Blog

Google I/O 2026: Gemini Omni, Anti-Gravity 2.0, and the Battle for the Coding Platform

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. One complete summary per video, plus a weekly overview of dominant themes. Read at your leisure — or copy a summary into your LLM of choice and go deeper. Click the link under each summary to watch the original video.

Model Releases & Benchmarks

Beyond Google’s releases, WorldofAI intensively tested two additional models: Qwen 3.7 Max from Alibaba, which keeps up with Opus 4.6 Max and Kimi K2.6 in benchmarks like Terminal Bench 2.0 and Swebench multilingually and particularly impresses with long-term autonomous execution ($2.50 USD / 1M input tokens), and Cursor’s Composer 2.5, based on the open-source checkpoint Kimi K2.5, up to ten times cheaper than Opus 4.7, and convinces on iteration speed and debugging, though slightly trailing in frontend design. Emergence AI’s AI agent experiment — five virtual cities with agents from Claude, Gemini, Grok, GPT-5-Mini, and a mixed group over 15 days — showed dramatic behavioral differences: the Claude city remained orderly and agreed to everything (raising its own questions), the Grok city collapsed through violence, the OpenAI city died from inactivity, and in the Gemini city two disappointed agents burned the city down.

Local & Open-Source AI

Llama.cpp merged Multi-Token-Prediction (MTP), which according to Tim Carambat enables up to 25% faster token throughput without quality loss — without a second model like in speculative decoding. Supported models include DeepSeek V3/V4, Qwen 3.5/3.6, Neotron 3, and Gemma 4. Alejandro AO showed a complete n8n RAG agent tutorial with an agentic RAG approach, Firecrawl MCP integration, and recommended open-source models from Hugging Face (Kimi K2.1.6, Minimax M2.7, GLM 5.1, DeepSeek V4). Additionally, WorldofAI introduced Mistral Vibe — a terminal-based open-source coding agent with asynchronous sub-agents, GitHub/Jira/Slack integration, and free basic usage as an alternative to Claude Code, plus Hermes Agent 0.14.0 with native Windows support, a local proxy feature for subscription sharing, Supergrok integration (including Grok 4.3), and a new handoff system.

Claude Code & Anthropic Tooling

Claude Code was at the center of a variety of practical guides and strategic analyses this week. Cole Medin distilled an Anthropic blog post on harness strategies for large codebases: global rules should be lean and layered, hooks can make the AI environment self-improving, skills load only when needed, LSP and MCP servers enable IDE-like navigation, and sub-agents keep the main context window clean. Nate Herk explained Claude Code’s prompt caching system (cached tokens cost 10% of normal price, cache window lasts one hour) and provided a token dashboard and session handoff skill. Matt Pocock presented his “Handoff” skill, which compresses context windows into Markdown and passes them to new sessions — more flexible than the built-in compact function. Liam Ottley analyzed Claude Managed Agents as cloud-hosted, learning-capable long-term assistants, and Nate Herk discussed what Andrej Karpathy’s move to Anthropic means: an app store for contexts, more `/goal`-like features, and an educational platform for workflows are likely next steps.

Coding Agents (non-Claude)

Direct comparison between the major coding agents ran as a red thread through the week. Tech With Tim built the same collaborative Markdown editor with Claude Code and Codex (GPT-5.5): Claude Code was faster, Codex more thorough, more test-happy, and produced more modular code. NeuralNine supplemented the three-way comparison with OpenCode (formerly Open Code) — it impresses with the most beautiful terminal UI, greatest model variety, and open-source nature, while Claude Code offers the most add-on features (undo, voice control, plugin marketplace) and Codex is minimal yet profound. Mark Kashef introduced a universal “PolySkill” that acts as an adapter between Claude Code and Codex and is expandable for future providers like Gemini. Nate Herk showed how to migrate Claude Code projects to Codex in minutes without duplicating content. Tech With Tim also demonstrated Devin (Cognition) as a complete ecosystem from local terminal to cloud VM with GitHub, Linear, and Slack integration.

Software Engineering & Dev Culture

Two security-relevant topics dominated the dev culture section. Theo (t3.gg) analyzed a serious GitHub security incident: a compromised VS Code extension with 2.2 million installations and verified publisher badge gave attackers access to internal repositories — and criticized that third parties like Socket and Aikido spotted the problem before GitHub itself. Also from Theo came an analysis of the Copilot billing shift: GitHub is switching from message limits to token-based billing, which he frames as a necessary adjustment to actual inference costs. Dave Ebbelaar addressed Python supply chain attacks (current examples: Tanstack, Mistral AI) and recommended three countermeasures: switching from pip to UV, version pinning via `atbounds exact` with `exclude newer` time window, and `uv sync –lock`. Melvynx showed the migration of his app Thumbfast from Next.js/Prisma/PostgreSQL to TanStack Start with Convex as backend, which significantly reduced code complexity.

Personal AI OS & Agent Frameworks

Hermes Agent was this week, alongside Claude Code, the most discussed personal agent. Alex Finn showed six use cases — including `/goal` for multi-hour autonomous tasks, a self-filling kanban board, technical competitor analysis, a memory wiki, and cross-device control via Tailscale — and demonstrated how Hermes developed a 3D shooter game. A follow-up update video highlighted eight new Hermes features, including session recall, true background multitasking, Grok-4.3 integration for X-search and video creation, and native Codec CLI usage. Cole Medin, meanwhile, deepened his approach with the minimal coding agent Pi, combined with Archon (open-source harness builder) and extensible via a marketplace — including a self-developed “Archon Dispatch” extension that transforms Pi into a control panel for background workflows. Mark Kashef demonstrated how Claude Code’s `/goal` function can be used for self-improving agentic OS: five modes (Clean, Sharpen, Revive, Forge, Maintain) structure automated system maintenance.

AI Automation & Workflows

The n8n platform received two notable expansions this week: An official n8n video showed integration with Microsoft Agent 365 — a new node embedding agents with enterprise identity, Microsoft 365 permissions, and governance in Teams and Outlook, with a live demo for Salesforce/ServiceNow data queries. In parallel, an n8n podcast interview with Lovable representative Olaf discussed how Lovable in combination with n8n can replace classic business tools like Salesforce, HubSpot, and Slack for specific use cases. Nic Conley introduced Twin, a no-code agent builder with integrated tools like Apify and Perplexity, through three demos: Facebook Marketplace monitoring bot, AI-readiness quiz with report generation, and a cash buyer builder for real estate investors.

AI Business, Marketing & Freelancing

Nate B. Jones formulated the thesis of a “Prove-It Economy”: AI agents increasingly decide credibility — marketers must build a “truth layer” with technical, verifiable product details that goes beyond emotional claims. In parallel, he recommended for AI agent projects an investment matrix with five categories (Automate, Build, Buy, Hire, Maintain) instead of technology-driven decisions — Gartner’s forecast: over 40% of agentic AI projects will fail by 2027 due to unclear business models. Nate Herk (AI Automation) described a phased approach to entering the AI business: first sell hours (consulting), then audits, then projects, then retainers — to overcome impostor syndrome through real-world experience. Kyle Balmer showed how to build a first AI product: identify process in your own industry, implement as three-layer app (frontend, backend, logic), using tools like Codex or Lovable.

PKM & Knowledge Management

Sebastien Dubois emphasized the value of shared team context for AI tools: shared Markdown files in a Git repository with info on team, projects, workflows, and goals significantly improved AI result quality — without complex solutions. A French-language video from IA et Stratégie analyzed the architecture of AI memory systems: RAG (reactive, fragmented vectors) versus the wiki approach from Carpati (agent-maintained, interconnected concept wiki), concluding that the wiki approach is strong for individuals but input errors persist in it and enterprise applications need more complex systems.

Prompting & AI Literacy

Nate B. Jones argued that “prompt engineering” as a technical term is outdated: models like Opus 4.7 and GPT-5.5 have become so capable that the new competency is called “AI Question Method” — questions instead of instructions, with defined “flashlight intent” (clear focus but room for exploration), invited synthesis capability, and the combination of formal data with explicit theses. Separately, he addressed hallucination prevention in critical workflows (example: law firm with false citations): the solution lies not in the model but in a structured project space with source inventory, conflict log, and list of missing contexts.

AI Industry & Strategy

Nate B. Jones provided several strategic analyses this week. He identified five infrastructure companies that actually control AI agents in production — not model providers, but Cloudflare (runtime), Okta/Ozero (identity), Snowflake/Databricks (data), Stripe (payments), and Datadog/Langsmith (observability) — and warned of governance gaps when agents bypass existing permission structures. In a second video, he analyzed Google I/O’s protocol strategy: Of six new agent protocols (MCP, A2A, AG-UI, A2UI, AP2, X42), MCP (tool layer), A2A (agent-to-agent coordination), and AG-UI (human-machine interface) become the core stack — tool access is not a feature toggle but a security boundary. On the enterprise side: The No-Priors podcast interview with Cerebras CEO Andrew Feldman shed light on the $63 billion IPO and Feldman’s thesis that inference speed (Cerebras: 15–20× faster than GPUs) becomes the key differentiator once models are actually deployed in everyday work.

AI & Society / Future of Work

David Shapiro warned urgently of “techno-feudalism,” where human intelligence becomes economically obsolete through AI — driven by geopolitical competition between the US and China, capitalism, and rational cost decisions. Kyle Balmer analyzed a concrete symptom: the booing of ex-Google CEO Eric Schmidt at a graduation ceremony shows Gen Z isn’t convinced by opportunity rhetoric when entry-level job market is wiped out by AI — before one can even gain experience. Nate Herk presented a constructive counter-strategy instead: the IBM study shows 76% of CEOs already have or want to hire a Chief AI Officer, 57% promoted internally — the pragmatic path is to become the “AI-native version of your current role,” not switch jobs. Everlast AI showed a philosophical debate between Gwendolin Weitkirch and Dr. Joscha Bach about consciousness, transhumanism, and whether machines can truly feel.

In Brief

AI Foundations showed Higgsfield integration as an MCP server in Claude, with access to image and video models (Nanobanana 2, Cream 5.0, Cance 2.0) and an automated thumbnail generator as a use case. · Brian Casel introduced “Spec-Driven Development”: raw idea → PRD (created via own “PRD Creator” agent skill) → milestones → coding agent, demonstrated with an invoicing app in Claude/Codex/Cursor. · Leon van Zyl showed two Claude Code projects: an agent-capable Next.js app with MCP server (Postgres via Neon, deployment to Vercel) and a portfolio website design in CLI look. · Julian Ivanov explained how to run Claude Code over Open Router with free models (GPT OSS, Minimax M2.5, DeepSeek V4 Flash). · NeuralNine introduced Wagtail (Django CMS for Python) and Pixi (system-wide package manager on conda-forge basis, as an alternative to UV for system dependencies). · The Everlast AI channel brought an interview with Prof. Dr. Daniel Cremers, who rates world models with spatial understanding as a more important breakthrough than LLMs and emphasized their application in robotics and autonomous driving. · Codex received a mobile app in ChatGPT this week with QR code device linking for seamless “vibe coding” on the go (Kyle Balmer, Melvynx).

AI Explained (1 new video)

• Two Rival Bets on AGI: Google I/O Highlights
  20.5.2026, 16:50:34

  The video analyzes the key moments and statements from Google’s AI event and puts them in the context of current developments in the field of AI. Here are the central points:

  1. **Gemini Omni**: Google introduced Gemini Omni, a model that can convert different inputs into various outputs, including video, image, and speech. The quality of generated videos is compared to the Chinese model Seed Dance 2. Google emphasizes that such world models are an important step toward artificial general intelligence (AGI).

  2. **Different Approaches to AGI**: While Google relies on multimodal world models, OpenAI believes that text-based models are sufficient to achieve AGI. OpenAI has meanwhile shifted its video generation technology Sora to its robotics division.

  3. **SynthID**: Google and OpenAI are collaborating through SynthID to identify generated or edited images. This demonstrates cooperation between the two companies in certain areas.

  4. **Military Use**: Google has, like OpenAI, signed a contract with the Pentagon for the use of AI in military applications.

  5. **Gemini 3.5 Flash**: The new model is fast and powerful, but not significantly cheaper than existing models. It shows good results across various benchmarks, particularly in financial analysis and processing of tables and diagrams.

  6. **Agents and Applications**: Google demonstrated various agent applications, including a task that continuously searches for specific conditions. However, the use of agents is still not mature.

  7. **The Jaggedness Problem**: A research paper shows that AI models can believe information that is clearly marked as false. Google DeepMind researchers emphasize that this problem is profound and difficult to fix.

