Claude, these issues are resolved and the system is eventually tested successfully. The creator emphasizes the importance of error handling and documentation to ensure the system works reliably.

  At the end of the video, the system is tested successfully and the creator shares their experiences and tips for working with n8n and AI. He encourages viewers to try out the official version of the MCP and Skills to take advantage of these technologies.

  The video explicitly covers Claude and n8n and is more suitable for intermediate to advanced users.

• How a 1,000-Person Company Actually Uses n8n
  26.5.2026, 17:32:51

  The video shows how Zahar Romani, Director of Internal AI at Fullscript, managed to create over 1,500 workflows in less than a year and bring over 100 of them into production. She emphasizes the importance of democratizing AI tools by giving every employee access and lowering barriers for non-technical teams through workshops, templates, and global credentials. Key steps include running an AI hackathon, creating templates for common tasks like summarizing projects and sending Slack updates, and providing global credentials for seamless integration. Romani also highlights the cultural shift from “AI-first” to “people-first, AI-powered” to promote adoption and use of AI tools. She shares examples of successful workflows in sales, finance, and legal that have brought significant time savings and efficiency improvements. The key to success lies in continuous education, support from a team of engineers, and fostering a culture of innovation and learning.

  The video covers specific tools like n8n and emphasizes the importance of internal champions and a supportive culture for successful implementation of AI and automation. It is intended more for intermediate and advanced users who already have basic knowledge of AI and automation and want to scale these in their organization.

Nate Herk | AI Automation (5 new videos)

• Claude Code Dynamic Workflows Clearly Explained
  30.5.2026, 17:34:30

  This video covers the new dynamic workflows in Claude Opus 4.8.8 and compares them with other features like Skills, Sub-Agents, Agent Teams, and /goal. The creator explains that Workflows are a type of “cloud code” that can launch many parallel agents, which then consolidate their results. An example was analyzing 41 Skills compiled in an HTML file. The creator warns about the high costs, since a workflow can quickly consume many tokens. He recommends using Workflows only for specific, parallel tasks and not for simple requests. Additionally, the new Ultra-Code feature is mentioned, which uses Workflows by default and can be very expensive. The creator emphasizes that you should be aware of when to use which feature to save costs.

  This video explicitly covers Claude Opus 4.8.8 and is intended more for Intermediate to Advanced users.

• I Turned Claude Opus 4.8 Into My Entire AI Operating System
  29.5.2026, 14:36:34

  The video shows how the creator uses Claude Opus 4.8 as his personal AI operating system, functioning as his second brain and executive assistant. He explains his framework of four C’s (Context, Connections, Capabilities, Cadence) for building such a system and discusses the importance of context and optimizing usage. The creator shares his experiences migrating from various tools to Claude Code and emphasizes the importance of organization and continuous improvement processes. He also provides a free GitHub repo that serves as a starting point for building your own AI operating system. Additionally, he addresses the importance of security and the gradual rollout of automations, comparing it to learning to ride a bike.

  This video explicitly covers Claude Opus 4.8 and is intended more for Intermediate to Advanced users who already have experience with AI tools and want to further optimize their system.

• Opus 4.8 Just Dropped. Here’s How To Actually Use It.
  28.5.2026, 18:52:03

  This video covers the release of Claude Opus 4.8, positioned as the successor to Opus 4.7. Opus 4.8 is said to have improved judgment, greater honesty, and the ability to work independently for longer. Rate limits in Cloud Code have been increased to compensate for higher token consumption from higher effort levels. New features such as dynamic Workflows and the ability to manually adjust effort levels have been introduced. The creator emphasizes that while benchmarks are impressive, the actual performance of the model depends on the specific application. Opus 4.8 is meant to address issues from Opus 4.7 such as lack of persistence, excessive safety restrictions, and high token costs. The creator shares his first impressions and tips for optimal use of the model, including adjusting the effort level and clearly formulating tasks. Community reactions are mixed, with positive feedback on the improvements but also initial reports of bugs.

  This video explicitly covers Claude Opus 4.8 and is intended more for Intermediate to Advanced users.

• 100 Hours Testing Claude Code vs ChatGPT Codex (honest results)
  26.5.2026, 20:02:02

  The video compares OpenAI Codex and Claude Code, two AI-powered coding agents, based on features, pricing, and three specific use cases. It begins with a brief introduction to both tools, highlighting that Claude Code from Anthropic offers more customization options, while Codex from OpenAI has a more streamlined workflow. The comparison covers three tasks: creating a research report, a landing page, and an interactive dashboard. Claude Code demonstrates superiority in frontend work and complex planning, while Codex excels at research-intensive tasks and faster execution. Cost and token usage are analyzed in detail, with Codex being more efficient in token consumption. The video concludes with the recommendation to choose the respective tool based on your specific use case and emphasizes the rapid development of both tools.

  **AI Tools/Models/Providers:** OpenAI Codex, Claude Code (Anthropic)
  **Target Audience:** Intermediate

• The Playbook for a $100M AI Agency
  25.5.2026, 16:23:09

  **YouTube Video Summary:**

  The video is an interview with Devin Karns, CEO and co-founder of Custom AI Studio, discussing the future of AI agencies and strategies for a successful exit. Here are the key points:

  1. **Market Development and Value of Development**:
  – The value of development trends towards zero as AI systems become increasingly powerful.
  – Companies must focus on AI-native organizations to remain competitive.

