Context Compression Engines

This build lab focuses on the compression engine that keeps an agent useful when the conversation becomes too long. The goal is not to copy a private machine setup. The goal is to learn the architecture pattern well enough to build a small, classroom-safe version.

A compression engine turns a long transcript into durable state: goal, decisions, files touched, open tasks, blockers, and exact instructions that still matter.

Build the small version

1. 1Draw or write a compression checklist and a sample handoff summary for a long project.
2. 2Mark which parts are user-facing, which parts are internal, and which parts require approval.
3. 3Choose one low-risk workflow and implement only that workflow first.
4. 4Add one failure case before adding a second feature.
5. 5Write a short operator note: what the agent may do, what it must ask about, and what it must never do.

compression_record:
  goal: Build a classroom-safe agent demo.
  decisions:
    - local model for private prompts
    - hosted model for public examples
  files_touched:
    - app/agent.ts
  open_tasks:
    - add approval screen
  blockers:
    - need teacher test account
  must_preserve:
    - never send student names to hosted providers

The big idea: compression is not decoration. It is part of the product architecture students need before an agent becomes safe enough to use with real people.