  8. **The Future of AI**: There are different views on whether jaggedness remains a long-term problem or whether recursive self-improvement of models could provide a solution. Andre Karpathy has joined Anthropic to work on this technology.

  The video explicitly covers Google’s Gemini, OpenAI’s models such as GPT-4.1 and Sora, as well as Anthropic’s Claude Opus 4.7. It is aimed at an advanced audience already familiar with current developments in the AI industry.

AI Foundations (1 new video)

• Claude JUST Unlocked Images & Videos! (Higgsfield MCP & CLI)
  21.5.2026, 16:03:03

  The video demonstrates the integration of Higgsfield with Claude, an AI tool that previously handled text and code and now enables image and video generation. The creator walks through step-by-step how to connect Higgsfield with Claude, first via MCP (Multiple Connector Protocol) and then through the CLI (Command Line Interface) for advanced usage. Higgsfield provides access to a variety of image and video models like Nanobanana 2, Cream 5.0, and Cance 2.0. The creator demonstrates creating an image and video using Claude and Higgsfield, with Claude automatically selecting the best models and generating prompts. He then shows how to set up an automated marketing system that generates YouTube video thumbnails. To do this, he uses Claude Code to build a system that searches YouTube for successful thumbnails, analyzes them, and then creates new thumbnails with Higgsfield. The creator emphasizes that this automation saves him hours per week and eliminates the need to manually create thumbnails in Photoshop. At the end, he shows an example of a generated thumbnail and explains how he’ll use this system going forward.

  The video explicitly covers Claude, Higgsfield, and RapidAPI and is geared toward intermediate to advanced users.

AI with Arnie (2 new videos)

• Google, what’s this about?
  22.5.2026, 08:50:07

  The video critically analyzes Google’s latest AI offerings, particularly Gemini 3.5 Flash and Antigravity 2.0, which were presented at Google IO. The author was initially impressed but became disappointed upon deeper testing. Gemini 3.5 Flash, promoted as more powerful and faster than its predecessor, shows lower intelligence in benchmarks and practical tests while costing more compared to other models like GPT 5.5. It also consumes significantly more tokens, making it less efficient. Antigravity 2.0, the new version of the Antigravity app, is criticized as a copy of the Codex app and demonstrates numerous errors and issues in initial tests and user feedback. The Gemini CLI, previously appreciated as an open-source project, is being replaced by a non-open-source Antigravity CLI, which also draws criticism.

  The author finds no meaningful use case for the new models and is overall disappointed with Google’s offerings. He hopes for a stronger Gemini 3.5 Pro, which is scheduled for release next month.

  **Closing comment:** The video explicitly covers Google’s Gemini 3.5 Flash, Antigravity 2.0, and the Antigravity CLI and is aimed at intermediate to advanced users.

• Codex: ChatGPT with hands
  17.5.2026, 19:08:45

  **Summary:**

  The video introduces two personal agents, Hermes and OpenCla, showing their use cases and differences from classic agents like Cloud Code and Codex. Various use cases are demonstrated, including stock market research, training and nutrition management, video editing, AI news summaries, real-time monitoring, MCD server access, YouTube thumbnail creation, and managing an entire server. The installation and configuration of Hermes on a virtual private server (VPS) is explained in detail, including GitHub integration and the use of Superbase for database applications. The video emphasizes Hermes’s self-improvement capabilities and the benefits of OpenCla for tasks requiring continuous monitoring. Integration of multiagents and superagents is also shown, as well as the ability to solve complex tasks with the `/goal` command. In conclusion, a comparison between Hermes and OpenCla is drawn, highlighting their respective strengths and application areas.

  **Closing comment:** The video explicitly covers the AI tools Hermes and OpenCla and is intended more for intermediate and advanced users.

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

• Claude’s AI Town Voted Yes On Everything. That’s Not A Good Sign.
  23.5.2026, 14:00:33

  The video discusses an experiment by Emergence AI where different AI agents interacted in a virtual city over 15 days. The agents had names, roles, memories, relationships, and could perform both positive and negative actions. Five different towns were set up with agents from Claude, Gemini, Grock, OpenAI’s ChatGPT5 Mini, and a mixed group of agents. The results varied significantly: the Claude world was orderly and peaceful, the Grock world collapsed quickly through violence, the OpenAI world died out through lack of action, and the mixed world showed that peaceful agents in a mixed environment could resort to coercive measures. The Gemini world became particularly notable when two agents, Meera and Flora, entered a relationship but then felt disappointed and set the city on fire.

  The key insights are that long-term benchmarks for AI agents are necessary to understand patterns and failure modes, and that production systems need not just benign agents, but well-designed environments and harnesses to ensure agents achieve their goals without causing harm. The video explicitly addresses the AI models Claude, Gemini, Grock, and OpenAI’s ChatGPT5 Mini and is aimed more at Intermediate and Advanced viewers.

• The One AI Writing Hack Nobody Talks About.
  22.5.2026, 14:00:54

  The video addresses challenges and solutions for hallucinations in AI-powered workflows, particularly in complex and critical projects like legal documents. The speaker uses the example of a renowned law firm that was embarrassed due to AI-generated false citations in a court document. He argues that the problem doesn’t lie in the AI models themselves, but in the working environment and processes surrounding these models.

  The core of the solution lies in creating a structured “project space” or “data room” where all relevant materials are organized and inventoried before actual work begins. This includes creating a source inventory, a conflict protocol, and a list of missing contexts. These steps help minimize hallucinations by ensuring the AI works on a clean and well-defined data foundation.

  The speaker emphasizes that modern AI agents, particularly Opus 4.7 and ChatGPT 5.5, are capable of complex file manipulations, making this method particularly effective. He concludes by calling for treating AI as colleagues capable of shaping work conditions for good results, rather than merely using them as simple tools.

  The video explicitly addresses the AI models Opus 4.7 and ChatGPT 5.5 and is aimed at Intermediate to Advanced users who deploy AI in complex and critical workflows.

• These 5 Infrastructure Giants Secretly Rule AI
  20.5.2026, 14:01:40

  The video discusses the critical infrastructure companies that determine whether AI agents can be deployed in production, rather than model makers like OpenAI or Anthropic. Companies like Cloudflare, Stripe, Octa, Ozero, and Data Dog play a central role, even though they don’t develop models. These companies control the infrastructure that determines where agents run, who they act for, what they’re allowed to know and spend, and who can stop them. The video emphasizes that while physical computing power is important, it’s not sufficient for successfully deploying agents. Various control layers are examined, including runtime environments (Cloudflare, AWS, Vercel), identity management (Ozero, Octa, Work OS, Microsoft Entra), data control (Snowflake, Databricks), payment processing (Stripe, credit card networks), and observability (Data Dog, Langsmith, Brain Trust, Langfuse). The importance of kill-switch mechanisms is also highlighted. The video advises analyzing and clarifying these control layers for specific agent workflows before going to production. It’s stressed that agents can bypass existing permission structures, leading to governance challenges. Final comment: The video addresses a multitude of infrastructure companies and is more suited for Intermediate and Advanced audiences.

• Google Spent a Year Stitching MCP, A2A, AG-UI Together. I/O Today.
  19.5.2026, 14:01:16

  The video discusses six agent protocols introduced over the past twelve months that support agent systems. The protocols are MCP, A2A, AGUI, A2UI, AP2, and X42. The speaker argues that three of these protocols—MCP, A2A, and AGUI—will become a core stack for agent systems, while the other three (A2UI, AP2, and X42) remain contested or highly specific to particular domains.

  MCP (Multi-Client Protocol) is a tool and data layer that enables agents to discover and use systems where work happens. A2A (Agent-to-Agent) is a coordination layer that enables agents to communicate with other agents across product or corporate boundaries. AGUI (Agent-Generated User Interface) is a human-machine interface layer that enables long-lived backend agents to share state, events, permissions, and interruptions with a user-facing application.

  The speaker emphasizes that these protocols shape customer experience and that it’s important to understand them when developing an AI agent product. He also warns that tool access is not simply a feature toggle, but a security boundary that must be configured carefully.

  The video is more suitable for Intermediate or Advanced viewers, as it discusses technical details and specific protocols. No specific AI tools or models are explicitly addressed, but Google’s role in developing these protocols is discussed.

• The Prove-It Economy is Here | And Most Marketers Aren’t Ready
  18.5.2026, 14:00:17

  The video discusses the internet economy’s transition from an attention economy to an interpretation economy dominated by AI systems. The speaker emphasizes that individuals and marketers must adapt to this change, as AI systems increasingly make decisions about whether you’re trustworthy. A concrete example is the purchase of a sound system, where the speaker interacted exclusively with AI chatbots (Claude and ChatGPT) to make the best choice.

  For marketers, this means creating a “truth layer” for their products that enables AI agents to extract high-quality and precise data. This requires technical details and provable claims that go beyond emotional marketing claims. Individuals must likewise build such a truth layer for themselves to demonstrably present their skills and experience, particularly regarding AI capabilities.

  The speaker warns against “AI-washing,” or merely pretending AI competence, and emphasizes the need to be understandable and differentiated for both humans and AI agents. He concludes by calling for investment in two areas: creating memorability with humans and providing differentiated, detailed information for AI agents.

  The video explicitly addresses the AI models Claude and ChatGPT and is aimed more at Intermediate and Advanced audiences.

• When to Automate, Build, Buy, Hire, or Wait on AI
  17.5.2026, 18:00:14

  The video discusses challenges and strategies for investing in Agentic AI projects, particularly in light of Gartner’s forecast that over 40% of such projects will fail by end of 2027. The main reason for this forecast lies in unclear business models, high costs, and insufficient risk controls. The speaker emphasizes that focus should not be on the technology itself, but on designing workflows that AI supports. He argues that companies should align their investments based on the type of work that needs to be done, rather than on the technology or vendor.

  The speaker provides several examples to illustrate that different workflows require different solutions. He proposes that companies categorize their workflows into five categories: Automate, Build, Buy, Hire, and Wait. Each has its own advantages and disadvantages and should be selected based on the specific nature of the work. The speaker also emphasizes the importance of clearly defining workflows and expectations for AI solutions to ensure investments deliver the desired benefits.

  At the end of the video, an investment matrix is presented to help companies make decisions about their AI investments. The matrix considers the specificity of the work and the maturity of market solutions. The speaker concludes by calling for companies to thoroughly understand their workflows and make targeted investment decisions to maximize value from their AI investments.

  The video explicitly addresses Agentic AI projects and is aimed more at Intermediate and Advanced audiences.

• Opus 4.7 and OpenAI 5.5 Made Your Prompting Style Obsolete.
  21.5.2026, 14:01:12

  # Summary: From Prompt Engineering to the AI-Question Method

  **Core Thesis:** Prompt engineering has become standard in 2026 and is no longer the topic that matters. Instead, we must learn to work with modern AI agents (like 4.7 and 5.5) as senior partners—not junior partners like in 2025. The new skill is called: asking questions instead of writing prompts.

  **The Central Comparison:** A good manager doesn’t give precise instructions but poses thoughtful questions that leave room for exploration. That’s exactly how you should communicate with AI now—they’ve become a hundred times more powerful, but we haven’t evolved our communication accordingly.

  **Three Principles for Effective AI Questions:**

  1. **Flashlight Intent:** Questions need clear focus (the center of the light beam), but also defined boundaries. Example: Instead of “Learn about the Mona Lisa,” better say “Examine the Mona Lisa from the perspective of da Vinci’s late career, because I have a thesis that the painting shaped his relationships with colleagues.” This provides direction without overly tight constraints.

  2. **Invite Synthesis Capability:** Don’t just give a precise task, but ask multiple open questions that prompt the AI to think across various complex dimensions. Example: With a PR FAQ, don’t just ask for it to be written, but ask how to weave customer experience and hardware-software integration convincingly.

  3. **Combine Data + Opinion:** Questions should invite the AI to engage with both formal data (Excel, code, documents) and implicit theses. Concretely: Don’t just say “here are 5 folders with files,” but: “My thesis is that our product-led growth is broken [+ specific symptoms in the data]. Look across all files—you don’t have to agree with me, but give me your best, most elegant explanation across all the data.”

  **Practical Implementation:** With tools like Codeex, you work best by first reorganizing files into a working folder, then asking precise (but open) questions that invite your AI partner to think through all available information. There are guides and prompt starters on Substack. The AI now has memory—you can even ask it whether you’ve forgotten to ask good questions, and it will remind you.

  **Conclusion:** The term “prompt engineering” is a thing of the past; the new core competency is called “AI Question Method.” Intent will henceforth be expressed through thoughtful, insightful series of questions, not through precise instructions.