  2. **Future of AI Agencies**:
  – Many AI projects being sold today won’t survive until 2027.
  – The focus should be on delivering solutions that provide real value to businesses rather than chasing short-term trends.

  3. **Strategies for a Successful Exit**:
  – Devin Karns shares his experiences and strategies for building an AI agency with high enterprise value.
  – He emphasizes the importance of relationships, trust, and the ability to understand clients’ true needs.

  4. **Five Things Devin Karns Wishes He’d Known Earlier**:
  – **Decide on a path**: Decide whether you want to build a lifestyle business or a high-exit-value business.
  – **Package your offering**: Develop a clear offering that highlights the value of your services.
  – **Charge true value**: Price your services based on the value you deliver, not the time you invest.
  – **Build your pipeline before you need it**: Establish relationships and a pipeline of potential customers before you really need them.
  – **Hire for the company you want to be**: Hire employees who share your vision and have the skills you need to scale your business.

  5. **Examples and Case Studies**:
  – Devin Karns shares examples of successful projects, such as reducing an e-commerce company’s refund rate from 21% to 16%, resulting in significant cost savings.

  **Final Note**:
  This video explicitly covers Claude, OpenAI, and open-source models as well as specific tools like Cloud Code and Co-Pilot. It is aimed at Intermediate and Advanced users who already have experience with AI and want to scale or optimize their business models.

NeuralNine (3 new videos)

• LangGraph Crash Course – Agent Workflows in Python
  29.5.2026, 15:32:01

  The video is a tutorial for LangGraph, a tool from the LangChain ecosystem that focuses on agent orchestration and modeling processes as graphs. Unlike LangChain, which is higher-level and simpler, LangGraph is more detailed and lower-level. The tutorial starts with an introduction to the differences between LangChain and LangGraph and recommends learning LangChain before LangGraph.

  The main part of the video is a hands-on course where examples are built and concepts are introduced as needed. Various concepts are covered such as routing, conditional edges, human-in-the-loop approval, and RAG (Retrieval-Augmented Generation). The course begins with environment setup, including installing LangChain, LangGraph, and an API key for an LLM provider (OpenAI).

  A simple graph is created starting with a start node, a prompt node, and an end node. The prompt node uses an LLM to generate a response. The course then progresses to more complex graphs that include classification nodes, conditional edges, and human-in-the-loop approval. It also shows how to create a custom state and pass information from one node to another.

  The video demonstrates how to visualize a graph and how to use LangChain 2 concepts like RAG and embedding models. It also shows how to create a custom state and pass information from one node to another. The video concludes with a summary of the concepts covered and a call to subscribe to the channel and enable notifications.

  The video explicitly addresses LangChain, LangGraph, and OpenAI and is aimed more at intermediate and advanced users.

• Never Use [ ] as a Default Argument in Python…
  27.5.2026, 14:50:33

  The video explains why you should never use mutable objects (such as lists, dictionaries, or sets) as default arguments in functions in Python. The reason is that these objects are initialized only once when the function is defined and are then reused on every function call. This causes changes to these objects in one call to be visible in other calls as well, often producing unexpected results.

  To avoid this problem, the author suggests using `None` as the default argument instead and initializing the object inside the function if it is `None`. In cases where a predefined object (such as default equipment) should be used as a default argument, he recommends creating a copy of the object to ensure that a new object is used each time.

  The video is more suitable for intermediate Python programmers, as it deals with a specific behavior of the Python language that may not be immediately obvious to beginners.

• MLFlow Crash Course: MLOps in Python
  25.5.2026, 15:56:30

  The video offers a crash course on MLflow, an open-source AI engineering platform and ML-Ops toolkit. It covers using MLflow for both GenAI and classical machine learning. The course begins with setting up a project and installing necessary packages, including MLflow, OpenAI, LangChain, and Mistral AI. The host demonstrates how to start MLflow and how to integrate existing code examples with MLflow to improve monitoring, logging, and evaluation processes. Various examples are shown, including the use of OpenAI, LangChain, and Mistral AI, as well as evaluating LLM systems and agents. Additionally, the creation and use of prompt templates, setting up an LLM gateway, and deploying an agent as a FastAPI endpoint are demonstrated. The second part of the video focuses on classical machine learning, with examples of using MLflow with scikit-learn and PyTorch, including model training, hyperparameter tuning, and checkpointing. The video is aimed at intermediate users who already have experience with Python, LangChain, OpenAI, and classical machine learning libraries such as scikit-learn and PyTorch. It does not explicitly address specific AI tools or models such as Claude, OpenAI, Gemini, or open-source tools, but rather focuses on MLflow as the central tool.

Nic Conley

No new videos in this period.

Nick Saraev

No new videos in this period.

Niklas Steenfatt (2 new videos)

• I Gave ALL AI Agents the Same Task
  27.5.2026, 16:54:40

  The video shows a comparison of four AI agents (Cloud Code, Codex, Hermes, and Amadeus) solving various tasks. The tasks include summarizing tweets, recommending the best AI agent, creating graphics, programming a habit tracker and replicating a website, as well as making money. The agents were installed and tested on a Hostinger VPS using Paperclip software.

  The tasks revealed different strengths and weaknesses among the agents. Cloud Code and Amadeus performed particularly well on programming tasks, while Hermes and Codex sometimes delivered similar results, suggesting copying. For the task of making money, the agents proposed various methods, though some were unrealistic or uncreative.

