FREE PILOT EVALUATION TOOL

AI coding pilot scorecard.

Replace demo impressions with six explicit evaluation dimensions. Score each from 1 (unacceptable) to 5 (strong) using evidence from the same bounded task set.

Accepted engineering outcomesDid completed tasks meet the written acceptance criteria?Reviewer effortDid review take less effort than implementing the task directly?Execution reliabilityWere builds, tests, environments, and retries dependable?Security and governance fitWere access, secrets, model routes, and audit evidence acceptable?Developer adoptionWould developers choose this workflow again for suitable tasks?Cost and operational fitWas total model, compute, storage, and operator cost defensible?Evidence notesRecord task IDs, accepted outcomes, failures, incidents, review time, and cost evidence.

PILOT READOUT60/100 · Promising, with conditions

Investigate the lowest dimensions and repeat the pilot before a wider rollout.

Scoring discipline

A number is only as good as its evidence.

Record task acceptance, reviewer time, failed runs, incidents, model and compute cost, and qualitative developer feedback before assigning a score. Use the pilot methodology and blank CSV template to keep attempt-level evidence.

Use the same tasks

Compare workflows on bounded tasks with written acceptance criteria.

Track total effort

Include setup, prompting, retries, review, correction, and operations.

Apply hard gates

A security or reliability score below 3 blocks rollout regardless of the average.

Static example

A high average cannot override a critical control failure.

Example: outcomes 5, review 4, reliability 2, security 2, adoption 4, and cost 4 produce 70/100. The verdict is still “Do not expand” because security and reliability both fail the minimum gate. Resolve the failures, collect new evidence, and repeat the same bounded pilot.

Tool FAQ

Common pilot scorecard questions.

Read the pilot methodology →

How is the pilot score calculated?

Six equally weighted dimensions—accepted outcomes, reviewer effort, execution reliability, security and governance, developer adoption, and cost—are each scored 1 to 5 and normalized to a 0-100 total. Security and reliability act as hard gates: a score below 3 in either blocks rollout regardless of the average.

Why can a high average still say "do not expand"?

Because a strong average can hide a critical control failure. If security or reliability scores below 3, the verdict is "Do not expand" until you resolve the failed control, collect new evidence, and repeat the same bounded pilot.

Does the scorecard store my evidence?

No. Scoring and the JSON export run entirely in your browser; nothing is uploaded. Use the pilot methodology and CSV template to keep attempt-level evidence alongside the score.