Free Lesson
Long Context Engineering
30 min
Sep 23, 2026 5:00 PM
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What you'll learn
Why your agent breaks as it runs ?
It's not a bad prompt. It's context rot: recall drops as the window fills, even on easy tasks.
The "lost in the middle" problem
Models remember the start and end of a long context, but forget the middle where the answers usually live.
The four pillars of context engineering
A toolbox for curating what the model actually sees.
Worked before-and-afters
See a 5,000-token API response shrink to 220 tokens
Three moves you can ship this week
Audit your tools, stop front-loading context, and instrument the window so failures become fixable.
Why this topic matters
Most agents don't fail from bad prompts they fail because the context window quietly grows into an unmanageable jumble of tokens that the model can't reliably use. Recall drops as the window fills, and the facts your agent needs often sit forgotten in the middle. Context engineering is the skill of curating what the model sees on every call, so your agent stays sharp and accurate over long runs instead of rotting into confusion.