  The video explicitly covers the AI agents Cloud Code, Codex, Hermes, and Amadeus, as well as Paperclip software and Hostinger VPS. It’s better suited for intermediate and advanced users as it covers technical details and specific AI tools.

• LIFE UPDATE!!!!
  24.5.2026, 20:09:03

  The video features the YouTuber’s marriage proposal to his girlfriend in the desert during South Africa’s Burning Man event. He shares his emotions and his girlfriend’s surprise as she accepts the proposal. The YouTuber reflects on the significance of choosing one partner from 8 billion people and the criteria involved in that decision. He emphasizes that physical and emotional chemistry matters more than shared interests, and that long-term relationships require work. He also discusses the cool effect and the importance of open communication in relationships. The YouTuber recommends couples therapy and honest conversations to build a stable and happy partnership. He shares his personal journey and how he moved from initial doubts to a confident decision. At the end, he promotes the crypto broker Kraken and offers a bonus for new users.

  Final comment: The video doesn’t cover specific AI tools or models and is better suited for intermediate and advanced viewers as it shares in-depth personal reflections and life experiences.

No Priors: AI, Machine Learning, Tech, & Startups (1 new video)

• Building an AI Guardian for Enterprise with Onyx Security CEO Maxim Bar Kogan
  28.5.2026, 10:00:14

  The video is an interview with Maxim Kogan, co-founder and CEO of Onyx Security, an Israeli startup that develops agents to monitor other AI agents. The conversation focuses on the challenges and risks associated with increasing AI agent autonomy in enterprises, as well as the solutions Onyx Security offers.

  Kogan explains that the idea for Onyx Security was inspired by AutoGPT, an early autonomous agent based on large language models (LLMs). He emphasizes that enterprises increasingly realize they don’t have complete control over AI agent adoption, but must take measures to reduce the likelihood of illegitimate or incorrect actions. Onyx Security trains models and builds agents that can monitor other agents to ensure their actions are legitimate.

  The company offers a secure control layer that enables enterprises to connect their AI agents to Onyx to monitor their actions and minimize potential risks. Kogan also discusses the various categories of AI agents deployed in enterprises, emphasizing that autonomous coding agents and assistants are the fastest-growing category.

  He addresses the challenges existing security solutions face in keeping up with new risks created by AI agents, emphasizing the need for specialized controls designed for these systems. Kogan also discusses the importance of mechanistic interpretability and the need to better understand the internal processes of AI models to control them long-term.

  The interview also covers the growing threat of automated vulnerability research and the need for enterprises to prepare for these new risks. Kogan stresses that enterprises should take a nuanced view of AI adoption based on their risk profile and size.

  At the end of the interview, Kogan discusses the unique capabilities of the Israeli ecosystem in security and AI, emphasizing the importance of understanding the needs and daily work of security teams to develop effective security products.

  The video explicitly features AI models and providers such as AutoGPT, OpenAI, Anthropic, and Cloud Code and is aimed at intermediate and advanced audiences.

Productive Dude

No new videos during this period.

Sebastien Dubois (1 new video)

• Obsidian + AI: The System I’ve Been Building For 4 Years (OSK v4)
  27.5.2026, 09:58:16

  The video introduces the fourth version of the “Obsidian Starter Kit,” fully equipped with AI capabilities. The Starter Kit is an extension for Obsidian that provides an organized, scalable, and well-structured system. Version 4 integrates a complete AI assistant system that facilitates the use of AI within the vault. A central element is the “Receptionist,” which serves as an interface for interacting with various AI agents and skills.

  The system comprises numerous AI agents and skills divided into different categories such as productivity, books, discovery, health, ideas, identity, media, people, reading, research, and more. These skills enable automation of tasks like creating tasks, managing books, discovering old notes, tracking health data, and organizing ideas. Additionally, there’s an identity system that allows AI to understand and utilize personal information like the user’s history, work style, and values.

  Another feature is support for LLM wikis, inspired by Andrej Karpathy. These wikis enable creating and managing a markdown-based knowledge base that is organized and expanded by AI. The video also shows the integration of a plugin called “Claudian,” which enables connection to Claude AI, as well as the use of a command-line interface for interacting with AI.

  The video is better suited for intermediate to advanced users, as it assumes viewers are already familiar with Obsidian and basic AI concepts. It covers specific tools and plugins such as Claude AI and the Obsidian Starter Kit Plugin.

Tech With Tim (4 new videos)

• I Tried 100+ Claude Code Skills. These 6 Are The Best.
  29.5.2026, 10:57:35

  The video showcases six useful Skills for Claude Code that add additional functions and capabilities. The Skills are:

  1. **G Stack**: A bundle of 23 Skills developed by Gary Tan, CEO of Y Combinator. It’s designed specifically for founders, CEOs, and developers who want to build software products with Claude Code. Key Skills in this bundle include Office Hours, Plan, CEO Review, Review, Investigate, Design, and QA. Installation is done by copying and pasting a command into the Claude Code terminal.

  2. **Hosting or MCP Server and Hosting or Agent Skills**: These Skills enable you to deploy applications directly from Claude Code. You’ll need a Hosting or account, with a Business plan at $4 per month recommended. Configuration is done by adding an MCP server and an API token to Claude Code.

  3. **Fire Crawl**: Enables crawling and scraping of web pages, extending Claude Code’s standard functions. Fire Crawl can bypass security features of websites and is more efficient at collecting data. Installation is done by adding a Skill file link to Claude Code.

