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.
Interactive lab · AI research delegation
Build a research workflow, expose its dependency bottlenecks, and compare human-only, sequential-agent, and parallel-agent plans on time, cost, and clean-run probability.
AI Q&A
Short, crawlable answers connected to fuller guides, educators, docs, courses, and videos.
Best AI resources for model release notes and migrations
Watch the release notes, keep evals for your core workflows, compare the replacement model on your own prompts, and only then update the default model or alias. Treat migrations...
The 13 best AI SEO tools in 2026
Evatype is the strongest fit when the repeated failure is getting researched, approved website pages published. Surfer or Frase fit a team that already has writers, while Otterl...
The 13 best AI SEO tools in 2026
Buy one product first for the most expensive bottleneck. Add a second only when you can name the distinct job it performs—for example, Ahrefs for research plus Evatype for appro...
The 13 best AI SEO tools in 2026
No. Visibility products observe prompts, mentions, citations, and competitors. Writing and publishing products create or improve pages. Some vendors cross both categories, but t...
The 13 best AI SEO tools in 2026
No. A proprietary score is useful only if its recommendations improve the page for the intended reader. Compare factual corrections, editing time, CMS output, and results after ...
The 13 best AI SEO tools in 2026
Count the subscription, required tier upgrades, add-ons, setup, editorial labor, workflow maintenance, and unused allowances. Divide by accepted pages or decisions acted upon—no...
Recently added
New directory additions across educator videos, newsletters, social feeds, official model docs, agents, coding tools, and model-selection references. Today's selection: Oct 8, 2026.
Choose how to scan the same daily picks: keep the current layout, mix formats, or read it like a feed.
FS Data Lab published this guide on October 1, 2026. Use it when you want a rigorous way to estimate GPU latency and inference cost for AI-powered SQL filters, compare filter orderings, and understand how compute, memory bandwidth, selectivity, batching, and KV-cache reuse affect a query plan.
OpenAI announced on October 2, 2026 that ChatGPT Finances is rolling out to Free and Go users in the United States. Use this guide to understand the connected-account workflow, check the source data behind answers, and review privacy controls before linking an account.
GitHub released Copilot computer use in public preview on October 1, 2026. Use this guide to decide when visual desktop control is appropriate, enable it deliberately, and test its permission and stop controls before real work.
Fireworks released Ember-1 on September 23, 2026 as a Kimi K3-based model trained to use fewer reasoning tokens. Use this explainer to evaluate the quality, cost, latency, and context-growth claims on your own agent workload.
Google announced API Gateway MCP support on September 24, 2026. Use this explainer to assess the request flow, security boundary, preview limits, and a safe first rollout.
Anthropic reported ART on September 23, 2026. Use this explainer to separate what its agents found, what the lab confirmed, and what remains a hypothesis.
SpaceXAI released Grok 4.7 on September 21, 2026 for coding, agentic tasks, and knowledge work. Use this guide to compare its task reliability and total cost with your current model.
Union Alpha was revealed as Unbiased's Pareto 26.9 on September 17, 2026: a hosted system that routes work across several models and returns one checked answer.
Qwen3.8-Omni-Flash launched September 18, 2026 for long audio and video analysis, text answers, web search, and tool-calling workflows.
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Video · The Stack
Use this October 4 technical explainer to decide whether IQuest-Q1 belongs in a local coding-agent trial. It separates active-parameter claims from storage and memory needs, and it treats the publisher's benchmarks as evidence to test rather than a purchase verdict.
Technical article · FS Data Lab
FS Data Lab published this guide on October 1, 2026. Use it when you want a rigorous way to estimate GPU latency and inference cost for AI-powered SQL filters, compare filter orderings, and understand how compute, memory bandwidth, selectivity, batching, and KV-cache reuse affect a query plan.
Connected-finance safety guide · OpenAI
OpenAI announced on October 2, 2026 that ChatGPT Finances is rolling out to Free and Go users in the United States. Use this guide to understand the connected-account workflow, check the source data behind answers, and review privacy controls before linking an account.
