AI coding cost estimator

Use the estimator when a team wants a quick planning number for AI-assisted coding work before implementation begins.

Engineering managers and product teams can use this page when ordinary story-point planning does not capture how much AI-assisted exploration, prompting, generation, and review the work may require.

Enter expected prompts, average context size, generated output, review loops, and a token price to get a directional planning estimate.

In Token Poker, ask participants to vote privately before reveal. A private vote reduces anchoring and makes it easier to see whether disagreement is about delivery effort, likely AI usage, or both.

Record the final story-point estimate, final token estimate, and the assumptions that changed during discussion. The assumptions are often more useful than the number because they show what the team needs to learn next.

If token estimates are high, ask whether the ticket needs extra discovery, smaller slices, clearer acceptance criteria, or a deliberate decision to spend more AI budget on the work.

Actual cost depends on provider pricing, model choice, cache behavior, context reuse, and implementation details that may change during delivery.

Competitor and tool comparisons should stay specific. Token Poker focuses on AI-aware planning poker; other tools may be a better fit when a team only needs classic story-point voting or has different workflow requirements.