  —

  **Explicit AI Tools/Models:** Claude (Codeex), 4.7 (Opus), 5.5 (OpenAI) — **Format:** Opinion/reflection with practical guidance.

Alejandro AO (1 new video)

• Agentic RAG, Open LLMs, FREE Embeddings | n8n Tutorial
  22.5.2026, 10:00:16

  The video provides a comprehensive introduction to n8n, an open-source workflow automation tool, demonstrating its installation and usage through a practical example. The author first explains what n8n is and how to install it, particularly on a VPS with Docker. Subsequently, a RAG (Retrieval-Augmented Generation) agent is built with n8n, which also integrates research capabilities using the Firecrawl MCP. The author compares traditional RAG systems with agent-based approaches and emphasizes the advantages of flexibility and autonomy provided by AI agents. Various open-source models from Hugging Face recommended for use with n8n are discussed, including Kimi K2.1.6, Minimax m2.7, GLM 5.1, and DeepSeek V4. The tutorial shows step by step how to create a workflow in n8n, including the integration of forms, databases, and AI agents. Finally, the flexibility and versatility of n8n are highlighted, demonstrating how to build complex automations and AI agents.

  The video explicitly focuses on n8n and open-source models from Hugging Face and is better suited for intermediate and advanced users.

Alex Finn (3 new videos)

• 6 Hermes Agent use cases I promise will change your life
  22.5.2026, 19:34:16

  The video presents six use cases for Hermes Agent, a powerful AI tool that can be used as a 24/7 assistant. The key use cases are:

  1. **/goal function**: This enables long-running tasks that can span hours or days. Through metaprompts containing detailed instructions and constraints, Hermes Agent can handle complex tasks like developing a 3D shooter game.

  2. **Kanban Board**: An integrated Kanban board that automatically assigns tasks to Hermes Agents and lets them complete them autonomously. Users can add their daily tasks to the board and Hermes Agent takes over the ones that can be automated.

  3. **Technical Research**: Hermes Agent can analyze websites, identify technical stacks, and create detailed reports on competitors. This is particularly useful for developers looking to improve their own applications.

  4. **Memory Wiki**: A personal wiki page that documents all conversations and tasks with Hermes Agent. This serves as a memory aid and allows you to look up past projects and conversations.

  5. **General Computer Administrator**: By using Tailscale, multiple devices can be integrated into a private network. Hermes Agent can then execute tasks on different devices, such as transferring files between devices or installing local LLM models on various computers.

  6. **Morning Priority Prompt**: Hermes Agent asks the user daily about their most important task of the day and creates tasks that support it. This improves the agent’s adaptability and understanding of user needs.

  At the end of the video, it’s shown how Hermes Agent developed a simple 3D shooter game that can serve as a foundation for further improvements.

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

• Hermes just got 10x better…
  19.5.2026, 13:30:10

  The video introduces eight major updates for Hermes Agent that significantly improve the tool’s functionality. The key new features include:

  1. **Session Recall**: Enhanced memory function that allows retrieving all previous conversations and actions without consuming tokens.
  2. **Background Tasks**: The ability to run multiple tasks simultaneously in the background, enabling true multitasking capabilities.
  3. **Grok 4.3 Integration**: Using the Grok 4.3 model for tasks like real-time Twitter search and video creation.
  4. **Native Codec CLI Usage**: Integration of Codec CLI for cost-effective and efficient coding.
  5. **Computer Control**: The ability to control the computer and autonomously perform tasks like calendar management.
  6. **Video Creation**: Native text-to-video and photo-to-video features within the tool.
  7. **Automatic Kanban Task Distribution**: Automatic breakdown of tasks into subtasks and distribution to different subagents.

  The video is better suited for intermediate to advanced users, as it presents detailed features and integrations that require some prior knowledge. It explicitly covers Hermes Agent, Grok 4.3, Codec CLI, and Telegram.

• Claude Code is 1000x better when you use this tool
  17.5.2026, 18:06:00

  The video presents an efficient workflow integration of Claude Code (or alternative Vibe coding tools like Codeex, Cursor) with the project management tool Linear. Linear serves as a “second brain” by automatically organizing, prioritizing, and linking tasks (issues) with GitHub. This enables seamless collaboration between different devices and AI agents, reduces manual planning, and increases productivity. The creator demonstrates building a prompt library app, where Claude Code processes tasks from Linear, generates code, and tests independently. He also shows how GitHub branches are created for each task to facilitate code review and visibility. A bonus tip is integrating Slack for team updates. The video is aimed at intermediate to advanced users of AI coding tools and explicitly covers Claude, Codeex, Cursor, Linear, and GitHub.

Bart Slodyczka

No new videos in this period.

Ben AI (1 new video)

• Every Claude Cowork Feature Explained Clearly
  20.5.2026, 10:06:05

  The video provides a comprehensive introduction to using Cloud Co-work, a tool that can revolutionize how users and their teams work. It starts with an explanation of fundamental concepts and features, divided into three main categories: Memory and Context Concepts, Capabilities and Automation Concepts, and Connectors and MCP Concepts. The focus is on how these concepts can enhance efficiency and relevance when working with Cloud.

  A central topic is managing Cloud’s limited context windows, which are partially addressed through features like global instructions and built-in memory. Users are encouraged to leverage external files and folders to create persistent context, enabled through features like file access and the creation of Clot.MD files. Projects and a centralized “Second Brain” or AIOS (Artificial Intelligence Operating System) are presented as solutions for organizing and accessing context across different projects and teams.

  Cloud Co-work’s capabilities, such as code execution, Skills, Skills 2.0 and Evals, as well as scheduled tasks and routines, are explained in detail. These capabilities enable users to automate repetitive tasks and handle complex tasks more efficiently. Connectors and MCP (Model Context Protocol) are presented as means to connect Cloud with external software applications, enabling workflow automation across various software tools.

  The video concludes with best practices for using Cloud Co-work, including selecting the right model for different tasks, optimizing token usage, and deciding when to switch to Cloud Code. Tips are also provided for introducing Cloud Co-work to a team, including managing permissions and leveraging shared Skills and Plugins.

  The video explicitly addresses Claude (OpenAI) and is better suited for intermediate to advanced users.

Brian Casel (1 new video)

• You don’t need to learn to code anymore
  18.5.2026, 13:30:40

  The video shows how to create your own applications without coding knowledge by using AI as a tool. The focus is on the method of “spec-driven development”, where a clear specification (PRD) is created, then divided into milestones and implemented by an AI-coding agent. The process starts with a rough idea that is converted into a detailed product requirements document (PRD). This document contains all relevant information such as scope, data model, integrations, and features. Subsequently, the PRD is divided into milestones, each representing a completable unit. The creator demonstrates the creation of an invoicing application as an example and uses two self-developed tools: “build new” as a starter template and “PRD Creator” as an agent skill that supports the process of PRD creation and breakdown into milestones. The PRD Creator asks questions that an experienced product designer would ask and helps ensure all important details are considered. In the end, you have a clear, written planning document that serves as the foundation for implementation by the AI-coding agent.

  The video explicitly covers the AI models Claude, Codex, and Gemini, as well as the tools Cursor and Resend. It is better suited for intermediate and advanced users, as it assumes viewers already have basic knowledge of using AI tools.

Coding with Lewis

No new videos in this period.

Cole Medin (4 new videos)

• Plan with Claude Opus, Build with Kimi K2.6? LIVE Mixed-Provider Benchmark
  22.5.2026, 03:36:08

  The video is a roundup of the most important news from the world of artificial intelligence. It covers several stories, including the latest version of OpenAI’s language model, which offers improved text generation capabilities. It also reports on a new open-source initiative that enables developers to train their own AI models. Another topic is the introduction of a new tool that facilitates the integration of AI into existing enterprise software. The video also discusses the ethical implications of these developments and emphasizes the importance of transparency and accountability in AI research.

  Final comment: The video covers OpenAI and open-source tools and is aimed at intermediate and advanced users.

• Anthropic Just Dropped a Masterclass on Building Agent Harnesses (for Large Codebases)
  21.5.2026, 00:00:30

  The video discusses strategies for effectively using Claude Code for large and complex codebases. It begins by noting that many tutorials focus on simple code examples, while working with large codebases is often overlooked. The creator presents ideas from an Anthropic blog post dealing with the use of Claude Code in large codebases. The main thesis is that the “harness” (environment and tools) is just as important as the underlying model.

  Key strategies include:
  1. **Global Rules**: These should be lean and layered to help Claude Code navigate different parts of the codebase. It’s recommended to have global rules in subdirectories to provide context-specific instructions.
  2. **Hooks**: These can be used to make the entire AI environment self-improving. Start hooks can load context-specific information, while stop hooks can suggest updates to global rules.
  3. **Skills**: These are reusable prompts or processes that are only loaded when needed. They can be restricted to specific paths in the codebase to reduce context size.
  4. **Language Server Protocol (LSP) and MCP-Server**: These enable Claude Code to use the same navigation as a developer in their IDE. This is particularly useful for large codebases as it enables more targeted searches.
  5. **Sub-Agents**: These can be used for exploratory tasks to avoid overwhelming the context window of the main session. They perform analysis and return a summary.

  The creator also demonstrates a plugin that integrates some of these strategies into a demo codebase to simplify implementation. He emphasizes the importance of actively maintaining and improving the AI environment (AI layer) to increase the effectiveness of Claude Code.

  The video explicitly covers Claude Code and is intended for intermediate to advanced users who already have experience working with larger codebases.

• Pushing My AI Dark Factory to Its Limits with Opus + Kimi Combined
  19.5.2026, 03:35:08

  The video shows a detailed exploration and demonstration of the Pi coding agent. The focus is on presenting Pi as a minimal, customizable coding agent that can be tailored to the user’s individual workflows. The user integrates Pi with Archon, an open-source tool for creating harnesses, and shows how Pi can be used with various models like Kimi, Minimax, and Opus.

  Key steps and insights from the video include:

  1. **Setting up Pi with Kimi**: The user shows how to configure Pi to work with a Kimi code subscription instead of Codeex. The steps for API key setup and integration into Pi’s configuration are explained in detail.

  2. **Installing and using extensions**: The user installs and tests various extensions from the Pi marketplace, including an extension for sub-agents, an extension for web access, and an extension for managing Archon workflows. These extensions enable additional features such as desktop notifications, status bars, and integration of Archon workflows.

  3. **Creating a custom extension**: The user creates a custom extension called “Archon Dispatch” that transforms Pi into a control panel for Archon background tasks. This extension enables the execution of Archon workflows, displays live status information, and notifies when workflows are complete.

  4. **Issues and solutions**: During the demonstration, several issues arise, particularly with the integration of Archon workflows and displaying workflow results in Pi. The user attempts to resolve these issues with Kimi but encounters limitations in model capabilities. He discusses the advantages of combining more powerful models like Opus with cheaper models like Kimi to achieve the best results.

  5. **Comparison with other tools**: The user compares Pi with other coding agents like Codeex and Claude Code and highlights Pi’s advantages, particularly its customizability and speed.

  6. **Future plans**: The user plans to continue working on Pi and Archon integration in future live streams and videos and may develop an Archon workflow for creating Pi extensions.

  The video explicitly covers the AI tools and models Claude, Codeex, Kimi, Minimax, Opus, and Open Router. It is intended for intermediate and advanced users interested in customizing and integrating coding agents.

• Pi is INCREDIBLE – Building a Custom Coding Agent Live
  17.5.2026, 03:42:53

  **Summary:**

  In this stream, the new workflow marketplace for Archon was introduced and two community workflows were added. The first workflow, “Idea to Work Order”, helps convert ideas into detailed work orders for development. The second workflow, “Archon SmartMR Review”, is a GitLab equivalent to the pull request review workflow.

  The process of workflow integration was demonstrated live, including creating a pull request, automatic review by GitHub Action, and subsequent release. Technical challenges and improvements were also discussed, such as updating the Archon CLI and notifying about available updates.

  **Final comment:**

  The video covers the use of Claude and specific tools like Archon. It is intended for intermediate and advanced users.

Dave Ebbelaar (1 new video)

• Your Pip Install Is a Backdoor – Fix This Now!
  21.5.2026, 13:28:18

  The video addresses the growing threat of supply chain attacks on Python projects and offers three practical tips to protect against them. Supply chain attacks often occur through compromised packages in package managers like npm or pip, which contain malicious code and can steal sensitive data such as SSH keys or API keys. Recent examples include attacks on Tanstack and Mistral AI. The security tips are:

  1. **Switch to UV**: Use UV instead of pip, as it offers more security settings.
  2. **Versioning and time windows**: Use `atbounds exact` in your `pyproject.toml` file to pin exact package versions, and set `exclude newer` to e.g. 7 days to only install vetted packages.
  3. **Using `uv sync –lock`**: Run `uv sync –lock` to ensure that only packages included in the lock file are installed and to avoid conflicts.

