Context engineering

Your context window is a working set. Like any working set, it has limits, and the cost of a bad one compounds.

The four moves

1. Write — commit durable info out of the transcript and into files the model can re-read later. Plans, decisions, learnings, todos. Don't leave them floating in chat.
2. Select — load exactly what you need for the current step. Not the whole repo. The specific files that matter for the specific change.
3. Compress — summarize old transcript turns into one line each, and offload details to files. After a long debugging arc: one paragraph of "what we tried and what happened" beats 30 turns of blow-by-blow.
4. Isolate — delegate sub-problems to subagents so their discovery doesn't pollute the main context. Research-heavy exploration → Explore agent. Review → code-reviewer agent.

Practical heuristics

• Hot > cold. Keep recent decisions, current plan, and the ~3 files you're actively editing in context. Everything else can be retrieved.
• References, not contents. "See docs/adr/0007-queue.md" beats pasting 400 lines of ADR.
• One plan, one place. If the plan is in context AND in a file, they'll drift. Canonicalize in the file; reference from context.
• Invalidate explicitly. When a decision changes, say so. "We said X, now we're doing Y because Z." Don't let old assumptions linger.

Smells that say "you've lost the plot"

• The model repeats analysis you already gave it
• Transcript is >50 turns and you don't remember what turn 10 decided
• You're answering the same question for a second time
• The model confidently contradicts itself

Act on the smell. Use /holocron:handoff to write a durable doc and start fresh.

Related

• /holocron:handoff — persist state before compaction
• /holocron:learn — persist rules for future sessions
• /holocron:plan — write the plan to a file rather than carry it in chat