Method

Method

IdeaGrains tests AI models on real product work, then publishes evidence-backed reports showing which model made the strongest V2.

What IdeaGrains is

IdeaGrains is a benchmark catalogue built around real product cases. Each case starts as a V1 product or project, then different AI models are given the same improvement brief. The output is compared, scored, and published as a report linked back to the source case.

How the test works

01

Choose real product case

Use an owned V1 product or project, not a toy prompt.

02

Freeze V1 baseline

Capture the product state, screenshots, constraints, and known issues.

03

Give same brief

Each model receives the same improvement task and product context.

04

Review V2 attempts

Compare what changed in UX, code, judgement, and reliability.

05

Track human rescue

Log the fixes, rewrites, debugging, and decisions needed from a human.

06

Publish report

Show the evidence, caveats, source case, and practical verdict.

Why real product cases?

Real products include messy context: existing UX, technical constraints, deployment concerns, unclear tradeoffs, and user-facing consequences. That is where model differences become useful.

Why source cases matter

Every report links back to the product case it came from, so readers can trace the baseline, model attempt, evidence, and final verdict.

What human rescue means

Human rescue is the manual correction needed before an output becomes usable: fixing bugs, tightening copy, rejecting bad product judgement, or repairing deploy risk.

What we score

Product outcome

Did the model create a meaningfully better V2 for the product and user?

Technical execution

Was the implementation clean, deployable, secure enough, and low-risk?

Human effort

How much correction, judgement, debugging, or rewriting was needed?

Evidence quality

Did the report include enough prompts, outputs, before/after notes, and caveats?

Limitations

IdeaGrains is not an academic benchmark. It is a practical builder-focused benchmark using real product work. Scores include human judgement, documented evidence, visible caveats, and corrections when assumptions change.