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An agent loop that builds and tests web prototypes

14 starsPython

Autocrit – automated persona-based UX prototyping and evaluation

by 4di·Apr 5, 2026·3 points·2 comments

AI Analysis

●●SolidBig BrainBold BetShip It

Persona-driven critique loop is clever, but locked to pi.dev limits adoption.

Strengths
  • Separate persona agent generates tasks independently from coding agent — avoids bias.
  • Real browser automation via agent-browser or Playwright, not just simulated feedback.
  • Autonomous iteration loop persists state and resumes across sessions.
Weaknesses
  • Tied to pi.dev platform — narrow audience compared to standalone tools.
  • Zero stars, early stage — unproven at scale with complex prototypes.
Category
Target Audience

Product developers using AI coding agents, UX researchers

Similar To

UserTesting · Maze · Hotjar

Post Description

Hi HN, this is my first Show HN submission.

I've been thinking about how product development will change with AI. The earliest stages of product development have so much ambiguity. Because code was costly and expensive, we spent a lot of time writing specs and doing user research.

I thought I'd try an experiment after (a) seeing advancements around evaluation systems especially for UX (b) realizing that AI can create a reasonably good enrichment of a persona/end-user (c) seeing karpathy's autoresearch project.

Basically you provide high-level app idea, and a definition of the target user. Autocrit will create a persona definition, has that persona create evaluation tasks, and then starts a loop where a coding agent builds a prototype, and a persona agent will try to use it in a real browser. They will judge it based on the tasks, giving scores and verbatim feedback. The coding agent creates a plan to fix things, keeps improvements, reverts bad ideas, etc. The loop runs overnight.

The goal is to get a better understanding of where to take the product at an early stage e.g. paper prototypes, before actually starting to build the product. The evaluation loop of prototyping and getting feedback is automated here, but humans provide the definition of the persona, app idea / product goals, and hypotheses that need validation.

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