AI Agent Developer

Starts today

~6 months

Track

AI Agent Developer

We treat an AI agent as a harness around an LLM: every model call receives assembled context, chooses an answer or a tool call, and regular code runs the loop. The main path uses the OpenAI Responses API; the Agents SDK appears as the next orchestration layer. The finale is one LLM Wiki capstone project.

Access to a Discord community of heavy hitters

A lot of hands-on practice, flash tests, and capstone projects

Mentors, checkpoints, and mock interviews

Lifetime access and permanent updates

TrackThe course moves from the right mental models for LLMs and a short Python prep path into OpenAI-first AI agent engineering. You will work through the Responses API, structured output, the RAO/ReAct loop, tool contracts, MCP, retrieval and grounding, memory layers, planning, traces and evals, runtime wrappers, workspaces, trust boundaries, and the final capstone project. No myth of a living model: agency comes from the harness, state, context, and careful engineering policies.

Understand that every LLM call only sees assembled context, while agent memory is built by the harness, state, and retrieval
Work with the OpenAI Responses API and understand where the Agents SDK removes orchestration boilerplate
Design tools as contracts: schemas, validation, permissions, side effects, MCP, and approvals
Separate context, retrieval, grounding, and memory instead of calling every vector store the agent brain
Build an LLM Wiki capstone project with traces, evals, safety policies, and a clear acceptance path

AI Agent Developer

Who this track is for

New

Developers ready to write Python, use the CLI, and design reliable AI agents for real tasks

Pro

AI engineers moving from prompt demos to systems with tools, memory, and retrieval

Technical product and ops teams ready to automate research, support, and internal workflows hands-on

Technical founders building agent-based products and wanting to understand the architecture beyond ready-made wrappers

Anyone who wants to learn evaluation, safe run design, and debugging of agents on real tasks

Program

The current program moves from mental models and Python prep into an OpenAI-first agent harness, context engineering, retrieval, memory, evals, safety, and the capstone project.

Intro: what makes a system an agent

Python prep and building blocks

LLMs and the OpenAI API

Prompts and context packets

Tools: contracts and MCP

Platform

A crypto-native platform packed with research-backed learning tools and designed by a former Rarible product lead.

Wallet-based login
No logins or passwords — just connect MetaMask from any device and start learning.
Microformats
The material is broken into small, easy-to-digest blocks so you can keep moving even if you only have 15 minutes a day.
Active learning
Interactive tasks and exercises that let you apply new knowledge in practice. Every module ends with a capstone project so you use the full stack of skills you just gained.
Code first
The platform is built for working with code: built-in editor, dark theme, and syntax highlighting like in your usual VS Code or Remix IDE.

CommunityA community of AI and crypto enthusiasts, developers, cryptographers, engineers, auditors, and investors who sharpen each other’s craft and form teams together.

Daily streams, no days off

Live coding

Hands-on development with a mentor — the closest alternative to pair programming, still the gold standard of effective skill transfer in IT.

AMA with experts

Market reviews

Career

Our goal is for you to outgrow the DAO as fast as possible — launch your own project or join a global startup.

Mock interviews

A simulation of a technical interview with active developers and team leads — like Total Recall on Valocordin.

Portfolio

Nothing sells you better than a GitHub profile packed with real production-grade architecture cases — whether it’s a complex smart contract or an autonomous AI agent.

Success stories

Graduates share their wins, explain how they found work in AI and crypto, and pass résumé hacks on to newcomers.