Learnetto AI directory

Find the best AI educators, resources, and learning paths.

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.

183 educators 12 learning paths 10 agent tools 41 AI answers 625 resources

Interactive lab · AI research delegation

See where parallel AI agents actually save time

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

Answers to common AI learning questions

Short, crawlable answers connected to fuller guides, educators, docs, courses, and videos.

The 13 best AI SEO tools in 2026

Do I need one AI SEO tool or a stack?

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

Are AI-visibility tools the same as AI writing tools?

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

How should I compare the real cost?

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...

Best AI agent courses

What is the best AI agent course for developers?

AI Agents in LangGraph is the best first pick for developers who want explicit state, tool use, and workflow control. Add a broader agents course after that if you want to compa...

Recently added

Daily new AI learning picks

New directory additions across educator videos, newsletters, social feeds, official model docs, agents, coding tools, and model-selection references. Today's selection: Oct 10, 2026.

Choose how to scan the same daily picks: keep the current layout, mix formats, or read it like a feed.

Technical article FS Data Lab

How to Cost Your AI-Powered Filters

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.

ai-sql inference cost filter ordering
Connected-finance safety guide OpenAI

ChatGPT Finances privacy and accuracy 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.

chatgpt personal finance connected accounts
Desktop agent safety guide GitHub

GitHub Copilot computer use explained

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.

github copilot computer use desktop agents
AI-assisted science explainer Anthropic

Claude and the ART enzyme system explained

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.

claude ai agents ai for science
Frontier coding model launch explainer SpaceXAI

Grok 4.7 explained

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.

grok 4.7 coding agents long-running agents
Multi-model routing launch explainer Unbiased

Union Alpha revealed as Pareto 26.9

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.

pareto 26.9 union alpha model routing
Omnimodal model launch explainer Qwen

Qwen3.8-Omni-Flash explained

Qwen3.8-Omni-Flash launched September 18, 2026 for long audio and video analysis, text answers, web search, and tool-calling workflows.

qwen3.8 omnimodal models audio
System One Model launch TypeSafe AI

Introducing System One Models & Jev

Jev launched on September 15, 2026 as TypeSafe AI's first System One model: a non-chat model that turns application state into typed decisions and probabilities for software workflows.

jev system one models rlcd
Managed agent API launch and guide OpenAI

Introducing the Agents API

You want OpenAI's September 10, 2026 launch guide for building long-running cloud agents with the managed Codex harness, context compaction, tool search, multi-agent delegation, and your choice of hosted or self-managed sandbox.

openai agents codex

Technical article · FS Data Lab

How to Cost Your AI-Powered Filters

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.

ai-sql inference cost filter ordering roofline model

Connected-finance safety guide · OpenAI

ChatGPT Finances privacy and accuracy 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.

chatgpt personal finance connected accounts plaid

Desktop agent safety guide · GitHub

GitHub Copilot computer use explained

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.

github copilot computer use desktop agents copilot cli

AI-assisted science explainer · Anthropic

Claude and the ART enzyme system explained

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.

claude ai agents ai for science biology

Frontier coding model launch explainer · SpaceXAI

Grok 4.7 explained

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.

grok 4.7 coding agents long-running agents model selection

Multi-model routing launch explainer · Unbiased

Union Alpha revealed as Pareto 26.9

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.

pareto 26.9 union alpha model routing ensembles

Omnimodal model launch explainer · Qwen

Qwen3.8-Omni-Flash explained

Qwen3.8-Omni-Flash launched September 18, 2026 for long audio and video analysis, text answers, web search, and tool-calling workflows.

qwen3.8 omnimodal models audio video

System One Model launch · TypeSafe AI

Introducing System One Models & Jev

Jev launched on September 15, 2026 as TypeSafe AI's first System One model: a non-chat model that turns application state into typed decisions and probabilities for software workflows.

jev system one models rlcd structured decisions
F

FS Data Lab added technical article

How to Cost Your AI-Powered Filters

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.

ai-sql inference cost filter ordering roofline model
O

OpenAI added connected-finance safety guide

ChatGPT Finances privacy and accuracy 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.

chatgpt personal finance connected accounts plaid
G

GitHub added desktop agent safety guide

GitHub Copilot computer use explained

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.

github copilot computer use desktop agents copilot cli
A

Anthropic added ai-assisted science explainer

Claude and the ART enzyme system explained

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.

claude ai agents ai for science biology
VID

OpenAI posted a video pick

2026 · Codex · production monitoring

Production Monitoring with Codex: Grafana, Kubernetes, & Security

Use this October 8 OpenAI demo to design a bounded assistant for incident investigation. It joins telemetry, release context, code, a proposed patch, human approval, and post-change checks across three short scenarios.