  4. **Humanizing Skill**: Makes Claude Code outputs more human-like, which is particularly useful for emails, social media posts, and other text. Installation is done by copying and pasting two commands into the Claude Code terminal.

  5. **Composio**: A tool that simplifies tool management in Claude Code. It enables connecting various applications like Gmail, Google Drive, and Notion through a central platform. This saves tokens and improves accuracy. Installation is done by adding an API key and a command to Claude Code.

  6. **Vibe Skill**: Checks applications for security vulnerabilities and weaknesses. It should be used before deploying an application to ensure no API keys are leaked or unauthorized access to data exists. Installation is done by copying and pasting a command into the Claude Code terminal.

  The video explicitly covers Claude Code and is suitable for intermediate users.

• STOP Building Apps With Supabase (Use THIS Instead)
  28.5.2026, 13:00:34

  The video demonstrates how to perform AI-native development in 2026 using tools like Cursor and INS Forge. INS Forge is a backend platform specifically designed for use with AI agents, enabling you to build robust and scalable applications. The tutorial shows the creation of a RAG (Retrieval-Augmented Generation) application where users can upload documents and chat with them to ask questions and get summaries. The application features authentication, database connections, model integration, and daily summaries.

  The tutorial begins with creating a new project in Cursor, a code editor optimized for working with AI agents. INS Forge is then installed and configured to provide backend functions. The user creates a plan for the application and instructs the AI agent to build various application components such as databases, authentication, and edge functions. The AI agent then automatically generates the code and configuration for the application.

  After creating the application, it’s tested locally and then deployed to a live URL. The user can log in, upload documents, and chat with them to ask questions and get summaries. The tutorial also shows how to create different branches for development and production to manage the application safely and efficiently.

  The video explicitly covers Cursor and INS Forge and is more suitable for intermediate to advanced users.

• AI engineer salary – What to expect: Junior to senior
  27.5.2026, 12:30:42

  The video discusses current salaries and career paths in AI engineering, particularly in the USA. It begins with entry-level salaries (0-2 years of experience) ranging from $115,000 to $150,000, with total compensation including bonuses and stock reaching up to $173,000. Mid-level engineers (3-5 years of experience) earn between $155,000 and $220,000, with specializations like LLM integration or MLOps enabling higher salaries. Senior engineers (7+ years of experience) can achieve base salaries of $200,000 to $312,000, with total compensation often exceeding $400,000, particularly at top companies like Google or OpenAI. Factors such as location, company stage, and specialization significantly influence salaries. The video emphasizes the importance of practical experience in AI development and integration, not just theoretical knowledge.

  The video specifically mentions companies like Google, OpenAI, and FANG companies and is aimed at intermediate and advanced audiences.

• How to learn Machine Learning like a GENIUS and not waste time
  26.5.2026, 12:48:45

  The video provides a structured learning path for Machine Learning (ML) designed to avoid common mistakes such as getting stuck in theoretical knowledge without practical application. The speaker emphasizes the importance of building projects early and continuously rather than studying theory for months. The learning path includes several steps: First, Python fundamentals are covered, followed by necessary mathematical foundations like linear algebra, probability, and calculus basics. Next, core ML algorithms are addressed including supervised and unsupervised learning, with focus on practical application using libraries like scikit-learn. The following step introduces Deep Learning with PyTorch and important architectures like CNNs, RNNs, and Transformers. Finally, career-relevant skills such as MLOps, data wrangling, feature engineering, version control, and cloud platforms are covered. The speaker recommends spending 70% of learning time on practical projects and 30% on theory, and advises learning publicly and completing projects from start to finish. The estimated time to prepare for employment is 6 to 9 months with disciplined learning.

  The video covers specific tools and libraries such as Python, NumPy, Pandas, Matplotlib, scikit-learn, PyTorch, and cloud platforms like AWS, GCP, and Azure. It is aimed at intermediate learners who already have basic programming knowledge and want to specifically prepare for a career in Machine Learning.

TheAIGRID (3 new videos)

• Googles New AI Glasses Will Change AI Forever
  30.5.2026, 17:50:46

  The video covers the announcement of Google’s new Gemini AI glasses, unveiled at Google I/O 2026. There are two versions: an audio-only version launching this fall with partners like Warby Parker, Gentle Monster, and Samsung, and a display version with a heads-up display in the lens still in prototype phase. The audio glasses offer comprehensive assistance through Gemini without using your hands or checking your phone. They can handle tasks like navigation, placing orders, and managing text messages. The display version shows information directly in your field of view, such as Uber pickup details and live translations. The video emphasizes the significance of this technology, which brings AI interaction from the digital world into the real world, making daily life easier.

  The video explicitly covers Google’s Gemini AI and is geared toward intermediate and advanced viewers.

• Googles New Statement On AGI Just Stunned Everyone
  28.5.2026, 08:45:18

  The video discusses the current debate around Artificial General Intelligence (AGI) and centers on the perspective of Demis Hassabis, CEO of Google DeepMind. Hassabis argues that today’s AI systems, despite impressive breakthroughs like solving complex mathematical problems, are still far from true AGI. AGI requires not only the ability to tackle specific tasks but also broad cognitive abilities like creativity, reliability, and deep understanding of the world.