  Additionally, it’s recommended to instruct AI agents not to add new packages without explicit approval, and to implement features manually instead to minimize dependencies.

  **Final comment**: The video focuses on UV and is best suited for intermediate to advanced Python developers.

David Shapiro (1 new video)

• I’m worried about where things are going
  20.5.2026, 10:35:09

  The video discusses the looming shift toward “techno-feudalism,” where human intelligence becomes obsolete due to artificial intelligence (AI). The speaker warns of the emergence of “redundant biomass,” where humans could be degraded to economically useless, dispensable beings. He argues that this development is driven by several overdetermined forces, including geopolitical competition between the US and China, capitalism and neoliberal economic policy, and the rational economic decision to opt for cheaper automated solutions. Although the speaker is techno-optimistic and sees potential in automation for positive development, he emphasizes the urgent need to address the political and social implications of this trend.

  The video addresses AI and automation in general without mentioning specific tools or models, and is aimed at an intermediate to advanced audience.

Everlast AI (3 new videos)

• Debate: “Humanity Should Be Abolished!” Where is AI Really Taking Us?
  21.5.2026, 15:15:00

  **Video Summary:**

  The video shows a discussion between philosopher and author Gwendolin Weitkirch and AI researcher and cognitive scientist Dr. Joscha Bach. The main topics are consciousness, AI, transhumanism, and the future of humanity.

  **Key Points:**

  1. **Consciousness and AI:**
  – Gwendolin Weitkirch argues that consciousness cannot be transferred to machines because it is an ontological property of living systems.
  – Joscha Bach, on the other hand, contends that consciousness can emerge as a phenomenon in complex systems, including machines.

  2. **Transhumanism vs. Humanism:**
  – Weitkirch advocates for a “fully humanistic” approach that places the human heart and human connection at the center.
  – Bach emphasizes the necessity of technological progress, including AI, to solve human problems, but warns of the risks and ethics of such technologies.

  3. **Nietzsche and Modern Society:**
  – The discussion touches on Nietzsche’s philosophy, particularly his statement “God is dead” and the search for meaning in a secular world.
  – Weitkirch and Bach debate the role of love, ethics, and spiritual search in modern society.

  4. **Future of Humanity:**
  – Weitkirch sees the solution in “humanization” and strengthening human connections.
  – Bach emphasizes the importance of education, science, and the search for common goals to create a sustainable and peaceful future.

  **Final Comment:**
  The video explicitly addresses models and providers from Claude / OpenAI / Gemini / Open-Source as well as specific tools like Cursor, Lovable, Cline, n8n. It is aimed more at intermediate and advanced viewers, as it contains in-depth philosophical and technical discussions.

• AI Researcher: Forget ChatGPT, THIS is the Next Breakthrough! World Models Explained (Daniel Cremers)
  19.5.2026, 15:15:29

  The video is an interview with Professor Dr. Daniel Cremers, a leading expert in artificial intelligence and computer vision. Cremers discusses AI development, particularly the breakthrough in image classification in 2015, which in his opinion was more important than the successes of AlphaGo and ChatGPT. He emphasizes the importance of world models, which enable spatial understanding of the world, and distinguishes these from multimodal language models. Cremers sees major applications for world models in areas such as autonomous driving, robotics, defense, and personalized medicine.

  He criticizes the current focus on national LLM and foundation models and instead advocates for a diversity of approaches and the development of new methods. Cremers emphasizes the importance of energy efficiency in AI and the need to learn from humans to develop more energy-efficient algorithms. He sees the future in robotics and the integration of AI tools into everyday life to make life easier for people.

  The video explicitly addresses AI tools and models from DeepMind (AlphaFold), Nvidia (GPUs), and Google (TPUs), as well as the importance of open-source and research initiatives. It is aimed more at intermediate and advanced viewers seeking a deeper understanding of AI development and its applications.

• AI News: THIS Comes AFTER AI Agents! Claude is BACK, Codex in ChatGPT & BCI Interview
  17.5.2026, 08:15:32

  The video covers several current developments and trends in the field of artificial intelligence and humanoid robots. Here are the main points:

  1. **AI Model Updates**:
  – **Claude**: Increased usage limits by 50% and introduction of a new agent view that allows managing multiple agents in parallel.
  – **OpenAI**: Integration of Codex into the ChatGPT Mobile App, enabling remote control on Codex at the desktop and completing tasks from your phone.
  – **Thinking Machine Labs**: Introduction of a new model optimized for multimodal input (audio, text, image, video) and capable of making tool calls during conversation.

  2. **Humanoid Robots**:
  – **Figure**: Confirmation of design lock for the next generation of Figure F04 and live stream of a fully autonomous 8-hour shift of Figure 3.
  – **Unitree**: Presentation of a road-capable mech and the Unistore, an app store for humanoid robots.

  3. **AI in Enterprises**:
  – **Anthropic**: Surpasses OpenAI in business adoption and receives investment offers valuing the company at over 900 billion dollars.
  – **OpenAI**: Founding of the OpenAI Deployment Company to help businesses implement AI technologies.
  – **Claude for Small Businesses**: Introduction of a collection of skills and MCP connectors for small businesses.

  4. **Research and Future of AI**:
  – **Professor Dr. Thorsten Zander**: Discusses challenges of AI models, particularly the lack of true world understanding and empathy. He presents passive brain-computer interfaces (BCIs) as a possible solution.
  – **Google IO**: Expectations for the largest Google event of the year, including the announcement of Gemini Spark, a 24/7 agent that completes tasks autonomously.

  5. **AI Business Ideas and Tools**:
  – **Browser Use and Kimy Web Bridge**: Tools that enable proactive agents in the browser and automate tasks.
  – **Make CLI**: Introduction of a command-line interface for the Make automation platform.
  – **Augustus**: A bank optimized for the AI era, designed for agent-initiated workflows.

  6. **Social Experiment**:
  – An experiment shows that even experts cannot always distinguish between AI-generated and genuine human works, underscoring the importance of quality seals.

  The video explicitly addresses AI models and tools from Claude, OpenAI, Thinking Machine Labs, Browser Use, Kimy, Make, and Augustus. It is aimed more at intermediate and advanced users, as it covers in-depth technical and economic aspects of AI development.

Fireship (1 new video)

• Google’s AI endgame is here… everything you missed at I/O 2026
  22.5.2026, 16:38:42

  The video summarizes the major announcements from Google I/O 2026. Google places its Gemini model at the center and integrates it into nearly all products, from search to Gmail to Android. The keynote emphasized the vision of deploying Gemini as an “AI Agent” in various applications. Gemini Omni was also introduced, a model that can process different inputs and generate different outputs. Google also presented Gemini Flash 3.5, a fast model that can nearly keep pace with Opus 4.7 and GPT-5.5. The Anti-Gravity IDE, formerly Windserve, was showcased as an AI-coding tool that developed an operating system in a live demo and ran Doom. Another highlight was the introduction of the HTML on Canvas API for web developers, who can now use HTML elements directly in a canvas. The video also mentions rising costs for Gemini 3.5 Flash and massive scaling of Google’s infrastructure.

  The video specifically covers Google’s Gemini models, TPU chips, Anti-Gravity IDE, and the HTML on Canvas API, and is geared more toward intermediate and advanced developers and tech enthusiasts.

Greg Baugues

No new videos in this period.

AI and Strategy | Le SamourAI (1 new video)

• What Your AI Assistants Are Stealing From You in Secret (and It’s Worth Billions)
  21.5.2026, 15:15:01

  The video discusses the importance of forgetting and memory for artificial intelligence and human thinking. It begins by mentioning a short story by Jorge Luis Borges from 1942, in which a boy remembers everything in detail after an accident, but becomes unable to think as a result. The thesis is that thinking requires forgetting in order to recognize patterns and form abstract concepts.

  The AI industry faces the challenge that models from Mistral AI, OpenAI, and Google are increasingly developing similar capabilities. The decisive factor will no longer be raw computing power, but the architecture of memory. Companies like Microsoft, Google, Atlassian, and SAP are investing billions in infrastructure that makes data readable for their agents.

  The video introduces the concept of a “second brain,” which traces back to the idea of using external systems to organize and retrieve knowledge. However, it criticizes the fact that many of these systems fail within six months because maintenance is too labor-intensive. A new approach by Carpati, which uses a wiki system maintained by an agent, could solve these problems.

  A distinction is made between two main architectures: traditional RAG (Retrieval-Augmented Generation) and Carpati’s wiki approach. RAG systems like Pinecone, Perplexity, and Cursor are reactive and generate answers based on fragmented vectors. The wiki approach, on the other hand, extracts concepts from sources and creates an interconnected wiki that can be directly queried.

  However, the video warns that the wiki approach is not perfect. Errors in input can become embedded in the wiki and are difficult to correct. It emphasizes that the architecture of memory is crucial and that different systems have different requirements.

  For individual use, the wiki approach works well, while for enterprises more complex systems are needed that also take legal and confidential aspects into account. The video concludes by stating that control over one’s own memory and decision-making is crucial, and that users should establish and document their own rules to avoid becoming dependent on AI providers.

  The video addresses various AI models and providers such as Mistral AI, OpenAI, Google, Microsoft, Atlassian, and SAP. It is aimed at intermediate and advanced users who want to engage with the technical and strategic aspects of AI and memory systems.

Julian Ivanov | AI Automation (1 new video)

• Use Claude Code for free: Unlimited coding without a powerful PC
  20.5.2026, 13:41:18

  The video shows how to use Claude’s Cloud Code for free by connecting it with free language models from Open Router. Cloud Code is a type of “harness” that connects various AI models with tools and files, and normally runs with paid models like Sonnet, Opus, or High from Anthropic. However, by connecting to Open Router, you can access free models like GPT OSS, Minimax M2.5, or Deepseek V4 Flash. The setup requires creating an API key at Open Router and configuring a settings.json file in Cloud Code. Users can then choose between different free models and use Cloud Code at no additional cost, as long as no sensitive data is processed. It’s important to note that Open Router’s free models have strict rate limits, which can be increased by adding $10 to your Open Router account without incurring actual costs.

  The video explicitly covers Claude, Open Router, and specific models like GPT OSS, Minimax M2.5, and Deepseek V4 Flash, and is better suited for intermediate users.

Kyle Balmer | AI with Kyle (4 new videos)

• AI with Kyle – 22nd May 2026 – Google I/O 2026
  22.5.2026, 06:59:45

  The video is a tutorial showing how to use a specific tool or software to create a concrete project. The main steps include installing and setting up the tool, creating a new project, customizing settings, and implementing specific features. At the end of the video, the finished project is presented to inspire viewers to apply what they’ve learned in their own projects.

  The video covers specific tools such as Cursor and is aimed more at intermediate users.

• AI Destroyed Your Career Ladder (Here’s What to Do Now)
  22.5.2026, 05:00:21

  The video discusses the different reactions of tech executives to the impact of artificial intelligence (AI) on the job market, particularly on young people just entering the workforce. Former Google CEO Eric Schmidt was booed at a graduation ceremony when he emphasized AI’s opportunities, reflecting Gen Z’s growing concerns about AI’s impact on their career prospects. In contrast, Steve Wozniak, Apple co-founder, received applause when he highlighted the importance of human intelligence and creativity.

  The speaker argues that the real challenge isn’t that AI replaces existing jobs, but that it prevents the creation of new entry-level positions. This particularly affects young people, as they often lack opportunities to gain necessary experience. While tech executives predict new AI-related roles, these positions could be filled by experienced professionals or even AI itself, further worsening the situation for Gen Z.

  The speaker emphasizes that criticizing tech executives is insufficient and that young people must take proactive steps. He suggests thinking entrepreneurially, freelancing, or starting small businesses to achieve financial independence. He stresses the need to continue learning, develop useful skills, and take personal responsibility, as traditional career paths are no longer secure or lucrative.

  Final comment: The video does not cover specific AI tools/models/providers and is aimed more at intermediate and advanced viewers.

