Part of the Agent Engineering Stack: From Zero to Production in 3 Days track — 8 classes, take them in any order.

See the whole track →
  1. Intro to Agents: 1-Day Intensive 15 Sep
  2. Context Engineering 16 Sep
  3. Production Agent Engineering 17 Sep
  4. Intro to Agents: 1-Day Intensive Date TBA
  5. Context Engineering You're here
  6. Agentic SDLC Date TBA
  7. Agentic SDLC Date TBA
  8. Agentic SDLC: Ship Software with AI Agent Teams Date TBA

Overview

Master advanced AI integration and programming techniques with hands-on Python development. Build agentic applications and learn sophisticated prompting patterns.

Who this is for & what you'll need

🟣 Pro engineeringBuilt for working engineers.
💻 💪 Capable or 💵 subscriptionUse your own capable machine, or a paid hosted option below.
On your own machineInstall LocalLM and run open-source LLMs locally for free (for those with the hardware).
Or use the hosted optionOr use the OpenAI API / ChatGPT Plus, with Google Colab (Oobabooga) for the open-model work.

Where This Class Leads

What you leave able to do

  • re architect an agent as a stateless reducer
  • reconcile a failing retrieval by reranking and rewriting
  • reconcile a working set with the context window it must fit
  • reconcile an agents run with a tool that failed
  • select among agent architectures
  • synthesise a memory hierarchy for an agent
  • synthesise an agent that carries notes across its own runs

How you show it. Paired runs of the same multi-step task with the note store kept and cleared, where the cleared run repeats a step the noted run skips, plus the note text the agent wrote and the later turn that cites it.

Join Us

Want to schedule this class for your team?

Contact us: liz@themultiverse.school