Do Not Drive to the Wall

~25 min · safety-margin, checkpoint, long-session

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Full context is an emergency state

When the window is nearly full, the model has less room to absorb corrections, inspect tool results, or produce a careful answer. It may also become more vulnerable to stale instructions competing with current ones — there is simply no spare attention for the human to redirect with.

Preempt, do not react

The correct move is preemptive. Checkpoint before the margin is gone. Summarize decisions while both the model and the human still have enough working space to verify the summary. Reactive checkpointing — the kind that happens after the first truncation or hallucination — is already too late; the corrupt state is already in the recent context.

Checkpoint is not failure

In serious work, stopping to preserve state is professionalism. The opposite is gambling that the last 5% of the window will somehow carry the hardest part of the job. Cute. Also how bugs breed.

Context margin is safety equipment. Spending it all is not efficient; it is reckless.

Code

Preemptive checkpoint trigger·python

def context_health(used_pct):
    if used_pct < 0.65:
        return "healthy"
    if used_pct < 0.75:
        return "checkpoint_now"
    if used_pct < 0.85:
        return "compact_or_handoff"
    return "emergency_only"

if context_health(used_pct) == "checkpoint_now":
    create_checkpoint()
    ask_human_to_confirm_live_rules()

Trigger rules·yaml

checkpoint_triggers:
  by_usage:
    - context_used_pct >= 65%
  by_event:
    - after_major_decision
    - before_risky_edit
    - before_publish_or_push
    - on_topic_switch
    - when_human_corrects_authority_rule

External links

OpenAI compaction guide

Exercise

Write a trigger rule for your own workflow: when should the model stop expanding scope and checkpoint instead? Include both usage-based and event-based triggers.

Progress

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