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Video · Tech With Tim
Use this October 4 hands-on tutorial to understand the code between a language model and a working agent. It builds tool calls, a multi-step loop, MCP connections, file-backed memory, and model switching in plain Python without an agent framework.
Desktop agent safety guide · GitHub
GitHub released Copilot computer use in public preview on October 1, 2026. Use this guide to decide when visual desktop control is appropriate, enable it deliberately, and test its permission and stop controls before real work.
Reasoning-efficient coding model explainer · Fireworks AI
Fireworks released Ember-1 on September 23, 2026 as a Kimi K3-based model trained to use fewer reasoning tokens. Use this explainer to evaluate the quality, cost, latency, and context-growth claims on your own agent workload.
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Video · Peter H. Diamandis
Use this October 3 expert panel to compare views on recursive self-improvement, enterprise open-source adoption, benchmark jumps, and model-cost tradeoffs. Treat the forecasts as speaker opinions rather than established outcomes.
MCP gateway launch explainer · Google Cloud
Google announced API Gateway MCP support on September 24, 2026. Use this explainer to assess the request flow, security boundary, preview limits, and a safe first rollout.
AI-assisted science explainer · Anthropic
Anthropic reported ART on September 23, 2026. Use this explainer to separate what its agents found, what the lab confirmed, and what remains a hypothesis.
Frontier coding model launch explainer · SpaceXAI
SpaceXAI released Grok 4.7 on September 21, 2026 for coding, agentic tasks, and knowledge work. Use this guide to compare its task reliability and total cost with your current model.
Multi-model routing launch explainer · Unbiased
Union Alpha was revealed as Unbiased's Pareto 26.9 on September 17, 2026: a hosted system that routes work across several models and returns one checked answer.
The Stack posted a video pick
2026 · iquest-q1 · local models
Use this October 4 technical explainer to decide whether IQuest-Q1 belongs in a local coding-agent trial. It separates active-parameter claims from storage and memory needs, and it treats the publisher's benchmarks as evidence to test rather than a purchase verdict.
FS Data Lab added technical article
FS Data Lab published this guide on October 1, 2026. Use it when you want a rigorous way to estimate GPU latency and inference cost for AI-powered SQL filters, compare filter orderings, and understand how compute, memory bandwidth, selectivity, batching, and KV-cache reuse affect a query plan.
OpenAI added connected-finance safety guide
OpenAI announced on October 2, 2026 that ChatGPT Finances is rolling out to Free and Go users in the United States. Use this guide to understand the connected-account workflow, check the source data behind answers, and review privacy controls before linking an account.
Tech With Tim posted a video pick
2026 · Python · agent harnesses
Use this October 4 hands-on tutorial to understand the code between a language model and a working agent. It builds tool calls, a multi-step loop, MCP connections, file-backed memory, and model switching in plain Python without an agent framework.
GitHub added desktop agent safety guide
GitHub released Copilot computer use in public preview on October 1, 2026. Use this guide to decide when visual desktop control is appropriate, enable it deliberately, and test its permission and stop controls before real work.
Fireworks AI added reasoning-efficient coding model explainer
Fireworks released Ember-1 on September 23, 2026 as a Kimi K3-based model trained to use fewer reasoning tokens. Use this explainer to evaluate the quality, cost, latency, and context-growth claims on your own agent workload.
Peter H. Diamandis posted a video pick
2026 · recursive self-improvement · claude sonnet 5.5
Use this October 3 expert panel to compare views on recursive self-improvement, enterprise open-source adoption, benchmark jumps, and model-cost tradeoffs. Treat the forecasts as speaker opinions rather than established outcomes.
Google Cloud added mcp gateway launch explainer
Google announced API Gateway MCP support on September 24, 2026. Use this explainer to assess the request flow, security boundary, preview limits, and a safe first rollout.
Anthropic added ai-assisted science explainer
Anthropic reported ART on September 23, 2026. Use this explainer to separate what its agents found, what the lab confirmed, and what remains a hypothesis.
SpaceXAI added frontier coding model launch explainer
SpaceXAI released Grok 4.7 on September 21, 2026 for coding, agentic tasks, and knowledge work. Use this guide to compare its task reliability and total cost with your current model.