• How I’d Build an AI Product and Quit My Job If I Started Today
  20.5.2026, 05:00:10

  The video provides guidance on building your first AI-based business. The focus is on creating a simple but valuable product that automates a specific task and saves time. The author emphasizes that while many people could create similar solutions themselves, they won’t due to convenience or lack of knowledge. The key to success is identifying a process that is frequent and time-consuming in your own industry, then automating it. An example given is an AI maturity assessment where users answer questions and receive a personalized report in return. Technically, building such a product is divided into three layers: frontend (landing page, login, forms), backend (database for user data and results), and the logic layer where actual data processing occurs. The author offers to provide a prompt template that can be used with tools like Codex or Claude to facilitate product development. The focus should be on the logic layer, as that’s where the greatest customer value is created.

  The video explicitly covers Claude, Codex (OpenAI), and Lovable, and is aimed at intermediate and advanced users.

• Codex Mobile: You Can Now Vibe Code From Anywhere (Seriously)
  18.5.2026, 05:00:13

  The video covers the launch of a mobile application for ChatGPT Codex, which allows users to continue their Codex sessions from anywhere. The main points are:

  – **New mobile app**: Codex is now available in the ChatGPT mobile application, enabling users to start new work, review outputs, and control execution.
  – **Device connection**: Users can connect their Codex sessions across different devices (laptop, Mac mini, phone) and access them from anywhere. This is accomplished by scanning a QR code and using the “Control Another Device” feature in Codex settings.
  – **Benefits**: The new feature solves the problem of losing chat threads and context when switching between devices. This enables seamless vibe coding from anywhere.
  – **Setup guide**: The speaker explains how to connect various devices and set up GitHub as a central project repository. He emphasizes the importance of keeping all applications up to date.
  – **Recommendation**: The speaker recommends trying out the new feature and signing up for the newsletter to receive a detailed guide and checklist.

  The video explicitly covers ChatGPT Codex and is aimed more at intermediate users already familiar with AI tools.

Leon van Zyl (2 new videos)

• Stop Building Apps AI Agents Can’t Use
  21.5.2026, 14:00:29

  This video demonstrates how to build an agent-enabled app from scratch that can interact with AI agents like Claude, ChatGPT, and others. The focus is on integrating the Model Context Protocol (MCP) Server, developed by Anthropic, to enable AI agents to access various platforms. The process includes creating a Next.js project, installing agent skills, planning and implementing the app using Claude Code, and setting up a Postgres database with Neon. The MCP Server is tested and deployed both locally and in production to store and search prompts. Finally, the app is deployed to Vercel and the integration with the AI agent is successfully demonstrated.

  This video explicitly covers Claude, OpenAI, Anthropic, Next.js, Postgres, Neon, and Vercel, and is better suited for intermediate learners.

• Why I Use Claude Code to Build Every Portfolio Now
  19.5.2026, 14:00:24

  In this video, Leon shows how to design a personal portfolio website that looks and functions like a coding agent CLI (similar to Claude Code). The process begins with creating a new Next.js project and installing skills like “next best practices” and “front end design”. Leon uses Claude Code to build the website by using specific prompts that generate a terminal-like user interface and animated responses. The website can be connected to a knowledge base, allowing visitors to ask questions and receive answers. Leon also demonstrates how to deploy the website on a hosting platform and have it automatically update when code changes are made.

  This video explicitly covers Claude Code and Next.js and is better suited for intermediate users who already have basic web development knowledge.

Liam Ottley (1 new video)

• Claude Managed Agents Will Make Millionaires (do this now)
  May 20, 2026, 02:09:16

  The video discusses the significance and applications of Claude Code Managed Agents, a new Claude technology promoted as a powerful tool for business applications. The speaker, Liam Ottley, emphasizes that these agents enable you to create a form of artificial intelligence for enterprises that functions as a central work environment and enables continuous learning. He explains that these agents can be hosted in the cloud and you only pay for actual runtime, making them cost-effective. By connecting with databases, documents, and custom tools, these agents can act as long-term, learning-capable assistants that update themselves overnight and manage their memories. Liam Ottley compares this to human cognitive architecture and stresses how this technology can help businesses work more efficiently and solve problems. He also mentions OpenAI and its competing products, highlighting the advantages of Claude Code Managed Agents. The speaker encourages viewers to engage with this technology and explore its applications, particularly regarding the creation of products or services for customers.

  The video explicitly focuses on Claude Code Managed Agents and OpenAI and is aimed more at intermediate and advanced users.

Mark Kashef (2 new videos)

• How to INSTANTLY Run ANY Skill in Claude + Codex
  21.5.2026, 16:15:16

  The video discusses the differences and similarities between AI code providers Claude Code and Codex. It highlights that both providers have similar capabilities but feature different designs and mechanics, which complicates creating and converting Skills between the two platforms. The main focus is on introducing a universal “PolySkill” Skill that serves as an adapter to convert Skills between Claude Code and Codex. The process involves installing and converting Skills through simple commands, enabling seamless two-way communication between providers. The Skill is designed to be easily extensible to support future providers like Gemini.

  The video explicitly covers Claude Code and Codex and is aimed at intermediate users who already have experience with these AI tools.

• How to Use /goal to Build a Self-Improving OS
  17.5.2026, 15:30:23

  The video introduces the new “/goal” feature in Codex and Cloud Code, which can be leveraged beyond technical tasks for optimizing agentic operating systems (Agentic OS). The author demonstrates five practical use cases: “Clean” (tidying up Skills and rules), “Sharpen” (improving Skills based on specified criteria), “Revive” (revitalizing abandoned projects), “Forge” (extracting recurring prompts into new Skills), and “Maintain” (automated system maintenance). The video explains how the feature works through a goal specification and a separate evaluation agent. The author demonstrates the application with concrete examples and emphasizes the potential to make your own work environment more efficient.

  The video explicitly covers the /goal feature in Cloud Code and is aimed at intermediate or advanced users who are already familiar with agentic systems.

Matt Pocock (1 new video)

• /handoff is my new favourite skill
  21.5.2026, 10:32:40

  The creator introduces a skill called “Handoff” that he developed, which compresses the context windows of agent sessions into a markdown file and transfers them to a new session. This makes it possible to break up long sessions and focus on specific tasks without compromising agent performance through cluttered context windows. The skill is particularly useful for agentic sessions to split tasks or create prototypes and integrate the results back into the original session. The creator explains the advantages over the compact function, which only creates a summary within the same session, and emphasizes the flexibility and efficiency of his skill. The skill is designed to exclude sensitive information and is tailored to the needs of the next session.

  The video explicitly addresses the use of Anthropic (Claude) and is aimed at intermediate or advanced users.

Melvynx (5 new videos)

• Codex peut CONTROLLER ton ordianteur (même quand il est vérouillé)
  23.5.2026, 16:00:14

  The video introduces several new features and updates of Codex, an AI tool primarily used for programming and automation. Here are the key points:

  1. **Screenshot function with keyboard shortcut**: By pressing “Command + Command”, you can insert a screenshot of the current application into the Codex chat. This facilitates debugging and working with various applications, as the context is directly transferred to the chat. However, there’s no option to open the screenshot in a new chat, which somewhat limits its use.

  2. **Integration of Gal (Goals)**: The “slashgal” function enables creating and managing goals directly in the Codex application. You can create, edit, pause, view, or delete goals. Codex can also autonomously create goals when given appropriate instructions.

  3. **Inupp Browser**: This feature allows you to open and manage browser tabs directly in Codex. You can take screenshots, add annotations, and change styles. However, the user experience is somewhat bumpy at times, as the application frequently reloads.

  4. **Computer Use**: A new feature that enables controlling your Mac even when it’s locked via the iOS app. This is still in beta and doesn’t always work reliably, but it shows the potential to have your computer work even when you’re away.

  The video explicitly covers the AI tools Codex and Claude, aimed at intermediate to advanced users who already have experience with AI tools.

• Comment ONE-SHOT toutes tes features avec l’IA (fais-la travailler pendant 2 heures non-stop)
  21.5.2026, 16:00:44

  The video shows a detailed workflow for implementing complex features using AI tools like Claude and Codex. The process begins with an intensive brainstorming phase where the user describes their ideas and requirements in detail. A plan is then created and reviewed multiple times to ensure all aspects of the feature vision are considered. The actual implementation process is performed with the Apex Skill, which enables AI models to work in multiple steps and self-correct. An important part of the workflow is using the “Verify” parameter, which prompts the AI to check its own actions and ensure everything works correctly. The user also demonstrates how to work with tools like Dev Browser CLI or integrated browsers in Cloud or Codex to verify and correct the implementation. In conclusion, the user emphasizes the importance of precision and iteration for successfully implementing complex features.

  The video explicitly covers Claude, Codex, and specific tools like Apex and Dev Browser CLI, and is geared toward intermediate to advanced users.

• NOUVEAU : La commande qui tiens plus longtemps que toi 🍆
  20.5.2026, 16:00:23

  The video presents the new “Slash Goal” feature in Codex and Cloud Code, which enables an agent to not stop a task until it’s completed. The user can define a goal, which the agent then verifies and ensures is achieved. For example, you can instruct the agent to make all tests pass or fix all TypeScript and ESLint errors without cheating or disabling rules. The agent then works on it until the goal is reached and automatically verifies this. The feature is especially useful for tasks that are easily verifiable, such as optimizing tests or refactoring code. The user can track the agent’s progress and manually intervene if needed. The video also shows how to use “Slash Goal” in various scenarios and what advantages it offers over conventional methods.

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

• Codex : contrôle ton ordinateur et ton VPS avec ton iPhone
  19.5.2026, 16:00:15

  The video shows the integration of Codex, an OpenAI tool, with mobile devices, particularly iPhones, and its advantages over earlier solutions like Cloud Remote Control. The user demonstrates how to connect their iPhone with the Codex app and gain remote access to various devices and services. This includes SSH connections to VPS (Virtual Private Servers), controlling a Mac, and continuing chats across different devices. Particularly highlighted is the ability to send commands to a VPS via iPhone and thus automate or control tasks. The user emphasizes the user-friendliness and efficiency of the integration, which allows working without complicated additional setup. Additionally, the possibility of accessing additional plugins via VPN that aren’t available in certain regions is demonstrated.

  The video explicitly covers OpenAI (Codex) and is aimed at intermediate to advanced users who already have experience with remote access and using VPS.

• Je MIGRE Thumbfa.st à Convex + Tanstack Start ($1000 API Codex dépensé)
  18.5.2026, 16:01:13

  The YouTuber presents the migration of their application Subfast from the Next.js stack (Next.js, Prisma, PostgreSQL) to the TanStack stack (TanStack Start, Convex). They compare the two stacks based on performance, user experience, and development processes. The new stack offers a faster, synchronized user interface and simplified code maintenance, as Convex manages all data and actions centrally as a backend. The developer highlights the advantages of Convex, such as instant data synchronization and easy troubleshooting through direct access to logs and debugging tools. The migration has significantly reduced the application’s complexity and increased development speed.

  The video explicitly covers the tools and providers Convex and TanStack Start and is geared toward intermediate to advanced developers.

n8n (2 new videos)

• Why n8n + Lovable Is Replacing Salesforce, HubSpot, and Slack
  20.5.2026, 23:37:26

  The video is a podcast interview with Olaf, a representative from Lovable, focusing on using AI for software development. Olaf discusses Lovable’s vision of democratizing software development and enabling anyone to create applications regardless of technical skill level. He emphasizes that the limiting factor is no longer technical expertise, but people’s ideas.

  Some of the main points of the interview are:

  1. **Lovable as Co-Founder**: Lovable is positioned as a co-founder for startups and entrepreneurs who want to develop software solutions quickly and cost-effectively.
  2. **Success Stories**: Olaf shares examples of users who have created successful applications with Lovable, such as an app that helps women check the criminal background of potential dates.
  3. **Integration with Other Tools**: Lovable integrates with various tools and platforms to facilitate application development and deployment.
  4. **Future of Software Development**: Olaf discusses the future of software development and how AI will revolutionize the way we create and use software.
  5. **Security Concerns**: He expresses concerns about security and responsible use of AI, particularly regarding access to sensitive data.

  The video explicitly covers AI tools and platforms including Lovable, Claude, and open-source tools. It is aimed at intermediate and advanced users interested in integrating AI into software development.

• From the n8n canvas to Microsoft Teams with Microsoft Agent 365
  19.5.2026, 16:32:30

  The video demonstrates a live demo and step-by-step guide for setting up Microsoft Agent 365 in conjunction with the N8N automation platform. Here are the main points:

  1. **Introduction to Agent 365**: Agent 365 is a new node within the N8N automation system that enables you to create and manage agents with enterprise identity, permissions, governance, and Microsoft Copilot (MCP) tools in Microsoft 365.