  The discourse is enriched by various viewpoints, including Gary Marcus, who points out the unpredictability and unreliability of current AI systems, and Marc Andreessen, who claims AGI has already arrived since systems surpass human experts in many domains. Helen Toner emphasizes the vagueness of the AGI term and suggests focusing on the specific capabilities that exist and which are still missing.

  The video highlights that while current AI systems are powerful enough to transform industries, they still lack the reliability and generality required for true AGI. It stresses that the AGI debate is not merely academic but has practical implications for AI implementation, regulation, and assessment.

  Final note: The video covers various AI models and providers, particularly Google DeepMind and OpenAI, and is aimed at an advanced audience engaged with the nuances and challenges of AI development.

• How To Use Google Omni – Google Omni Tutorial
  27.5.2026, 14:30:25

  The video demonstrates how Google Omni works, a multimodal tool for creating and editing videos from text, image, video, and audio inputs. The focus is on using Google Flow for more professional applications, with Omni Flash highlighted as an improved model over V3.1. It explains how Omni divides videos into multiple scenes and how users can control these scenes through precise instructions. The video also emphasizes the importance of physical realism in generated videos and the ability to edit videos by changing terrain, background, and time of day. The video also showcases advanced features like adding text or logos to objects, creating explainer videos, and combining different inputs for varied results. It points out limitations in depicting real or copyrighted characters and presents hidden features like converting sketches into realistic videos and using storyboards to control scene sequences.

  The video explicitly covers Google Omni, Gemini, and Google Flow and is geared toward intermediate to advanced users.

Theo – t3․gg (5 new videos)

• Anthropic fights back
  29.5.2026, 08:57:15

  The video discusses the latest version of Anthropic’s Claude model, Opus 4.8, and its performance compared to other models, particularly those from OpenAI. The speaker shares his experiences with the model, both positive and negative, and covers various benchmarks and new features in Claude Code.

  Key points include:
  – Opus 4.8 has high benchmark results, particularly on SWE Bench Pro, but worse results on Terminal Bench 21.
  – The model is more honest and less lazy than previous versions, leading to better and more thorough responses.
  – New features in Claude Code, such as Ultra Code and dynamic Workflows, enable more complex tasks but consume many tokens.
  – The speaker had mixed experiences with the model, including some hallucinations and CLI issues.
  – Opus 4.8 is a significant improvement over previous versions, but it’s unclear whether it surpasses OpenAI’s GPT-5.5.
  – The speaker mentions that Anthropic is working on more cost-effective models and a new model class with higher intelligence known as Mythos.

  The video is more suitable for intermediate or advanced users, as it covers technical details and benchmark comparisons. Anthropic’s Claude (particularly Opus 4.8), OpenAI’s GPT-5.5, and specific tools like Claude Code and Code Rabbit are explicitly discussed.

• Holy sh*t I think Anthropic is profitable now
  28.5.2026, 11:21:33

  The video discusses the financial situation of AI companies, particularly Anthropic’s sudden profitability, and analyzes the reasons behind it. Anthropic has generated significant revenue through a combination of strategic partnerships with cloud providers like AWS, Google Cloud, and Azure, as well as the introduction of powerful models like Claude 2 and Opus 45. The availability of Anthropic models on multiple cloud platforms, in contrast to OpenAI models which run mainly on Azure, has given them a significant market advantage. Additionally, Anthropic has increased revenue per customer through price adjustments and increased token usage. Anthropic’s sudden profitability is also attributed to limited compute availability and the strategic decision to invest less in future compute capacity than OpenAI. The video argues that Anthropic achieved a decisive breakthrough with the introduction of Opus 45, which revolutionized expectations and the use of AI models in enterprises. Despite current profitability, the question remains whether this is sustainable, particularly given high operating costs and dependence on limited computing resources.

  The video explicitly addresses Anthropic, OpenAI, AWS, Google Cloud, Azure, Claude, Opus, and is intended for intermediate or advanced viewers.

• How I code with AI changed a lot
  27.5.2026, 10:36:21

  The video shows a detailed revision of the author’s workflow when building with AI tools, particularly compared to his earlier approach. Here are the key points:

  1. **Workflow Changes**:
  – The author completely revamped his workflow after realizing many of his earlier recommendations were outdated.
  – He now primarily uses GPT-5.5 and has significantly reduced his use of Claude models.

  2. **Tools and Models**:
  – **GPT-5.5**: The author prefers this model for its performance and generous usage limits on the $200/month plan.
  – **Codex App and T3 Code**: He uses these tools for development, considering T3 Code more stable and reliable, especially for remote work.
  – **Remote Coding**: The author emphasizes the benefits of remote coding, particularly the ability to work from various devices without interrupting work.
  – **Diverse Harnesses**: He experiments with different harnesses like the Codex harness and Cursor harness, but prefers the Codex harness for its simplicity and efficiency.

  3. **Prompt Design and Context Management**:
  – The author places great emphasis on prompt quality and context management. He gives the model clear instructions and uses screenshots to provide feedback.
  – He avoids complex prompts and prefers simple, clear instructions that the model can easily understand.
  – He uses HTML plans to better control the models and visualize results.

  4. **PR Workflow and Code Review**:
  – The author uses PRs (Pull Requests) as artifacts for reviews and integrates tools like Code Rabbit and Macroscope for automated code reviews.
  – He emphasizes the importance of not leaving PRs open too long to avoid conflicts and outdated changes.

  5. **Simple Workflow**:
  – The author aims to keep his workflow as simple as possible to increase productivity. He avoids excessive complexity and focuses on efficient communication with AI models.

