 FIG_001 · A PROMPTS |
 FIG_001 · B SKILLS |
 FIG_001 · C AGENTS |
 FIG_001 · D MCP SERVERS |
|---|---|---|---|
| Paste into any AI assistant for expert-level help on a narrow task. | Drop into Claude, Cursor, Codex, OpenClaw, Hermes, or any agent that reads SKILL.md. |
Deploy as autonomous workers — you wrote the loop yourself in Phase 14. | Plug into any MCP-compatible client. Built end-to-end in Phase 13. |
| **`code/agent_loop.py`** build it ```python def run(query, tools): history = [user(query)] for step in range(MAX_STEPS): msg = llm(history) if msg.tool_calls: for call in msg.tool_calls: result = tools[call.name](**call.args) history.append(tool_result(call.id, result)) continue return msg.content raise StepLimitExceeded ``` | **`outputs/skill-agent-loop.md`** ship it ```markdown --- name: agent-loop description: ReAct-style loop for any tool list phase: 14 lesson: 01 --- Implement a minimal agent loop that... ``` **`outputs/prompt-debug-agent.md`** ```markdown You are an agent debugger. Given the trace of an agent run, identify the step where the agent went wrong and explain why... ``` |
22 lessons The intuition behind every AI algorithm, through code.18 lessons Classical ML — still the backbone of most production AI.13 lessons Neural networks from first principles. No frameworks until you build one.28 lessons From pixels to understanding — image, video, 3D, VLMs, and world models.29 lessons Language is the interface to intelligence.17 lessons Hear, understand, speak.14 lessons The architecture that changed everything.14 lessons Create images, video, audio, 3D, and more.12 lessons The foundation of RLHF and game-playing AI.22 lessons Build, train, and understand large language models.17 lessons Put LLMs to work in production.25 lessons See, hear, read, and reason across modalities — from ViT patches to computer-use agents.23 lessons The interfaces between AI and the real world.42 lessons Build agents from first principles — loop, memory, planning, frameworks, benchmarks, production, workbench.22 lessons Long-horizon agents, self-improvement, and the 2026 safety stack.25 lessons Coordination, emergence, and collective intelligence.28 lessons Ship AI to the real world.30 lessons Build AI that helps humanity. Not optional.17 projects 2026 end-to-end shippable products, 20-40 hours each.| FIG_003 · A THE INDUSTRY SIGNAL |
FIG_003 · B FOUNDATIONAL PAPERS COVERED |
|---|---|
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> *"The hottest new programming language is English."* > — **Andrej Karpathy** ([tweet](https://x.com/karpathy/status/1617979122625712128)) > *"Software engineering is being remade in front of our eyes."* > — **Boris Cherny**, creator of Claude Code > *"Models will keep getting better. The skill that compounds is **knowing what to build**."* > — Industry consensus, 2026 |
- *Attention Is All You Need* — Vaswani et al., 2017 → [Phase 7](#phase-7) - *Language Models are Few-Shot Learners* (GPT-3) → [Phase 10](#phase-10) - *Denoising Diffusion Probabilistic Models* → [Phase 8](#phase-8) - *InstructGPT / RLHF* → [Phase 10](#phase-10) - *Direct Preference Optimization* → [Phase 10](#phase-10) - *Chain-of-Thought Prompting* → [Phase 11](#phase-11) - *ReAct: Reasoning + Acting in LLMs* → [Phase 14](#phase-14) - *Model Context Protocol* — Anthropic → [Phase 13](#phase-13) |