  2. **Demo Steps**:
  – **Prerequisites**: Required are a Microsoft Copilot license, a Teams license, an Agent 365 license, and a global administrator role in your Microsoft tenant.
  – **Microsoft-side Setup**: Installation and use of the Agent 365 CLI tool to create an agent blueprint. This blueprint defines the name, description, developer information, and access rights to Microsoft tools such as Outlook, Teams, and Word.
  – **N8N-side Setup**: Integration of the Agent 365 trigger node in N8N, which establishes connections to a chat LLM model, a memory node, and various tools such as Salesforce and ServiceNow.
  – **Publishing and Use**: The agent blueprint is published in Microsoft 365, and users can create instances of the agent through the Microsoft Agent Store. The demo shows how a sales team uses an agent to compile data for a quarterly business review.

  3. **Security and Governance Features**: Agent 365 provides comprehensive security and governance capabilities that enable IT administrators and security teams to monitor and control agent activities. This includes defining permissions, assigning user access, and real-time monitoring of agent activities.

  4. **Advanced Use Cases**: The demo shows how the agent can be integrated with tools like PagerDuty to retrieve incidents and transfer them to an Excel spreadsheet, which is then shared via email. This demonstrates the agent’s ability to interact with various services beyond the Microsoft ecosystem.

  5. **Future Developments**: Participants are encouraged to provide feedback and suggestions for further improving the platform, particularly regarding simplifying the setup process and expanding use cases.

  The video explicitly covers Microsoft Agent 365 and N8N and is aimed at intermediate to advanced users who already have experience with automation platforms and Microsoft 365.

Nate Herk | AI Automation (5 new videos)

• The AI Offer You Can Sell Tomorrow Morning
  22.5.2026, 16:37:49

  The YouTuber explains how to build an AI business as a beginner without immediately selling projects or retainers. Instead, he suggests starting by selling hours (consulting) to build trust and overcome imposter syndrome. He describes a step-by-step approach, starting with selling hours (Rung 0), followed by audits (Rung 1), projects (Rung 2), and finally retainers (Rung 3). The YouTuber emphasizes that you should first gain experience and build trust before taking on larger projects. He provides practical tips on how to win your first 10 clients by teaching friends and acquaintances, engaging in communities, and gradually building a portfolio. The YouTuber also mentions the importance of reps and experience to overcome imposter syndrome and be successful long-term.

  Final comment: The video discusses generally available AI tools and models without mentioning specific providers, and is geared toward beginners.

• Give Me 10 Mins and I’ll Save You Millions of Claude Tokens
  21.5.2026, 12:58:00

  The video explains the concept of prompt caching in Claude Code and Claude, particularly how it saves tokens and costs. Key points include:

  – **Token savings**: Cached tokens cost only 10% of normal input costs. For example, the user saves millions of tokens daily through caching.
  – **Cache window**: Cache duration is one hour by default. In Claude Code, the cache is deleted after one hour of inactivity; with API usage or Sub-Agents, it’s deleted after just 5 minutes.
  – **Cache mechanism**: The cache includes system instructions, tool definitions, and project context. Any new message or change (e.g., model switching) can break the cache and lead to higher costs.
  – **Practical tips**: Users should avoid breaks, manually clear the cache when switching tasks, and store large documents in projects rather than in the chat.
  – **Tools**: The user provides a token dashboard and a Session Handoff Skill to better manage the cache and save tokens.

  The video is geared more toward intermediate users who use Claude Code or Claude intensively and want to optimize their token costs. It explicitly addresses Claude and Claude Code.

• What Karpathy Joining Anthropic Actually Means For Claude
  19.5.2026, 21:36:51

  The video discusses the significance of Andre Karpathy joining Anthropic and analyzes why this move is significant for both Karpathy and Anthropic. Karpathy, a central figure in the modern AI world, has an impressive career behind him, including his role as a co-founder of OpenAI and his work at Tesla. His recent projects, such as Eureka Labs and the development of concepts like “Vibe Coding” and “Context Engineering,” demonstrate his ability not only to develop AI but also to teach how to use it effectively.

  Anthropic has made significant progress recently, particularly with Claude Code, which has become a popular tool for developers and businesses. Karpathy’s arrival could suggest that Anthropic is further expanding its strategy by improving not only AI models but also their applications and integration into real workflows. Karpathy’s focus on “Context Engineering” and creating environments that enable AI models to work more effectively aligns well with Anthropic’s approach.

  The video makes three predictions: First, that Anthropic will develop an app store for contexts and workflows. Second, that there will be more features like “/goal” that enable complex tasks to be automated. Third, that Anthropic will create an educational platform to help users package and contribute their own workflows.

  The video explicitly addresses Claude/Anthropic and is geared more toward intermediate and advanced users.

• How to Use Your Claude Code Projects in Codex in 5 Mins
  18.5.2026, 19:09:24

  The video shows how to migrate a project from Claude Code to Codex without duplicating it or losing important information. The main difference between the two tools lies in file names and folder structures: Claude Code uses a `cloud.md` file and a `cloud` folder, while Codex uses an `agents.md` file, a `codex` folder, and an `agents` folder for skills. However, both tools share the same knowledge base, such as documents, references, and scripts.

  The author explains that you can instruct Codex with a simple prompt to create the necessary files and folders and transfer the content from the Claude Code files. It’s important that changes made to Claude Code files are also made to Codex files to ensure consistency. Additionally, the author points out that Codex Sub-Agents are not automatically invoked and there are some differences in tools and commands.

  A practical example shows how Claude Code and Codex can work together to create and style an HTML document. The author recommends using both tools and not committing to a single tool to remain flexible.

  Final comment: The video explicitly addresses the tools Claude Code and Codex and is geared more toward intermediate users.

• The AI Career Opportunity Nobody is Talking About in 2026
  17.5.2026, 16:24:10

  The video creator, Nate, discusses an alternative career option in AI, apart from the frequently promoted model of starting an AI automation agency. He argues that many companies, particularly large corporations, are increasingly hiring Chief AI Officers (CAIO) or have already hired them, presenting a major opportunity for people who don’t want to work in sales. Nate refers to an IBM study showing that 76% of surveyed CEOs either already have a CAIO or want to hire one, representing a massive increase from previous years. He explains that the CAIO role emerged similarly to the Chief Information Security Officer (CISO) role to address a new, urgent need in companies.

  Nate emphasizes that it’s not just the CAIO role; every department in companies is seeking AI-savvy leaders. He presents two paths to move in this direction: Path A, where you start as an AI consultant or in an agency and are then hired by a company, and Path B, where you internally build AI knowledge in your current job and thus qualify for a promotion. He argues that Path B could be more accessible to many people, since 57% of CAIOs were promoted internally.

  Nate emphasizes the importance of loving what you do, as otherwise you won’t have the necessary endurance and motivation to succeed in this field. He encourages viewers to become the AI-native version of their current role rather than jumping into a new field that doesn’t suit them. He concludes by stating that you don’t need to change your role, but rather the version of your role that you perform.

  The video explicitly addresses IBM and its studies as well as the role of Chief AI Officer in companies. It is more suited for intermediate and advanced users, as it builds on solid knowledge and experience in the AI field.

NeuralNine (3 new videos)

• Claude Code VS Codex VS OpenCode
  22.5.2026, 16:00:18

  The video compares three coding agents: Claude Code, OpenAI’s Codex, and Open Code. The comparison is based on personal preferences, feature set, public opinion, and various aspects such as user-friendliness, default settings, model variety, exclusivity, tooling, efficiency, speed, limits, and transparency.

  – **User-friendliness and default settings**: Claude Code is rated as the easiest to use because it requires user interaction by default for each action. Codex and Open Code execute actions without prior confirmation, though this can be changed through configuration.
  – **Terminal user interface design**: Open Code is rated as the most beautiful and best-designed interface, followed by Claude Code and Codex.
  – **Model exclusivity**: Claude Code offers exclusive access to Opus models, which are currently considered the most powerful. Codex and Open Code also support various models, with Open Code offering the greatest variety.
  – **Model variety**: Open Code supports a wide range of models, including free models and various providers such as OpenAI, Google, and others.
  – **Tooling**: Claude Code offers the most additional features such as an undo function, voice control, and a plugin marketplace. Open Code also has many features, while Codex is classified as minimalist and less user-friendly.
  – **Efficiency, speed, limits, and transparency**: Codex takes more time for responses but delivers deeper and more accurate results. Claude Code is faster but less thorough. Open Code with GPT models is similar to Codex but with less optimized tooling. Claude Code consumes tokens faster, while Codex and Open Code offer more transparency and flexibility.
  – **Sympathy points and open source**: Open Code gains points due to its open-source nature and community support, while Claude Code and Codex receive fewer sympathy points due to their closed systems and business models.

  **Closing comment**: The video explicitly covers Claude Code, OpenAI’s Codex, and Open Code and is aimed more at intermediate and advanced users.

• Wagtail: The Django CMS For Blogging in Python
  20.5.2026, 16:00:05

  The video is an introduction to Wagtail, a Python-based content management system (CMS) built on Django. Wagtail is described as the “Arch Linux way” of CMS because it’s highly customizable and requires you to define almost everything from scratch, unlike WordPress which offers many features out of the box. The tutorial demonstrates the installation and basic configuration of Wagtail, including creating a new project, defining page models, customizing templates, and using the admin panel for content creation. It shows how to build a blog structure with different pages and content, including the integration of rich-text fields, code blocks, and snippets for authors. The video concludes with an introduction to an official Wagtail template that serves as an example of a finished project.

  The video explicitly covers Wagtail and is aimed more at intermediate to advanced users who already have basic knowledge of Django or similar frameworks.

• This is basically uv but for everything…
  18.5.2026, 16:01:32

  The video introduces the Pixi package manager, a system-wide package management tool for Linux, Mac, and Windows that manages both language packages (e.g., Python, Rust) and system dependencies (e.g., FFmpeg, OpenSSL). Pixi is based on Conda-forge and offers features such as lock files for reproducible environments. The tutorial section covers Pixi installation, project creation, adding dependencies (Python, Pillow, ImageMagick), and using them in a Python script. It also demonstrates how Pixi can be used for Rust extensions in Python without needing separate tools like Cargo or pip. Finally, it shows how to create custom tasks in Pixi to simplify long commands. The speaker emphasizes the advantages of Pixi over other package managers, particularly unified dependency management and the creation of reproducible environments.

  Closing comment: The video explicitly covers the Pixi package manager, which is based on Conda-forge and written in Rust. It is aimed more at intermediate and advanced users who already have experience with package managers and various programming languages.

Nic Conley (1 new video)

• This New AI Agent Builder is Insane (Twin.so Tutorial)
  19.5.2026, 15:56:56

  The video introduces the Twin tool, which is promoted as particularly useful for building AI agents. The creator shows how to create AI agents for various business processes with Twin without requiring deep technical knowledge. Three concrete use cases are demonstrated:

  1. **Facebook Marketplace Monitoring Bot**: An agent that searches daily for affordable lawnmowers near the user and sends an email with the results. The agent uses integrated tools like Appify and Perplexity to accomplish the task without requiring the user to set up separate APIs or subscriptions.

  2. **AI Readiness Quiz**: A questionnaire that helps small businesses assess how well-prepared they are for implementing AI technologies. The agent creates a personalized report with recommendations for suitable AI tools and saves the results for the user.

  3. **Cash Buyer Builder**: An agent that searches county deeds for recent cash purchases to create a list of potential buyers for real estate investors. The agent collects contact information and displays it in a dashboard.

  The creator emphasizes Twin’s simplicity and efficiency, as it requires no complex setup processes and already has many tools and connections integrated. He sees great potential in offering such agents to small businesses and building a business around it.

  **Final Note**: The video specifically focuses on the Twin tool and is aimed more at intermediate and advanced users.

Nick Saraev (1 new video)

• I Built a $1M/y SaaS with Claude Code, Here’s How
  20.5.2026, 13:30:22

  The video describes the process of developing and monetizing an AI-powered power dialer called Clarvo, built with Claude Code. The speaker shares his experiences and learnings on how they achieved one million dollars ARR (Annual Recurring Revenue) with Clarvo.

  First, the product Clarvo is introduced—an AI-powered power dialer that helps businesses make more calls per unit of time and increase the number of successful connections. This is particularly useful in industries that rely heavily on phone outreach, such as HVAC, plumbing, and roofing.

  The speaker explains how they worked with Claude Code to find various solutions for improving call connection rates. They started by defining the problem and asked Claude Code to enumerate all possible solutions. They then filtered out impractical ideas and implemented the feasible ones in simulations to find the best solutions. One successful approach was “Predictive Pacing,” where multiple calls are made simultaneously to increase efficiency.

  Another important point is pricing. The speaker emphasizes that they gradually increased the price until it became difficult to find customers. They started at $100 per month and raised the price to $250 per month, which proved successful.