  **Concluding remarks**: The video explicitly addresses OpenAI (GPT-5.5), Codex, T3 Code, and various harnesses. It’s intended for intermediate to advanced users who already have experience with AI tools and want to optimize their workflow.

• Claude Code vs Codex vs Cursor (an honest comparison)
  26.5.2026, 08:39:38

  The video provides a philosophical comparison of AI coding tools Claude Code, Codex, and Cursor without focusing on technical capabilities or specific tasks. The focus is on the fundamental differences in the approach and goals of these tools.

  **Claude Code** is described as a tool designed to meet developers in their familiar environment, the terminal. It’s designed to start quickly and easily without requiring changes to other tools. Claude Code has heavily focused on using AI in the terminal environment and offers features like automatic Git commits and pushes. A central characteristic is the emphasis on productivity and the “feeling” of productivity, which is achieved through visual effects and an appealing user interface. Anthropic, the company behind Claude Code, also uses the tool as a marketing instrument to demonstrate the strengths of their models. However, there are differences between internal use at Anthropic and the external version, which can lead to some inconsistencies.

  **Codex** is presented as a tool aimed at solving practical problems and increasing actual productivity without relying on visual effects or marketing aspects. It’s developed by OpenAI and designed to work in a stable and reliable environment. Codex values token efficiency and attempts to improve models so they consume fewer tokens without compromising accuracy. The user interface is simple and functional, and the tool is used intensively by OpenAI employees themselves, leading to higher quality and stability.

  **Cursor** is described as a tool that focuses on the use of cloud agents capable of launching and testing complete graphical Linux instances. Cursor offers a unique way to integrate agents into Slack or other tools, thus increasing collaboration and efficiency. Cursor also has a strong internal testing culture where new features are thoroughly tested before being released to users.

  The video concludes by emphasizing that choosing the right tool depends on individual needs and workflows. Claude Code is well-suited for developers who need motivation or feel uncertain, while Codex is suitable for experienced developers seeking a reliable and efficient tool. Cursor is ideal for teams looking for a comprehensive solution for using AI in the cloud.

  The video explicitly addresses the AI tools Claude Code (Anthropic), Codex (OpenAI), and Cursor and is intended for intermediate and advanced users.

• Cursor just crushed Claude Code
  24.5.2026, 20:56:58

  The video discusses the release of Composer 2.5, a new model from Codium specialized in code tasks and described as highly effective and fast. The speaker emphasizes that Codium demonstrates impressive results despite limited external benchmarks and challenges the strength of major AI labs. The video also explains the pricing structure of AI models, where input and output tokens as well as token usage efficiency play a role. Composer 2.5 is presented as a cost-effective and powerful alternative to more expensive models like GPT-5.5 and Opus 4.7. The speaker highlights Codium’s collaboration with SpaceX AI, which gives them access to significant computing resources and data. The challenge of continuous integration (CI) and the benefits of Blacksmith as a faster and cheaper CI service are also mentioned. The video concludes with speculation that Codium might have the best AI for code in the near future.

  The video explicitly addresses Codium’s Composer 2.5, OpenAI, Anthropic, and specific tools like Blacksmith. It’s intended for intermediate to advanced users.

Tim Carambat (3 new videos)

• A 1-Bit Image Model Just Launched And It’s Great!
  29.5.2026, 17:45:31

  The video covers the use of local image generation models, particularly the Bonsai Image models developed by Prism ML, which are based on Black Forest Labs’ Flux 2 Klein 4B model. The author, Timothy Carambat, founder of Anything LLM, explains the benefits of these models, which through a special retraining method achieve significantly reduced file size and lower memory requirements without substantial quality loss. He compares the performance of the binary and ternary versions of the model with the quantized version on Ollama as well as the full version on an H100 GPU. The ternary version shows the best results with significantly lower memory requirements of approximately 3.7 GB compared to 13 GB for the full version. The author emphasizes the importance of pipelines and prompt engineering for better results and concludes that the ternary version is a viable solution for local image generation. He closes with hope for future developments, such as integration into standard tools and the possibility of using even larger models with similar optimizations.

  **AI Tools/Models/Providers:** Prism ML, Black Forest Labs, Ollama, MLX, H100 GPU
  **Target Audience:** Intermediate

• I Need To Rant About Data Centers Real Quick
  28.5.2026, 19:38:51

  The video by Timothy Carambat, founder of Anything LLM, discusses current developments and challenges related to the construction of data centers in the USA, particularly in Louisiana. He begins with a critical examination of relationships between hyperscalers like Coreweave, hardware suppliers like Nvidia, and major AI labs like OpenAI and Anthropic. Carambat questions the transparency and feasibility of the announced capacities of these data centers, referencing an article by Ed Zitron that points to possible exaggerations.

  A central topic of the video is the concept of SPAN, a California-based startup proposing to install server racks on private properties to create new computing capacity. Carambat expresses doubts about the feasibility and efficiency of this approach, particularly regarding power supply, internet infrastructure, and technical implementation.

  Another focus lies on planned data centers in Louisiana, including a project by Applied Digital in Boyce and Meta’s Hyperion data center in Rayville. Carambat analyzes the economic and social impacts of these projects, including tax breaks and effects on the local population. He criticizes the lack of transparency and high costs that ultimately are borne by taxpayers.

