Tasks / Design

One-shot prototype

Can the configuration produce a working, constraint-compliant prototype in one attempt?

Measures the systemTask v1.2 · 2 casesDifficulty

What AI gets right here, and what you’ll still have to catch

From 12 graded outputs by 6 models.

Reliably right

Avoids template layout and copy tells100% pass
Shows the no-slots state100% pass
Respects explicit constraints83% pass

Where it slips

Says what it tests and what's faked46% pass
Avoids the generic AI palette67% pass
Stays in scope75% pass

Case viewer

Read the brief, then put up to three outputs side by side, each with the LLM judge’s verdict on every check. Highlights mark what a PM had to fix.

The brief

Build a clickable prototype that lets a patient move an existing appointment to another available slot in one flow. Deliver a single self-contained HTML file that opens straight into the flow in a browser: no design canvas, artboard or "play" step. Use made-up data.

ScenarioSam Patel has a GP appointment with Dr Amira Khan at Harbour Medical Centre on Tuesday 6 October at 09:30 and needs to move it. Show the next seven days of availability; at least one of those days is fully booked.

ConstraintsDesigned for a mobile screen, about 390px wide. No login, sign-up or account screens. Show a clear "no slots available" state for a fully booked day. The original appointment stays booked until the patient confirms, and the confirmation shows the new time.

What a strong answer does

A working mobile rebooking flow: pick a new slot, confirm, and see the new time confirmed; a fully booked day says so clearly; nothing beyond rebooking.

Critical failures (cap the score)

Core interaction broken

Case

v1.1 · synthetic · health, mobile

GPT-6.1 SolAPI GPT-6 LunaAPI Sonnet 5.5API Opus 5.5Claude GPT-6 AstraChatGPT Gemini 3.5 Flash-LiteGemini

GPT-6.1 SolAPI

5 of 7 checks passed

Output

Open the prototypeThe file the model delivered, in a new tab

Save this as `reschedule.html` and open it in a browser. It runs directly, with no external dependencies.

Check by check

Mixed · 2

Core interaction worksThe two graders disagreed on this one.
Says what it tests and what's fakedThe two graders disagreed on this one.

Got right · 5

Respects explicit constraints
Shows the no-slots state
Stays in scope
Avoids the generic AI palette
Avoids template layout and copy tells

Grades and run details

Decision model 86

Decision model checks

passStays in scope74%
partialSays what it tests and what's faked53%
passRespects explicit constraintsby hand100%
partialCore interaction worksby hand100%
passShows the no-slots stateby hand100%
passAvoids the generic AI paletteby hand100%
passAvoids template layout and copy tellsby hand100%

Artefacts

Prototype (html)

Run

Run: #1
API response time: 79 s
Submitted: 29 Sept 2026

Results

Every setup we’ve tested on this task, across all cases and repeats, graded on the current checklist. Calibrated: the graders match our PM on 86% of checks.

#	Model · Harness	Decision model	LLM judge	Runs	Critical failures
1	Sonnet 5.5withAPI	92.9	–	2	None
2	GPT-6.1 SolwithAPI	88.7	–	2	None
3	GPT-6 LunawithAPI	84.5	–	2	None
4	Opus 5.5withClaude	76.8	–	2	None
5	GPT-6 AstrawithChatGPT	69.6	–	2	None
6	Gemini 3.5 Flash-LitewithGemini	49.4	–	2	None

The PM job

Getting a clickable prototype in front of users or stakeholders fast.

Why it matters

A prototype that looks right but whose core interaction is broken wastes a research session. This task rewards working behaviour over polish.

What good looks like

The core interaction works end to end
Respects the stated constraints and scope
Handles the empty and error states named in the brief
Says what it's testing and what's faked
Looks like something you'd share: clear hierarchy, none of the stock AI-template look

Deliberately not measured

Production code quality
Design to a requested style: the brief never asks for one, so this measures default taste

Capability tested

Turning a spec into a usable interactive artefact

The failure we’re looking for

An attractive shell with a broken or absent core interaction

Grading

Browser checks (interaction and design) and decision model, calibrated against a blind PM review

This task measures the whole setup. Tools, instructions and skills in the harness do real work here, so read the harness as carefully as the model name.