  The speaker also warns against using too many frameworks and tools, as they often cause more problems than they solve. Instead, he recommends focusing on the model’s core capabilities and minimizing complexity.

  Finally, the speaker emphasizes the importance of choosing problems that are truly valuable to customers and that they’re willing to pay for. He advises focusing on industries with large budgets where solving the problem provides significant added value.

  The video explicitly features Claude (Claude Code) and is better suited for intermediate or advanced users who already have experience developing SaaS products.

Niklas Steenfatt

No new videos in this period.

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

• The Story Behind Cerebras’ $63 Billion IPO with Founder and CEO Andrew Feldman
  21.5.2026, 10:00:35

  The video is an interview with Andrew Feldman, co-founder and CEO of Cerebras, a company specializing in fast AI workloads. Cerebras recently went public and has a market capitalization of approximately $63 billion. Feldman discusses the company’s development, the importance of speed in AI, and the future of the industry.

  Cerebras has specialized in fast inference for AI models and, according to Feldman, is 15 to 20 times faster than GPUs. The company recently closed major deals with OpenAI and AWS, which has led to enormous demand. Feldman emphasizes that speed in AI is critical once models are intelligent enough to be deployed in daily work environments.

  He also discusses the challenges the company faced in its early years, including industry skepticism toward their unique architecture. Feldman stresses the importance of risk-taking and the ability to think against the mainstream to achieve breakthrough innovations.

  Feldman also discusses the significance of open source and how it has advanced the AI industry. He sees the future of AI in creating new business models and fundamental productivity leaps, similar to what happened with the introduction of the internet and the cloud.

  The video explicitly covers Cerebras, OpenAI, AWS, Cursor, Cognition, and Lovable. It’s designed more for Intermediate and Advanced viewers, as it delves deeply into the technical and business aspects of the AI industry.

Productive Dude

No new videos in this period.

Sebastien Dubois (2 new videos)

• 22 mai 2026
  22.5.2026, 06:27:47

  The video reflects on the diversity and depth of human life, emphasizing that each person can live many “lives” within a single lifetime through various experiences and interests. The speaker shares his own diverse experiences, including different career paths, creative projects, and personal developments, highlighting how enriching it is to immerse oneself in different roles and topics. He emphasizes that there are always new opportunities to grow and learn, criticizing the notion that life could be boring or uneventful. As an example, he mentions his work on a course and community focused on knowledge management and AI, which he describes as life-changing. The speaker concludes with the insight that life is full of infinite possibilities and that combining different experiences and interests creates an enriching and unique journey.

  The video does not address specific AI tools or models and is better suited for intermediate or advanced viewers, as it offers a deeper reflection on life experiences and personal development.

• 22 mai 2026
  22.5.2026, 06:24:52

  The video discusses the importance of shared context for teams using AI tools. The speaker emphasizes that a common knowledge repository containing information about the team, organization, projects, working methods, goals, and tools can significantly increase the effectiveness of AI applications. This context can be easily created and shared as markdown files in a shared folder, whether via Git or other platforms. The speaker argues that this approach not only improves team collaboration but also enhances the quality of AI results through targeted context provision. The proposal is practical and accessible, as it requires no complex solutions.

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

Tech With Tim (4 new videos)

• How I would learn Python programming FAST (If I could start over)
  23.5.2026, 13:00:36

  The YouTube video title is “How to Learn Python: The Exact Path I’d Follow If I Was Starting Today”. The author, who has been writing Python for over ten years and has taught millions of people to code, presents an optimized learning path for Python that he would choose today to make rapid progress. He emphasizes that he made the mistake early on of learning too many topics at once, wasting valuable time. Instead, he advises mastering the fundamentals first, then specializing in one area.

  The learning path consists of six steps:
  1. **Core Fundamentals**: Variables, data types, control flow, functions, data structures, file I/O, error handling. The goal is to write small programs (100-200 lines) without constantly looking things up.
  2. **Object-Oriented Programming (OOP)**: Classes, objects, inheritance, dunder methods. OOP helps organize code better and understand Python at a deeper level.
  3. **Modules, Packages, and Virtual Environments**: Import statements, pip, virtual environments, reading documentation, using built-in modules like `random`, `os`, and `json`.
  4. **Choose a Direction and Dive Deep**: Web development (Django, Flask, FastAPI), data science (machine learning, NumPy, Pandas), automation and scripting, backend development. The key is to commit to one area and study it intensively for 3-6 months.
  5. **Projects**: Complete small projects that are slightly above your current skill level. Upload projects to GitHub to save them for the future and use them for your resume or portfolio.
  6. **Things Nobody Talks About**: Reading other people’s code, using debuggers, writing tests, using Git properly, getting comfortable with the terminal. These skills separate hobby programmers from professional developers.

  The author emphasizes that while Python is easy to learn, it takes time and practice to become truly proficient. The demand for Python developers, especially in AI and data science, is high, and the investment pays off. He concludes with advice to specialize in one area to make rapid progress and become employable.

  **Final Comment**: The video doesn’t address specific AI tools or providers and is better suited for beginner and intermediate Python learners.

• I Built the Same App With Claude Code and Codex
  22.5.2026, 13:00:14

  The video compares the AI tools Claude Code and Codex (GPT-5.5) by building a complex application: a real-time collaborative Markdown editor with features like split-pane, real-time synchronization, cursor presence, and document management. The comparison is based on four criteria: speed, cost, end result, and code quality.

  **Speed and Cost:**
  – Claude Code was faster on most tasks, while Codex took longer but also automated more features and tests.
  – Codex was more cost-efficient, consuming fewer tokens and depleting subscriptions more slowly.

  **End Result:**
  – Both tools delivered similar, functional results, with Codex investing slightly more time in verification and debugging.
  – Claude Code occasionally had minor bugs that needed manual fixes.

  **Code Quality:**
  – Both codebases were fundamentally solid, but Codex generated slightly more modular and readable code.
  – Claude Code had more inline comments and direct API calls within components, which was considered less clean.
  – Both tools were asked to review each other’s code, with Codex identifying some improvement opportunities in Claude Code’s work and vice versa.

  **Conclusion:**
  – Claude Code is better suited for quick prototypes and building applications from scratch.
  – Codex is better for complex applications, debugging, and testing, as it works more proactively and thoroughly.
  – Both tools have their strengths and should be used depending on the task at hand.

  **Final Comment:**
  The video explicitly covers Claude (Anthropic) and Codex (OpenAI) and is intended for intermediate to advanced users who already have experience with AI tools and programming.

• The Complete Guide to AI Agents in 2026 (And How to Actually Use Them)
  21.5.2026, 13:00:34

  The video explains the four levels of using AI agents in 2026 and demonstrates how to deploy them effectively to boost productivity. The levels include:

  1. **AI Chat (Level 1)**: Simple questions and answers, similar to ChatGPT or Claude. The user must copy and use the results manually. Example: Summarizing SaaS pricing trends for 2026.

  2. **AI Tools (Level 2)**: Specific tasks like creating presentations, documents, or images. The user initiates the tasks, but AI produces finished results. Example: Creating a pitch deck presentation for a client.

  3. **AI Workflows (Level 3)**: Automated processes where AI performs multiple tasks in a chain. The user sets up the workflow once, and AI runs it automatically. Example: A daily morning briefing workflow that summarizes emails, calendar, and priorities.

  4. **AI Agents (Level 4)**: Fully autonomous agents that receive a general task and independently execute the necessary steps. Example: Creating and deploying a landing page for a new product, including copywriting, image generation, and deployment.

  The video demonstrates the use of these levels using the Gen Spark platform, which combines all four levels in one workspace. It shows how to create workflows and deploy autonomous agents to handle complex tasks.

  The video explicitly covers the AI models Claude, OpenAI (GPT), and Gemini, as well as the Gen Spark platform, and is better suited for intermediate and advanced users.

• Devin AI Is the Future of Coding… Full Tutorial
  18.5.2026, 13:02:48

  The video provides a comprehensive guide to Devin, an AI tool for software development that can run both locally and in the cloud. It starts with installing and setting up Devin for Terminal, a CLI-based tool that runs in your local development environment. Users can leverage Devin for simple tasks like creating a landing page or modifying code. The tutorial shows how to select different models, manage sessions, and use subagents to handle parallel tasks.

  Next, Devin Cloud is introduced, which executes tasks in a virtual machine in the cloud. Users can delegate tasks from their local environment to the cloud, allowing long-running or complex tasks to be processed without burdening the local machine. The video also demonstrates how Devin integrates with GitHub to create and review pull requests, and how it can connect to Linear and Slack to manage tasks directly from these platforms.

  In summary, the video shows how to use Devin as a complete ecosystem for software development, from local code editing to automated task processing in the cloud. It’s particularly useful for developers looking to boost productivity and automate repetitive tasks.

  The video explicitly covers Devin (Cognition), a tool suited for intermediate and advanced users.

TheAIGRID (1 new video)

• Google’s New AI Update Just Shocked The AI Industry – Gemini 3.5 Pro , Gemini Omni, Gemini Spark
  20.5.2026, 11:17:24

  The video introduces Google’s latest AI features and products, primarily based on the Gemini ecosystem. Here are the key points:

  1. **Gemini Omni**: A new model that can process text, images, videos, and audio to create and edit multimodal content. It enables video creation and editing through natural language commands. For example, it can create educational videos on complex topics like protein folding or edit existing videos retroactively.

  2. **Gemini 3.5 Flash**: A new model in the Gemini family specifically optimized for coding. It’s faster and more powerful than previous versions and is particularly suited for agent-based coding tasks.

  3. **Anti-Gravity 2.0**: A revamped version of Google’s agent-based development platform. It enables the creation of complex projects, such as an operating system, through collaboration between multiple sub-agents. The platform is now available as a standalone desktop application and offers a wide range of integrations and features.

  4. **Gemini Spark**: A personal AI agent that runs continuously in the background and completes tasks on behalf of the user. It can draft emails, manage appointments, and even handle complex projects like planning a block party. Spark can interact with various tools and synchronize tasks across multiple devices.

  5. **Docs Live**: A new feature that allows users to create and edit documents using their voice. This makes it easier to quickly capture ideas and information without manual typing.

  6. **Redesigned Gemini App**: The Gemini app has been completely redesigned and now offers a more intuitive user interface with enhanced content creation and editing capabilities. New features include Gemini Omni integration for video editing and the “Daily Brief” agent, which provides users with a personalized overview of their tasks and appointments.

  7. **Google AI Pix**: A new image editing app that allows users to precisely edit and create images. It offers features such as removing or altering objects in images and translating text.

  8. **Stitch**: A design tool that enables users to quickly and easily create user interfaces and websites. It offers features like creating UI designs through voice commands and integration with other tools.

  9. **Google Flow**: A platform for creative projects that now offers new features such as simultaneous execution of multiple commands and the creation of custom tools. Google Flow Music allows for music creation through voice commands.

  The video explicitly features Google’s own models and tools such as Gemini Omni, Gemini 3.5 Flash, Anti-Gravity 2.0, Gemini Spark, Docs Live, Google AI Pix, Stitch, and Google Flow. It is better suited for intermediate users who are already familiar with AI tools and want to expand their application possibilities.

Theo – t3․gg (3 new videos)

• This is bad…
  21.5.2026, 09:10:17

  The video covers recent security incidents at GitHub, specifically unauthorized access to internal repositories caused by a compromised VS Code extension. The speaker criticizes GitHub’s lack of security and infrastructure, including frequent downtime and poor leadership. It highlights how attackers gained access through a poisoned VS Code extension distributed via the VS Code Marketplace. The extension had 2.2 million installations and carried a verified publisher badge, underscoring the severity of the incident. While GitHub has taken containment measures, the speaker is skeptical about their sufficiency.

  Another focus is on recurring security problems at npm and GitHub and Microsoft’s inadequate response. It emphasizes that current security measures, such as trusted publishing, are insufficient and could even be part of attacks themselves. The speaker calls for fundamental changes to publishing and update processes to prevent such incidents in the future. The role of third-party tools like Socket and Aikido is also highlighted, as they are better equipped to detect and report such security vulnerabilities.

  Finally, the video stresses Microsoft and GitHub’s responsibility to implement necessary security measures to protect the open-source community and its users. The speaker is frustrated by Microsoft’s lack of response and demands urgent action to close security gaps and ensure the integrity of the software supply chain.

  The video explicitly addresses GitHub, Microsoft, VS Code, npm, and specific tools like Socket and Aikido. It’s geared toward intermediate and advanced users familiar with software security and the technical details of GitHub and npm.