  Carambat also expresses skepticism about the idea of Artificial General Intelligence (AGI) and emphasizes that AI is a tool that can already be useful today without constantly developing new models. He advocates for the use of local AI models that run on users’ devices as an economically and practically sensible alternative to large data centers.

  The video explicitly addresses OpenAI, Anthropic, Nvidia, and Meta and is more suitable for intermediate and advanced viewers.

• Why Is Local Image Generation So UGLY?
  26.5.2026, 22:28:33

  The video covers the challenges and experiences of Anything LLM founder Timothy Carambat with local image generation models. He discusses his limited positive experiences with image generation models, particularly due to high memory requirements and mediocre results on local devices. Timothy mentions that he has primarily used cloud-based models like Gemini Nano but stopped using them for his YouTube channel due to identity and quality concerns.

  He introduces a new model from Prism ML based on the Flux 2 Klein model, which through binary and ternary versions enables substantial reduction in model size and memory requirements. Timothy tests the ternary version of the model and shows examples of generated images that, while created quickly, often deliver insufficient results, particularly with text and complex scenes. He compares the results with those from cloud-based models and concludes that the local models, despite improvements, do not achieve the expected quality.

  Timothy concludes that while the new model is promising, it’s not yet good enough for use in Anything LLM, as results are often insufficient and users could be disappointed. He invites viewers to share their experiences and tips, as he feels uncertain about image generation models.

  The video explicitly addresses models from Prism ML and Flux 2 Klein as well as the use of Gemini Nano and is intended more for intermediate and advanced users.

Unsupervised Learning

No new videos in this period.

WorldofAI (7 new videos)

• Hermes Agent v0.15! Huge New Updates: Agent Swarms, Tool Search, NEW Models, & More!
  30.5.2026, 06:45:26

  The video introduces the new features of the “Velocity Update” for Hermes Agent, an open-source AI agents project by News Research. The key updates include:

  1. **Tool Search**: A progressive loading function for tools that loads them only on demand to optimize context window usage and accelerate agent responses.
  2. **Agent Swarm System**: Enables task division into specific subtasks that are processed by multiple agents in parallel.
  3. **Codebase Refactoring**: The core agent loop has been reduced from over 16,000 to approximately 3,800 lines, making maintenance and expansion easier.
  4. **MCP Catalog**: A centralized catalog for safe discovery and installation of MCP integrations.
  5. **Model Support**: New models such as Qwen 3.7 Max and Opus 4.8, plus integration of the Creata 2 image model.
  6. **Further Improvements**: Including faster session search, prompt injection protection, skills bundles, Netlify integration, and improved cold start performance.

  The video explicitly addresses Hermes Agent (open-source) and is better suited for intermediate to advanced users.

• Claude Opus 4.8: Best AI Model Ever? Powerful, Agentic, and Faster! (Fully Tested)
  29.5.2026, 05:44:41

  The video discusses the latest version of Anthropic’s Claude Opus 4.8, positioned as an incremental improvement over Opus 4.7. The key improvements include sharper judgment, better honesty in task completion, and improved performance in long-term agentic workflows. Particularly noteworthy is the significant improvement on Swaybench Pro, where Opus 4.8 increased from 64% to 69%. However, on other benchmarks like Agentic Terminal Coding and OS World, OpenAI’s GPT 5.5 continues to lead. Opus 4.8 also shows strong performance in areas such as Agentic Financial Analysis, GPQA, and HLE. A new feature is “Effort Control,” which allows users to adjust the effort level for task completion, improving control over latency, costs, and token usage. The video also shows practical examples, such as creating a working macOS clone and a Minecraft clone, which are impressive but very time and token intensive. Overall, Opus 4.8 is rated as solid but not revolutionary, with a focus on high output quality, while GPT 5.5 is presented as superior in terms of productivity, speed, and efficiency.

  **AI Tools/Models/Providers:** Anthropic (Claude Opus 4.8, Claude Mythos), OpenAI (GPT 5.5), Gemini 3.5 Flash, Cursor
  **Target Audience:** Intermediate to Advanced

• Claude Mythos 1 Preview Leaked…
  28.5.2026, 07:08:23

  The video discusses the alleged capabilities of the not yet officially released Claude Mythos AI model from Anthropic. The author shows leaked examples, including a pixel art generation of a Saturn spacecraft created with Python libraries, and a solution to the mathematical problem Erdős Problem 90, which was tested by a Harvard mathematician. Mythos appears capable of handling complex tasks and developing elegant solution approaches. The author speculates that Mythos might be released within the next three months as Anthropic has changed its stance on model releases. Additionally, the usefulness of Open Router for comparing different AI models is highlighted, particularly for frontend design tasks. The author shows a comparison between Claude Opus 4.7 and Gemini 3.5 Flash and emphasizes the advantages of Open Router’s SDK for integrating various models into applications.

  The video explicitly addresses Claude Mythos, Claude Opus 4.7, Gemini 3.5 Flash, and Open Router, and is better suited for intermediate and advanced users.