Unbiased added multi-model routing launch explainer
Union Alpha was revealed as Unbiased's Pareto 26.9 on September 17, 2026: a hosted system that routes work across several models and returns one checked answer.
AI video library
Current picks across coding agents, MCP, model selection, RAG, evals, and production AI.
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OpenAI · 2026, code review, coding agents
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Duncan Rogoff | Learn Claude Code · 2026, claude code, agent evaluation
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Kurzgesagt – In a Nutshell · 2026, ai safety, agent security
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The Stack · 2026, iquest-q1, local models
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Tech With Tim · 2026, Python, agent harnesses
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Peter H. Diamandis · 2026, recursive self-improvement, claude sonnet 5.5
New directory
Find reusable skill registries, local agent harnesses, and AI worker products before choosing what to learn or buy.
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.
Workflow skill catalog
Matt Pocock / AI Hero · Skill catalog
Use this when you want opinionated coding-agent workflows instead of generic prompt snippets.
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.
Skill marketplace
OpenClaw · Registry
Use this when you need a public registry for OpenClaw skills and plugins rather than hand-copying skill folders.
Agent orchestration
Builderz Labs · Open-source dashboard
Use this when the hard part is seeing, assigning, and coordinating agent work rather than writing another prompt.
AI worker platform
Mission Control AI · Preconfigured AI workers
Use this when you want role-specific AI workers with SOPs, integrations, and governance policies already built in.
Sorted for range: founders, product teams, developers, evals, model internals, and production systems.
| Educator | Best for | Skills | Start with |
|---|---|---|---|
| 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. | |
| Builders shipping LLM systems | Evals, RAG, LLM product quality | Read the evals guide and build a small test set for your own app. | |
| Engineers, PMs, AI product teams | Evals, LLM reliability, Product quality | Review the course outcomes and pair it with a real feature you can evaluate. |
Use these as quick routes into the directory.
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
Useful for: Engineers who want deeper understanding
Learn: Neural nets from scratch; Transformers; Training loops; Fine-tuning basics
Resources: Andrej Karpathy , Sebastian Raschka , Jay Alammar
Useful for: Engineering teams
Learn: Observability; Cost and latency; Deployment; Data pipelines
Resources: Full Stack Deep Learning , Chip Huyen , Eugene Yan
A rotating mix of official docs, hands-on guides, model catalogs, and practical AI engineering resources.
| Resource | Type | Level | Use when |
|---|---|---|---|
|
How to Cost Your AI-Powered Filters
FS Data Lab
|
Technical article | Advanced | FS Data Lab published this guide on October 1, 2026. Use it when you want a rigorous way to estimate GPU latency and inference cost for AI-powered SQL filters, compare filter orderings, and understand how compute, memory bandwidth, selectivity, batching, and KV-cache reuse affect a query plan. |
|
OpenAI model guide
OpenAI
|
Model docs | Beginner to advanced | You need to choose between current GPT-5.6 variants, smaller GPT-5.4 variants, reasoning levels, tool support, and cost-sensitive API paths, including the current default starting points of GPT-5.6 Sol, Terra, and Luna. |
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Claude Code skills
Anthropic
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Guide | Intermediate | You want Anthropic's official guide for packaging reusable Claude Code skills instead of leaving long instructions inline in every session. |
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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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Grok 4.7 explained
SpaceXAI
|
Frontier coding model launch explainer | Intermediate to advanced | SpaceXAI released Grok 4.7 on September 21, 2026 for coding, agentic tasks, and knowledge work. Use this guide to compare its task reliability and total cost with your current model. |
|
Gemini Deep Research Agent
Google AI for Developers
|
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. |
|
OpenRouter MCP Server
OpenRouter
|
MCP guide | Intermediate | You want OpenRouter's official MCP path for pulling live models, prices, rankings, docs, and test calls into Codex, Claude Code, or another coding assistant while you compare providers. |
|
Designing the hf CLI for agents
Hugging Face
|
Agent tooling and evaluation guide | Intermediate | You want a measured guide to agent-friendly CLI design, including structured output, retry-safe commands, independent grading, and benchmarks showing where higher-level tools reduce calls and token use. |
