SmarterContext
Issue #005 · Wed, Jul 1, 2026
Your AI keeps forgetting what you told it. Learn to fix that. |
When to paste vs when to retrieve
Not everything needs a vector database. Sometimes pasting is the right answer — know when. |
Retrieval is powerful but it's overhead: indexing, embeddings, a search step that can miss. For small, stable, always-relevant knowledge (your 30-line context file, a style guide, today's task) just paste it — it's faster, fully in-window, and never misses. Reach for retrieval only when your knowledge is large, changes often, or only a fraction is relevant per query. The decision is a function of size, volatility, and relevance density — not hype. |
▸ The template
# Paste-vs-retrieve decision table
PASTE when:
- total knowledge fits comfortably in-window (< ~30%)
- it's relevant to (almost) every query
- it's stable (style guide, core rules, glossary)
RETRIEVE when:
- knowledge is large (manuals, archives, tickets)
- only a slice matters per question
- it changes often and must stay current
HYBRID (most real setups):
- PASTE the always-on context.md every time
- RETRIEVE the big reference corpus on demand |
▸ Level it up
New to this: If it fits in one screen and you'd want it in every chat, just paste it. Don't build a database for 30 lines.
Vibe coder: Go hybrid: paste your small always-on context file, and only reach for 'chat with your docs' tools for the big reference material.
Advanced: Budget your context window explicitly — reserve a fixed slice for the pinned context.md, allocate the rest to top-k retrieval, and measure tokens spent per answer to keep cost flat. |
Takeaway: Paste the small-and-always-relevant; retrieve the large-and-sometimes-relevant. Most setups do both.
Deciding what to pin vs fetch is a judgment call you re-make constantly — Brainfile manages the pinned-vs-retrieved split for you as your knowledge grows. |
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Know someone fighting the same context problem?
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