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Part IV — AI Studio Deep Dive: Every Knob Matters Eventually/11. Context Management Like a Pro
11. Context Management Like a Pro
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What this section is for
Context management is the difference between “the model keeps helping” and “the model keeps getting confused.”
This section teaches you how to:
- decide what to include and exclude,
- summarize state between iterations,
- treat context like a budget,
- handle multi-file projects without losing coherence,
- prevent conflicting instructions over time.
Context is not storage
Don’t treat the context window as a dumping ground. Treat it like working memory: allocate it intentionally.
The mental model: context is working memory
Models don’t “remember” your project. They operate on what you provide right now. If the context is:
- too small: the model guesses.
- too big: the model gets distracted and contradicts itself.
- well-curated: the model is coherent and useful.
This is why context management is a core skill—not an advanced trick.
Context principles that keep you fast
- Prefer specs over history: a stable spec block beats 50 chat messages.
- Prefer “relevant slices” over “the whole repo”: paste only what matters.
- Prefer tests and errors as evidence: they anchor behavior.
- Prefer summaries over raw dumps: compress and re-anchor regularly.
- Prefer file maps: keep a high-level index so you can navigate without flooding context.
Section 11 map (11.1–11.5)
- 11.1 What to include vs exclude from context
- 11.2 Summarize state between iterations
- 11.3 The “context budget” technique
- 11.4 Handling multi-file projects without losing coherence
- 11.5 Preventing conflicting instructions over time
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