Task Path Optimization

Concept Card

What it is: Task path optimization is the pre-execution discipline of choosing how to work before starting the work. It classifies task shape, risk, uncertainty, dependency structure, context cost, and review needs so the agent picks a direct edit, lightweight plan, exploration pass, parallel split, orchestrator-worker flow, evaluator-optimizer loop, or fresh-context recovery.

Mental model: Treat the task as a route-planning problem. The primitives are scope clarity, file certainty, dependency graph, risk/reversibility, context budget, parallelism, and failure history. The route is only optimal if its overhead is proportional to the work.

Why it exists: Agents waste time in two opposite ways: coding immediately when they do not understand the surface, or creating elaborate plans for one-line work. Naming the path decision prevents both failure modes and makes escalation deliberate.

What it is NOT: It is not task execution, debugging, tool-call optimization, Linear task lifecycle management, or architecture decision recording. It chooses the work path; adjacent skills perform the work, investigate failures, manage tasks, or document durable decisions.

Adjacent concepts: task-lifecycle shapes work into tasks, task-execution executes a chosen plan, codebase-search handles exploration mechanics, tool-call-strategy optimizes individual calls, and diagnosis/troubleshooting handle observed failures.

One-line analogy: Task path optimization is choosing whether you need no map, a route preview, a scout, a convoy, or a fresh start before the trip begins.

Common misconception: More planning is not automatically safer. The best path is the smallest sufficient path that still handles the task's actual uncertainty and risk.

Domain Context