Learn AI and LLMs from scratch using free resources

Learn Agentic AI using Dapr Agentic Cloud Ascent (DACA) Design Pattern and Agent-Native Cloud Technologies: OpenAI Agents SDK, Memory, MCP, A2A, Knowledge Graphs, Dapr, Rancher Desktop, and Kubernetes.

Real-world AI workflows for creators.

[COLM'26] SkillLearnBench is the first benchmark for evaluating continual learning methods that automatically generate agent skills.

Evidence-based learning engine — first-principles curricula, free-recall verification with receipts, FSRS-scheduled memory, and explorable artifacts. Learn anything; keep it.

AutoSkill: Experience-Driven Lifelong Learning via Skill Self-Evolution

A selective learning and memory substrate for agentic systems — typed, revisable, decayable memory with competence learning and trust-aware retrieval.

A practical framework for AI-Assisted Research in Mathematics and Machine Learning

self-healing and self-learning loop for coding agents

SQL transactions learning tool (AI ready)

The definitive OpenAI, Claude, MCP, Harness, Evals, and Production Agent Systems learning roadmap.

BlenderLore: Learning 3D Coding from Internet Tutorial Videos.

Memory that learns what works.

Simple standalone MCP server giving Claude the ability to remember your conversations and learn from them over time.

The first AI plugin that speaks first. Code-enforced learning + active forgetting + PAC (Proactive Accountability Challenge). Works with Claude Code, Gemini CLI, Hermes, OpenClaw.

Full computer-use for AI agents. Self-learning workflows. Native macOS. No screenshots required.

A universal, industry-neutral taxonomy of cognitive core skills (perception, memory, reasoning, planning, action, verification, learning, governance) for LLMs, SLMs, AI agents, and world models — with schemas, 159 skill cards, benchmarks, and CI.

A collection of notes on Data Science

memX: self-learning, self-maintaining memory plugin for AI agents; native support for claude code, codex, and openclaw

Co-creation infrastructure for humans and code agents — visual environment, skills, continuous learning, and distribution.

Solid Tumor Associative Modeling in Pathology

Toward Skill-Native LLMs: Skill Entropy for Benchmarking and Training Long-Horizon Reasoning

A native Python agent CLI built on DeepAgents CLI, featuring an independent memory Agent that captures learnings after each task and delivers efficient AI coding assistance through hierarchical memory management.

VexJoy AI Agent with Intelligent Routing - /do routes plain-English requests to the right specialist agent and gates the work with reviews, tests, and a learning loop.