Dispatch economics

Quality first, tokens second — and they align. A single agent grinding for hundreds of turns doesn't just cost more; it gets worse (context rot: by turn 200 it re-reads a bloated history every turn and reasons over noise). Small, fresh-context units are both cheaper and smarter.

We learned this on a real bill: three days, one week's entire quota, ~5 billion cached-context tokens read. The autopsy is in case-studies/token-burn-postmortem.md.

Rules

• One agent per ticket by default. A fleet needs all three preconditions:
  1. Quote first — say out loud, before launch: how many agents, which model tier each one runs on, how long, estimated tokens.
  2. Per-agent contract — ≤100 turns, ≤5 tasks; hit a cap → save progress to disk, report, split into a fresh agent.
  3. True parallelism only — fan out only work items with no dependencies on each other.
• Every quote names a tier per agent. Tier sits beside agent count, duration and budget percentage — same line, not a footnote, never "we'll decide as we go". Two reasons, both load-bearing. The founder is the one paying for this compute: a quote without tiers asks him to approve a blind box. And having to write the tier down forces you to re-read your own staffing before launch — "cheapest tier" sitting next to "verify the payment logic" is a mistake you catch when you have to say it out loud. Which tier to pick: model-tiering.
• Verification force ≤ 1/3 of build force. Reviewer armies grow quadratically if you let them (N findings × M verifiers). Cap adversarial review at 2 rounds — converged means stop; there is no "one more round for safety".
• Slice work vertically. A ticket = one thin end-to-end feature (schema + logic + UI + test) that fits in a single fresh context window. Never slice by technical layer — layer-slices create the 300-turn monster agents.
• The expensive session never digs. Your main (priciest) session dispatches a scout to read files or the web and consumes its conclusion. Thinking at the top, grinding at the bottom — but note that scouting an unfamiliar codebase is thinking, not grinding, and is staffed accordingly: model-tiering.
• Restarts resume, never re-run. Crashed work restarts from its saved artifacts. Re-running from scratch doubles the bill for zero new value.

Success criteria

Every dispatch was quoted before launch, tier named per agent. No agent exceeded its contract. The bill correlates with shipped output — and the top line item is thinking, not grinding.