Aglet

Learn From Repeated Oversized Agent Tasks

Learning from oversized tasks means preserving the boundary that made a slice finishable and the trigger that justified any expansion. Record the added question, its dependency, and the decision it served. Turn those lessons into examples and review habits without suppressing legitimate discovery.

Keep the lesson for the next incident

  1. Classify scope growth

    Group incidents by vague outcome, multiple audiences, hidden dependency, missing exclusion, optional work, changing objective, or absent stop rule. Keep one timeline and downstream consequence for each class. Distinguish useful expansion from scope that only repeats or postpones a decision.

  2. Keep slicing exemplars

    Retain before-and-after briefs showing primary decision, evidence slice, exclusions, deferred questions, dependency owner, deliverable, and widening trigger. Include a justified expansion and a split that improved review. Update examples when the task family or evidence standard changes.

  3. Review recurrence and ownership

    Assign owners for scope decisions, dependency handoffs, and final review as needed. Sample new tasks on a defined cadence and track invisible expansion or unfinished slices. Reopen investigation for repeated broad verbs, changing objectives, or queue items that have no finite stop.

What to carry forward

Close the learning record with scope-growth classes, slicing exemplars, owners, and a trigger for unbounded or repeatedly expanding work. Preserve intentional discovery as queued behavior. The durable result is finite agent tasks with visible relationships between slices and decisions.

Keep the decision with the work.

Use a Work Item in Aglet to record the problem, the evidence you have, and the next decision. Add an owner and priority, then keep updates in the discussion so the next person can follow the reasoning.

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