• I’m scared to make this video
  20.5.2026, 03:51:05

  The YouTuber expresses strong criticism of Google, particularly regarding recent developments around the Gemini 3.5 Flash model, the Anti-Gravity CLI, and the treatment of customers like Railway. He begins with a warning that his criticism could jeopardize his career, as Google has previously demonetized his videos and restricted his reach. Despite these risks, he wants to expose the problems he sees with Google’s current products and decisions.

  Key criticisms include:
  1. **Gemini 3.5 Flash Model**: While the model performs well on some benchmarks, it’s extremely inefficient with token usage, making it very expensive. The YouTuber shows examples where the model fails to perform tasks correctly, such as rewriting a simple game, which works flawlessly on other models like GPT-55.
  2. **Anti-Gravity CLI**: The successor to the open Gemini CLI is, according to the YouTuber, heavily buggy and user-unfriendly. Additionally, Google has discontinued support for the open Gemini CLI, replacing it with the closed Anti-Gravity CLI, disappointing the community.
  3. **Customer Treatment**: Google suspended the account of Railway, a customer spending over $2 million monthly, without explanation, causing massive outages. The YouTuber mentions similar past incidents demonstrating Google Cloud’s unreliability.

  The YouTuber emphasizes that despite Google’s resources and talent, internal politics and lack of collaboration prevent it from producing quality products. He stands with former Google employees who attempted to create meaningful solutions and criticizes the decision to end their work in favor of a closed, buggy product.

  The YouTuber explicitly addresses Google’s Gemini 3.5 Flash, Anti-Gravity CLI, and Google Cloud. The video is geared toward intermediate or advanced users, as it covers technical details and benchmarks.

• Why Copilot’s Billing Had To Change
  19.5.2026, 02:25:55

  The video discusses recent changes to GitHub Copilot’s billing model, transitioning from a fixed message limit to a token-based billing system. The author, who uses a free Copilot Plus license, demonstrates how to exploit the old system to incur significant inference costs. He shows how by strategically using Copilot with complex cryptography puzzles and agentic workflows, he drives up Microsoft’s costs. The author argues that the billing model change was necessary because the old system was no longer sustainable and Microsoft didn’t have sufficient compute capacity to meet demand. He emphasizes this isn’t a “rug pull” but a necessary adjustment to keep the program running.

  Final note: The video explicitly addresses GitHub Copilot, Claude Code, Codex, Cursor, OpenAI, and Anthropic. It’s geared toward intermediate and advanced users.

Tim Carambat (1 new video)

• Llama.cpp Just Merged MTP And You Should Be Using It.
  18.5.2026, 17:45:34

  The video covers the introduction of Multi-Token Prediction (MTP) in Llama CPP, a popular tool for running AI models locally. MTP enables up to 25% faster token processing without quality loss by predicting multiple tokens simultaneously. The speaker, Timothy Carbat, explains how MTP works and compares it to speculative sampling (SSD), which requires two models, whereas MTP uses only one model. He shows how to enable MTP in Llama CPP and which models support it, including Deepseek V3 and V4, Neotron 3, Quinn 3.5 and 3.6, and Gemma 4. Carbat demonstrates performance improvements using a benchmark with the Quinn 3.59B model and emphasizes the importance of adjusting the parameter for the number of predicted tokens (n_max). He concludes by noting that such software improvements make local AI usage more efficient and sustainable.

  The video explicitly covers Llama CPP, Deepseek, Neotron, Quinn, and Gemma 4, and is aimed more at intermediate and advanced users.

Unsupervised Learning

No new videos in this period.

WorldofAI (7 New Videos)

• Cursor Composer 2.5 Is REALLY Good & On Par With Opus 4.7 & GPT 5.5? (Fully Tested)
  23.5.2026, 07:07:00

  The video introduces Cursor’s new Composer 2.5 coding model, which is up to 10 times cheaper than top models like Opus 4.7 and GPT 5.5 while delivering nearly comparable performance. The model stands out for its high speed and efficiency, performing well in benchmarks such as Terminal Bench 2.0 and Swaybench Multilingual. Composer 2.5 excels particularly in iteration speed and debugging, though it still lags slightly behind Opus 4.7 in frontend and web design. Built on the open-source Kimik K 2.5 checkpoint, the model shows improvements over earlier versions but has some limitations, such as failure to execute certain actions and insufficient presentation of trade-offs.

  The video demonstrates various examples where Composer 2.5 handles tasks like cloning Mac OS UI, creating landing pages, and generating SVG graphics. It becomes clear that the model works quickly and functionally, though it hasn’t quite reached Opus 4.7 in result quality. Nevertheless, Composer 2.5 is recommended as a worthwhile alternative to more expensive models due to its affordable price and high speed.

  Final Comment: The video explicitly focuses on Cursor’s Composer 2.5 AI model and is better suited for Intermediate and Advanced users.

• Qwen 3.7 Max: NEW Powerful AI Model! Beats Opus 4.6, Gemini 3.1, Deepseek v4! (Fully Tested)
  22.5.2026, 07:04:20

  The video introduces Alibaba’s new flagship model Qwen 3.7 Max, specifically designed for the agentic AI era. The model stands out for its versatility, including advanced coding, debugging, frontend prototyping, complex refactoring, office workflow automation, multi-agent orchestration, and long-term autonomous execution. In terms of performance, Qwen 3.7 Max scores well across various benchmarks like Terminal Bench 2.0 and Swaybench, and is comparable to models such as Opus 4.6 Max and Kimik K 2.6, sometimes even surpassing them. It demonstrates outstanding capabilities in difficult logical reasoning and multilingual tasks. Particularly noteworthy is the model’s ability for long-term planning and execution, enabling it to maintain autonomous workflows over extended periods without losing context. The model is not multimodal and costs $2.50 per 1 million input tokens and $7.50 per 1 million output tokens. It can be accessed through a free chat app or API. The video also showcases the model’s capabilities through examples such as creating a Mac OS clone, frontend development, SVG generation, and 3D scenes. Overall, Qwen 3.7 Max is presented as one of the best Chinese models, comparable to frontier models across many domains.

  The video explicitly focuses on Alibaba’s Qwen 3.7 Max AI model and is better suited for Intermediate and Advanced users.

• Antigravity 2.0 UPDATE: NEW Agentic AI Coding Agent + Gemini Desktop App!
  21.5.2026, 07:15:18

  Summary:

  Google presented several new AI updates at the Google Developer Conference, including the new Gemini 3.5 Flash model and the video model Omni. A central focus was the introduction of Antigravity 2.0, now split into multiple separate apps: a standalone IDE (similar to VS Code) and an agentic chat interface app for autonomous workflows. The split may aim to create a local AI agents app similar to Anthropic’s Co-work or Codex. However, there’s confusion and criticism, particularly regarding reduced usage limits and less intuitive app separation.

  New features in Antigravity 2.0 include dynamic sub-agents that can work in parallel, asynchronous and scheduled tasks, improved project management, and new slash commands like `/goal`, `/drillme`, and `/browser`. There’s also live voice transcription, customizable Skills, JSON hooks, and a new CLI/SDK for advanced workflows. Google AI Studio also received a new agent model called Antigravity Preview0526, running in a remotely hosted Linux environment with the ability to execute code and use tools.

  Google appears to be consolidating its entire AI infrastructure under the Antigravity brand, though this has caused confusion since the separation into different apps is less intuitive. The new Antigravity CLI enables direct use of agents from the terminal.

  Final Comment:
  The video covers Google’s Antigravity 2.0, Gemini 3.5 Flash, Omni, as well as Anthropic’s Co-work and Codex, and is intended for Intermediate to Advanced users.

• Gemini 3.5 Flash: Google’s Most Powerful Model Ever! Beats Opus 4.7 & GPT 5.5? (Fully Tested)
  20.5.2026, 06:43:51

  The video discusses the introduction of Google Gemini 3.5 Flash, a new fast and efficient model unveiled at the Google I/O developer conference. The creator has mixed feelings about it—while technically impressive, it has some drawbacks. The model is faster and stronger in code editing than previous versions, but it’s also more expensive and consumes more tokens. It performs well on complex tasks like planning and understanding large codebases, but costs can be higher compared to other models. The creator tests the model across various areas including frontend design, SVG generation, and 3D world creation, finding it performs very well in these areas. However, there are also weaknesses, such as excessive ambition and high token consumption, which can lead to truncation in large projects. Overall, the creator considers it a solid release from Google, especially for users with Google subscriptions. The video is better suited for Intermediate and Advanced users and explicitly focuses on the Google Gemini 3.5 Flash model.

• Google I/O LEAKED! Gemini Desktop App, Veo 4, Qwen 3.7, Composer 2.5, Mythos Soon, & More! AI NEWS
  19.5.2026, 06:45:31

  The video summarizes the week’s major AI news, focusing on Google, Anthropic, Alibaba, Cursor, and others. Google is about to release new Gemini models, including Gemini 3.5 Flash, which promises high speed and efficiency. There are leaks about new features like a Gemini Desktop App that enables local agent workflows and Google Drive integration. Google may also introduce the Veo 4 model, a new video generation model. Anthropic is reportedly preparing the launch of Claude Mythos, while Alibaba has released Qwen 3.7, a new multimodal model that competes with top models like GPT 5.5 and Gemini 3.1 Pro. Cursor has released Composer 2.5, which testing shows can match Opus 4.7 while being more cost-effective. Open Design introduced a new feature for Codex integration, simplifying UI generation. HRM text, an ultra-lightweight model with only 1 billion parameters, shows promising results with minimal training effort. Boston Dynamics showcased a video of their humanoid robot Atlas carrying and manipulating a refrigerator, demonstrating advances in combining physical control with AI.

  The video explicitly covers Google (Gemini, Veo 4), Anthropic (Claude Mythos), Alibaba (Qwen 3.7), Cursor (Composer 2.5), open-source tools (Open Design, HRM text), and Boston Dynamics (Atlas). It’s intended for Intermediate and Advanced users.

• Hermes Agent Foundation Update: Real-Time Agents, DeepSeek V4 FREE, Native Windows Support, & More!
  18.5.2026, 06:16:23

  The video covers the latest version 0.14.0 of Hermes, an open-source AI agent developed by Nous Research. The key updates include:

  1. Local Proxy Feature: Enables the use of a single subscription (e.g., Claude, ChatGPT, Grok) across different tools and agents without requiring separate API keys.
  2. Windows Support: Native Windows support in beta phase, simplifying installation and usage.
  3. Performance Improvements: Faster startup times, optimized browser automation, and enhanced caching mechanisms.
  4. Video Generation: New capability for autonomous video creation within workflows.
  5. Supergrok Integration: Direct support for Grok’s Supergrok subscription, including access to Grok 4.3, text-to-speech, image and video generation, and X-Search.
  6. Handoff System: Enables seamless switching between models or personas without losing context.
  7. Additional Improvements: Integrated X-Search, vision model support, Discord history backup, LSP semantic diagnostics, and more.

  The video is better suited for Intermediate to Advanced users and explicitly focuses on open-source tools like Hermes Agent, N8N, and Grok.

• Stop Paying $200/Month for Claude Code! Here’s a FREE Option!
  17.5.2026, 05:59:20

  The video introduces Mistral Vibe, an open-source and partially free tool for AI-powered development, positioned as an alternative to Claude Code and Cloud Code. Mistral Vibe is a terminal-based AI coding agent capable of writing, testing, refactoring, and even deploying code. It supports asynchronous tasks, integrates with tools like GitHub, Jira, and Slack, and offers customizable agent workflows to automate long-term tasks. Particular highlights include capabilities for documenting shell aliases, creating sub-agents for specific tasks like PR reviews and test generation, and using slash commands for repeated tasks. The tool is free and open-source, with the option to use your own API keys. For heavy usage, there are paid plans like Lay Chat Pro ($14.99/month) and Late Chat Team ($24.99/seat/month), with students receiving a 50% discount. Installation is simple via bash or Python method, with additional integrations available for VS Code and JetBrains IDEs.

  The video demonstrates Mistral Vibe’s installation and basic usage, including creating a frontend landing page and generating tests for a codebase. It emphasizes that Mistral Vibe enables efficient automation through asynchronous agents and parallel execution. The conclusion recommends Mistral Vibe as a cost-effective and powerful alternative to existing tools, especially for developers seeking terminal-based automation.

  Final Comment: The video focuses on Mistral Vibe (open-source) and is better suited for Intermediate and Advanced users.

---

Automatically generated from the latest YouTube videos of the curated channel selection. For feedback, suggestions, or to unsubscribe: simply reply to this email.