Learnetto AI directory
A compact directory for people who want practical AI skills and up-to-date official docs: prompting, automation, coding agents, MCP, model selection, AI product work, RAG, evals, model internals, and production AI engineering.
Recently added
New directory additions across educator videos, newsletters, social feeds, official model docs, agents, coding tools, and model-selection references. Refreshed Jun 18, 2026.
Choose how to scan the same daily picks: keep the current layout, mix formats, or read it like a feed.
You want a current business-friendly example of treating AI agents like onboarded teammates with roles, context, and review.
You want a non-engineer explanation of why Claude Code-style tools matter for everyday professional work.
You want actionable Claude and AI workflow tutorials for non-technical operators without a general AI news feed.
You want a concrete list of reusable Claude meta-skills for writing, fact-checking, file organization, decisions, and prompt building.
You want a concise technical briefing on why code, traces, tests, and harnesses matter for real agent systems.
You want a weekly agent-building show that mixes current AI news with technical discussion of agent infrastructure.
Use this for longer-form weekly AI context when you want model, agent, product, and market changes explained together.
Use this for non-technical Claude Code, Claude Cowork, and personal operating-system walkthroughs.
Use this as a daily AI briefing when you want news paired with practical ways to apply new AI tools at work.
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Video · Silicon Valley Girl
Watch this first when you want current AI operator examples for moving from prompts to repeatable team workflows.
Beehiiv post · Allie K. Miller
You want a current business-friendly example of treating AI agents like onboarded teammates with roles, context, and review.
Beehiiv post · Allie K. Miller
You want a non-engineer explanation of why Claude Code-style tools matter for everyday professional work.
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Video · Claude
Use this for Anthropic's current Claude Code direction, agent workflow framing, and developer tooling roadmap.
Substack newsletter · Pietro Montaldo
You want actionable Claude and AI workflow tutorials for non-technical operators without a general AI news feed.
Substack guide · Pietro Montaldo
You want a concrete list of reusable Claude meta-skills for writing, fact-checking, file organization, decisions, and prompt building.
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Video · Fireship
Use this as a fast technical recap of Google I/O 2026 and the Gemini-era product/model changes worth tracking.
Beehiiv post · Sumanth P
You want a concise technical briefing on why code, traces, tests, and harnesses matter for real agent systems.
YouTube and X livestream · Mastra
You want a weekly agent-building show that mixes current AI news with technical discussion of agent infrastructure.
YouTube channel · This Week in AI
Use this for longer-form weekly AI context when you want model, agent, product, and market changes explained together.
YouTube channel · The Happy Operator
Use this for non-technical Claude Code, Claude Cowork, and personal operating-system walkthroughs.
Silicon Valley Girl posted a video pick
2026 · ai adoption · business workflows
Watch this first when you want current AI operator examples for moving from prompts to repeatable team workflows.
Allie K. Miller added beehiiv post
You want a current business-friendly example of treating AI agents like onboarded teammates with roles, context, and review.
Allie K. Miller added beehiiv post
You want a non-engineer explanation of why Claude Code-style tools matter for everyday professional work.
Claude posted a video pick
2026 · claude code · coding agents
Use this for Anthropic's current Claude Code direction, agent workflow framing, and developer tooling roadmap.
Pietro Montaldo added substack newsletter
You want actionable Claude and AI workflow tutorials for non-technical operators without a general AI news feed.
Pietro Montaldo added substack guide
You want a concrete list of reusable Claude meta-skills for writing, fact-checking, file organization, decisions, and prompt building.
Fireship posted a video pick
2026 · gemini · frontier models
Use this as a fast technical recap of Google I/O 2026 and the Gemini-era product/model changes worth tracking.
Sumanth P added beehiiv post
You want a concise technical briefing on why code, traces, tests, and harnesses matter for real agent systems.
Mastra added youtube and x livestream
You want a weekly agent-building show that mixes current AI news with technical discussion of agent infrastructure.
This Week in AI added youtube channel
Use this for longer-form weekly AI context when you want model, agent, product, and market changes explained together.
The Happy Operator added youtube channel
Use this for non-technical Claude Code, Claude Cowork, and personal operating-system walkthroughs.
Today's rotation
Current picks across coding agents, MCP, model selection, RAG, evals, and production AI.
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Silicon Valley Girl · 2026, ai adoption, business workflows
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Claude · 2026, claude code, coding agents
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Fireship · 2026, gemini, frontier models
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Zen van Riel · 2026, agentic engineering, claude code
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Peter Yang · 2026, ai agents, claude code
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Teacher's Tech · 2026, claude code, ai agents
New directory
Find reusable skill registries, local agent harnesses, and AI worker products before choosing what to learn or buy.
Skill system
OpenClaw · Official docs
Use this to understand the OpenClaw skill format: markdown instruction files in directories with SKILL.md frontmatter and tool-use guidance.
Skill marketplace
OpenClaw · Registry
Use this when you need a public registry for OpenClaw skills and plugins rather than hand-copying skill folders.
Agent harness
OpenClaw · Open-source agent harness
Use this when you want an agent runtime you can shape with local skills, plugins, and workspace-level behavior.
Self-improving agent
Nous Research · Open-source agent
Use this when persistent memory, skill creation from completed tasks, and remote agent operation matter more than a simple chat UI.
AI assistant builder
Lindy · AI executive assistant
Use this when the job is business admin across apps rather than custom coding or local agent infrastructure.