S

SpaceXAI added frontier coding model launch explainer

Grok 4.7 explained

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.

grok 4.7 coding agents long-running agents model selection
U

Unbiased added multi-model routing launch explainer

Union Alpha revealed as Pareto 26.9

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.

pareto 26.9 union alpha model routing ensembles
Q

Qwen added omnimodal model launch explainer

Qwen3.8-Omni-Flash explained

Qwen3.8-Omni-Flash launched September 18, 2026 for long audio and video analysis, text answers, web search, and tool-calling workflows.

qwen3.8 omnimodal models audio video
T

TypeSafe AI added system one model launch

Introducing System One Models & Jev

Jev launched on September 15, 2026 as TypeSafe AI's first System One model: a non-chat model that turns application state into typed decisions and probabilities for software workflows.

jev system one models rlcd structured decisions

AI video library

Watch first

Current picks across coding agents, MCP, model selection, RAG, evals, and production AI.

From 15% to 90% GPU Utilization: Fix the Data Pipeline, Not the Model video thumbnail ►

From 15% to 90% GPU Utilization: Fix the Data Pipeline, Not the Model

AI Engineer · 2026, multimodal training, GPU utilization

Small Models, Big Results: Training a Finance Agent for Under $500 — Charles Dickens, Snorkel AI video thumbnail ►

Small Models, Big Results: Training a Finance Agent for Under $500 — Charles Dickens, Snorkel AI

AI Engineer · 2026, reinforcement learning, small models

Why Your Company Needs a Context Graph (and How to Build It) — Gil Feig, Merge video thumbnail ►

Why Your Company Needs a Context Graph (and How to Build It) — Gil Feig, Merge

AI Engineer · 2026, context engineering, enterprise data

Designing CLIs for Agents, Not Humans — Pedro Lopez, Airbyte video thumbnail ►

Designing CLIs for Agents, Not Humans — Pedro Lopez, Airbyte

AI Engineer · 2026, CLI design, MCP

Why 80% Reliability Isn't Good Enough — Felipe Blanes, Amazon AGI Lab video thumbnail ►

Why 80% Reliability Isn't Good Enough — Felipe Blanes, Amazon AGI Lab

AI Engineer · 2026, agent evaluation, customer feedback

Production Monitoring with Codex: Grafana, Kubernetes, & Security video thumbnail ►

Production Monitoring with Codex: Grafana, Kubernetes, & Security

OpenAI · 2026, Codex, production monitoring

New directory

AI skills, agent harnesses, and worker tools

Find reusable skill registries, local agent harnesses, and AI worker products before choosing what to learn or buy.

AI coworker

Viktor

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.

See in AI skills directory

AI assistant builder

Lindy

Lindy · AI executive assistant

Use this when the job is business admin across apps rather than custom coding or local agent infrastructure.

See in AI skills directory

Skill marketplace

ClawHub

OpenClaw · Registry

Use this when you need a public registry for OpenClaw skills and plugins rather than hand-copying skill folders.

See in AI skills directory

Agent orchestration

Mission Control

Builderz Labs · Open-source dashboard

Use this when the hard part is seeing, assigning, and coordinating agent work rather than writing another prompt.

See in AI skills directory

AI worker platform

Mission Control AI

Mission Control AI · Preconfigured AI workers

Use this when you want role-specific AI workers with SOPs, integrations, and governance policies already built in.

See in AI skills directory

Self-improving agent

Hermes 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.

See in AI skills directory

Educators to start with

Sorted for range: founders, product teams, developers, evals, model internals, and production systems.

Educator Best for Skills Start with
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.
Engineers, ML practitioners AI engineering, Systems, Production ML Use the book page and related essays as a production engineering path.
Beginners, educators, teams Prompting, AI literacy, Security Start at the fundamentals section, then move to prompt hacking/security.

Choose by skill

Use these as quick routes into the directory.

Frontier models and model selection

Useful for: Builders choosing between Claude, GPT, Gemini, Llama, Mistral, Cohere, DeepSeek, Qwen, Grok, Perplexity, and hosted open models

Learn: When to use Claude or GPT-class reasoning models for complex coding, analysis, and long-horizon agent work; How Gemini, Llama, Mistral, Cohere, DeepSeek, Qwen, Grok, and Perplexity differ by modality, openness, retrieval, coding, and price; Context windows, output limits, latency, pricing, tool support, and eval-based routing; How to migrate safely when frontier model versions change

Resources: Anthropic , OpenAI , Google AI for Developers , Meta Llama , Mistral AI , Cohere , DeepSeek , Qwen , xAI , Perplexity , Together AI , OpenRouter , Simon Willison

Resources worth opening

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.
Claude Code skills
Anthropic
Guide Intermediate You want Anthropic's official guide for packaging reusable Claude Code skills instead of leaving long instructions inline in every session.
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.
Codex for Builders
OpenAI
Official training Intermediate You want OpenAI's practical Codex overview for real development workflows, including the CLI, IDE, GitHub, GPT-5-Codex, MCP, and code-review patterns.
OpenAI Tool search
OpenAI
Guide Intermediate to advanced Your agent has a large function, namespace, or MCP catalog and you want GPT-5.4 or later models to load only the tool definitions needed at runtime, reducing context use while preserving prompt-cache efficiency.