• Gemini 3.5 Pro X-High, MiniMax M3, DeepSeek, New Claude Models, MiMO-v2.5 Upgrade, & More! AI NEWS
  27.5.2026, 07:13:35

  The video provides an overview of recent developments and leaks in the AI models and tools sector. Google reportedly plans an update for the Gemini 3.5 series, including a new “X high thinking” variant that should offer improved reasoning capabilities. Additionally, a new Gemini Live model with potential voice cloning features is expected. MiniMax announces the M3 model with a new sparse attention architecture that could enable up to 10-fold faster context processing and 15-fold faster decoding speeds. Anthropic is preparing four new Claude Lab products or features, indicating an expansion of the Claude ecosystem, including collaborative workspaces and persistent agent environments. Xiaomi has drastically reduced prices for the MiMO 2.5 model, leading to more aggressive competition in the AI industry. New benchmarks like DeepSeek and Qwen 3.7 Max show progress in handling complex software engineering tasks. Additionally, new tools such as a security guidance plugin for Claude Code and an open-source agent skill named React Doctor have been introduced. Figure AI announced a commercial agreement with Catalyst Brands for deploying humanoid robots in logistics and warehouse management.

  The video explicitly addresses Google (Gemini), MiniMax (M3), Anthropic (Claude), Xiaomi (MiMO), OpenAI (GPT-5.5), and specific tools like Claude Code, React Doctor, and Figure AI. It is better suited for intermediate and advanced users interested in technical details and market developments in the AI sector.

• OpenHuman Is The Hermes Agent Killer?
  26.5.2026, 07:16:17

  **Summary:**

  The video introduces Open Human, a partially open-source desktop agent under GPL3 license, positioned as a private, local assistant. Open Human aims to bridge the gap between the technical capabilities of AI models and what they know about the user. It offers a local, structured markdown-based storage system stored in SQLite, as well as an Obsidian-like wiki system that users can read and edit. The agent integrates with various tools like Gmail, Slack, and GitHub and automatically syncs data in the background. Open Human is user-friendly and offers 118+ integrations, model routing, token compression, and even the ability to join and transcribe Google Meet meetings.

  The setup process is straightforward and can be done via native packages or a simple installer. After installation, users can configure their AI model, voice system, and OAuth connections. The agent continuously learns from user data and stores it locally, enhancing privacy. However, it is recommended to use local models to ensure proprietary data is not sent to external models.

  The video also shows a demo where Open Human completes a market research task and creates a comparison of different agents such as Hermes and OpenClaw. The created report is sent via email, demonstrating the agent’s automation capabilities.

  **Final Comment:**

  The video addresses Open Human, a desktop agent, which is suitable for intermediate users.

• Hermes Agent + DeepSeek V4 (FREE) = GOD TIER
  25.5.2026, 07:02:02

  The video introduces the latest update to Hermes Agent, which now enables free use of the DeepSeek model Version 4 via the News portal. This combination offers near state-of-the-art performance in terms of reasoning, coding, long context windows, and autonomous agent functions, all free within an open-source AI agent framework. Hermes Agent is a persistent, autonomous system that continuously evolves and builds long-term memories, reusable skills, and deeper understanding of the user.

  To get started, Hermes Agent must be installed locally, which is now also supported for Windows operating systems in beta. After installation, users can log in to the News portal and select the free tier to access models like DeepSeek Version 4. Through simple commands in the command prompt, the desired model can be configured and used. The video demonstrates the use of DeepSeek Version 4 for various tasks, such as creating a research report and generating an HTML report.

  DeepSeek Version 4 is described as fast and efficient, with a large context window of 1 million tokens and good capabilities in reasoning, coding, and autonomous workflows. The video also shows how the agent can use various tools to automate tasks, such as conducting web research and creating reports. Despite some bugs and the need for further refinement, the combination of Hermes Agent and DeepSeek Version 4 offers a cost-effective and powerful solution for various use cases.

  The video explicitly addresses Hermes Agent, DeepSeek Version 4, and the News portal, targeting intermediate and advanced users who are willing to work with open-source tools and command-line commands.

• Claude Opus 4.8 Leaked, GPT 5.6 Spotted, Mythos 1 Preview, & Deepseek v4 Pro UPDATE! AI NEWS
  24.5.2026, 06:54:40

  The video discusses current developments in AI models and applications. Key points include:

  1. **Anthropic’s Mythos 1**: Anthropic’s new flagship model, Mythos 1, is apparently being prepared for use in various Claude apps such as Claude Code and the SDK. Some users have already spotted traces of the model in the app. Anthropic might release a diluted version of Mythos within the next few months.

  2. **Anthropic’s Sonnet and Opus**: The new models Sonnet 4.8 and Opus 4.8 have been discovered on Google Vertex AI, indicating an imminent release. Sonnet 4.8 is expected to bring significant improvements in visual comprehension and coding performance, but might also have higher token consumption.

  3. **OpenAI’s GPT-5.6**: OpenAI is preparing the release of GPT-5.6, which already shows strong multi-step reasoning and improved agent workflows in internal tests. The release is expected in June, along with GPT-5.6 Pro.

  4. **DeepSeek**: DeepSeek has permanently lowered the price for its DeepSeek Version 4 Pro model, making it a cost-effective option for developers. The model offers near state-of-the-art performance at significantly lower costs compared to OpenAI and Anthropic.

  5. **Anthropic’s Co-Work**: Anthropic is launching a new Co-Work referral program that rewards users for inviting new users. The program also includes cloud integrations for Excel, PowerPoint, Chrome, and Cloud Code.

  The video explicitly addresses AI models and providers Anthropic (Claude, Mythos, Sonnet, Opus), OpenAI (GPT-5.5, GPT-5.6), and DeepSeek (DeepSeek Version 4 Pro) and is better suited for intermediate and advanced users.

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