AI coworker
Viktor · Slack and Teams AI employee
Use this when the adoption surface should be chat-native and team-facing rather than a separate automation builder.
Sorted for range: founders, product teams, developers, evals, model internals, and production systems.
| Educator | Best for | Skills | Start with |
|---|---|---|---|
| Indie founders, product builders | Founder workflows, Product ops, Automation | Read the public notes and examples before deciding whether the paid material matches your business. | |
| Founders, service business owners | Founder workflows, Systems, Automation | Look for workflow breakdowns and implementation examples. | |
| Product managers, founders | Product strategy, Writing, AI adoption | Review the Maven syllabus and compare it to your current product workflow. | |
| Product teams, founders | Product, Growth, Team adoption | Browse the How I AI interviews and copy the workflows that match your role. | |
| Knowledge workers, educators, leaders | AI literacy, Workplace adoption, Strategy | Read recent essays on using AI as a collaborator and on organizational adoption. | |
| Developers, AI engineers | AI engineering, Agents, Developer tools | Watch AI Engineer talks for production patterns and tool choices. | |
| Everyone from beginners to builders | Prompting, Agents, RAG, ML foundations | Start with ChatGPT Prompt Engineering for Developers, then pick a RAG or agents course. | |
| Coders learning deep learning | Deep learning, PyTorch, Model training | Practical Deep Learning for Coders, lesson 1. | |
| Developers, data scientists | Practical ML, Ethics, Education | Use fast.ai essays and course material alongside hands-on notebooks. | |
| Programmers who want model internals | Neural networks, Backprop, LLM internals | Watch micrograd, then makemore, then the GPT video. | |
| Developers, technical generalists | LLM tools, Prompting, AI safety, Local models, Model selection | Read the recent model-roundup posts, then try the llm command-line tool with two or three different providers. | |
| Developers building LLM apps | Structured outputs, Extraction, RAG | Try the Instructor examples for extraction and validation. |
Use these as quick routes into the directory.
Useful for: Everyone
Learn: What LLMs can and cannot do; Tokens, context windows, hallucinations; Privacy and data handling
Resources: DeepLearning.AI , Learn Prompting , Ethan Mollick
Useful for: Writers, operators, PMs, founders
Learn: Clear task framing; Examples and constraints; Editing, synthesis, and critique loops
Resources: Learn Prompting , DAIR.AI , Peter Yang
Useful for: Founders, operations teams, developers
Learn: Trigger-based workflows; Tool calling; Agent failure modes; Human review points
Resources: Brian Casel , Josh Pigford , AI Engineer
Useful for: PMs, designers, founders
Learn: AI UX patterns; Use-case selection; Prototyping; Measuring quality
Resources: Peter Yang , Lenny Rachitsky , Shreya Shankar
Useful for: Software developers
Learn: Codebase navigation; Test generation; Refactoring; Reviewing AI output
Resources: Simon Willison , Addy Osmani , Matt Pocock , AI Engineer
Useful for: Developers using coding agents and tool-connected workflows
Learn: How to structure instructions, memories, and skills; When to use MCP servers versus retrieval or file search; Subagents, hooks, and tool boundaries; How to keep agent context small, relevant, and testable
Resources: Anthropic , Hugging Face , OpenAI , Matt Pocock , Simon Willison
Useful for: Developers building AI apps
Learn: Chunking and retrieval; Structured extraction; Reranking; Grounded answers
Resources: Jason Liu , Hamel Husain , Eugene Yan
Useful for: AI product teams
Learn: Test sets; Human review; Regression checks; Quality metrics
Resources: Hamel Husain , Shreya Shankar , Chip Huyen
A rotating mix of official docs, hands-on guides, model catalogs, and practical AI engineering resources.
| Resource | Type | Level | Use when |
|---|---|---|---|
|
OpenAI model guide
OpenAI
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Model docs | Beginner to advanced | You need to choose between GPT-5.5, GPT-5.5 Pro, GPT-5.4 mini, GPT-5.4 nano, reasoning levels, tool support, and cost-sensitive API paths. |
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Claude Code best practices
Anthropic
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Engineering guide | Intermediate to advanced | You want Anthropic's own recommendations for scaling Claude Code across larger codebases, parallel sessions, and stronger context discipline. |
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Gemini coding agent setup
Google AI for Developers
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Guide | Intermediate | You want Google's official setup path for Gemini-driven coding-agent workflows, Gemini Docs MCP, and skills rather than generic prompt advice. |
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Hugging Face Context Course
Hugging Face
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Free course | Intermediate | You want a focused course on context engineering for code agents, including skills, subagents, hooks, and MCP. |
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Claude choosing a model
Anthropic
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Guide | Intermediate | You need Anthropic's current guidance on balancing capability, speed, and cost before changing Claude models. |
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A Complete Guide To AGENTS.md
Matt Pocock
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Guide | Intermediate | You want to write project instructions that help coding agents understand commands, conventions, architecture, and working boundaries. |
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Gemini Deep Research Agent
Google AI for Developers
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Guide | Intermediate to advanced | You want the latest official Google docs for long-running research agents, cited reports, background execution, and MCP-aware investigation workflows. |
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Model Context Protocol Tutorial
Matt Pocock
|
Free tutorial | Intermediate | You want to understand MCP and build TypeScript MCP servers over stdio or HTTP, connect Claude Code to tools, use MCP prompts, and package servers for distribution. |
