Your AI agent ships UI that's technically correct and experientially wrong. You can see it the moment the diff lands. You don't always have time to fix it.
Your agent reached for tabs again — even though the job is sequential.
It built another dashboard when the user just needed to do the thing.
The shadcn defaults are showing. Again.
Not a benchmark suite — a list of moves your agent makes when it doesn't know any better.
The job was do the thing, not watch the thing. Your agent didn't know the difference.
High-stakes, sequential workflows split across status tabs. The default move when the agent doesn't know the flow.
The UI ignores who's using it, when, and why. The diff passed review. The user can't get through it.
You've redone agent UI three times this week. Stop.
Ship the right thing on the first build — same agent, same model, no new tool to learn.
You watched your design system get flattened into shadcn defaults.
Encode your taste so the agent has to pass through it before the diff lands.
You shouldn't be the QA layer for agent slop.
Every build measured against the actual job, before it reaches you.
You ship custom UI in customer repos every week.
Drop-in in any repo, any agent, any stack. One pointer file. No infra.
Or AGENTS.md. The agent reads it on every run. No SDK, no MCP server to host, no infra.
On its own. It already knows what to send: the changed file, the user task, the page in context.
The agent applies them before it opens the PR. The brain stays with us. One pointer file lives in your repo.
## Design judgment Before finalizing UI changes, call https://api.thedesignagent.ai/ux with the changed component path and the user task it serves. Apply returned patches before opening the PR. Read .thedesignagent in repo root for project conventions. Use /visual for craft review when shipping new screens.
Same task, same agent, same model. The only difference: TheDesignAgent in the build loop.
“You’ve seen this exact tab pattern in fifty agent builds.”
Tabs by status — the default reach when data has categories. The operator's job is sequential, not categorical.
The job isn't “monitor orders by category.”
It's “fulfill one order, end-to-end.” The agent picked a layout that fights the workflow.
Sequential workflow — Claim → Pick → Pack → Ship.
One operator, one order, end-to-end. Status comes from the rail, not from where you click.
The score trajectory is the receipt. No knobs to tune. Just keep building; the layer remembers.
A toggle. Same call, same agent. The output is a different kind of UI — chat-first, command-driven, agent-led. Built around how AI actually works inside the surface, not adapted to it.
Most agent-built UI today is conventional UI that an agent assembled. Forms, tables, tabs. AI Native Mode flips the assumption: the agent isn't the builder, it's the partner. The screens it generates are shaped around running an agent, not being a form.
Tied into Trailhead — our growing library of AI-native patterns: command surfaces, agent inboxes, generative previews, instruction-and-confirm flows. The mode picks from Trailhead automatically based on the JTBD.
Component libraries exist because building UI was expensive and inconsistency was hard to prevent. AI agents changed the cost equation. The case for building unencumbered — and what you need instead.
5 min read →Anti-patternsFour KPI cards, a table, a date filter. The dashboard is the agent's lowest-effort answer to 'build me a tool for this data.' It's also wrong most of the time.
4 min read →Your agent will not become a designer.It can stop shipping like one who quit.
Flat per-call. Either lens. Patches included. No seats, no tiers, no negotiation.
One call = one evaluation, either lens. Both lenses included in your account. The project memory grows with every call you make.
Get an API key. View calls and fit-score history in your dashboard. Pay through Stripe like any other SaaS. Standard for teams.
Get API key →Skip the dashboard. Open the Stripe link, top up call credits, your agent uses them autonomously. Designed for agents that buy their own usage.
Open agent pay link ↗