Cost per Successful Task

Cost per Successful Task means the average amount of money it takes for an AI to actually finish a job properly, start to finish.

A delivery analogy makes this easy to picture. If a courier company ships 100 packages and 20 arrive damaged and have to be resent, the real cost isn't simply the "price per package sent" — it's the actual money spent per package that arrived successfully. AI coding tools work the same way. The price of a single request might look cheap on its own, but if failures and retries happen often, the real cost of getting one usable result can end up much higher.

That's why this metric is often a more practical yardstick than a simple price sheet when comparing tools or models. Even the same AI model can produce very different numbers depending on which tool it's paired with and how that pairing is tuned, so a figure measured for one specific combination can't be assumed to apply to a different combination.

The article notes that "GPT-5.6 Terra running in Kiro's spec-driven development environment cut the cost per successful task by about 82%." A common misreading is that this 82% represents an overall price cut for GPT-5.6 itself. In fact, it's a benchmark result measured for one specific combination — the Kiro tool paired with the Terra variant — so it can't be assumed to carry over to other tools or other model versions.