Smarter AI comes from engineered context structure, not more words—fewer degrees of freedom, more reliable decisions.
Previous · Part 2
Why More Context Makes AI Worse (And What to Do Instead)
Next · Part 4
Your First Context File v1: Project, Goals, Constraints, Preferences
This builds on Part 2: Why More Context Makes AI Worse (And What to Do Instead)
Continue with Part 4: Your First Context File v1: Project, Goals, Constraints, Preferences
The job of a summary is not “recap.” It’s “re-wire.”
If context is the engine, the summary is the interface. It translates messy inputs into a form your future self—and your system—can reliably use.
A bad summary doesn’t just lose information.
It quietly mis-shapes everything that comes next.
What you’re really designing: an output contract
When you create a summary, you’re not compressing notes.
You’re defining what the next output is allowed to become.
- What matters most?
- What must not change?
- What decisions are already locked?
- What is still flexible?
Think of it as the minimum sufficient context needed to produce the next correct output—without re-reading everything.
The shift most people miss
Most summaries try to answer:
- “What happened?”
High-quality summaries answer:
- “What should happen next—and under what constraints?”
That shift is everything.
Because your system doesn’t care about the past.
It cares about what to do now without getting it wrong.
The critical categories (this is your control surface)
If your summary doesn’t include these, it will drift.
1) Goals — what success looks like
State outcomes, not activities.
Good:
- “Publish a dispatch that converts curious readers into weekly subscribers.”
Weak:
- “Write a good article.”
2) Constraints — what limits the solution space
Constraints define the edges of acceptable output.
Examples:
- Must be self-contained
- No external links
- Paragraphs under 4 sentences
- Use custom blocks where useful
Constraints create contrast, and contrast creates clarity.
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