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Ashr: Mimic Your Production Environment and Users to Catch Agent Fails

Custom Tests and Evals Simulating Real User Behavior

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YC · launched Feb 27, 2026 · 9 upvotes (top 82%) · 0 views

Niche: ai agent evaluation platforms · 182 launches, 8 in the last 7 days ▼ -50% · Explore this niche →

Category and tags

  • Horizontal
  • Observability & eval
  • Developer
  • AI-native
  • Commercial product
  • Deep Learning
  • Generative AI
  • Reinforcement Learning
  • Data Engineering
  • AI

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Could you build this?

Partial While an AI coding assistant can easily scaffold LLM evaluation scripts and basic test runners, reliably simulating complex production environments and stateful user interactions without high flakiness requires specialized infrastructure.

What it would actually take: The architecture requires an isolated containerized sandbox orchestration layer (such as Firecracker microVMs or Docker) paired with an API traffic replay and masking proxy to mirror production states. The hard parts include state management across multi-step agent actions, synthetic user trajectory generation that accurately models adversarial edge cases, and automated verifiers that avoid semantic evaluation drift. This requires distributed systems expertise and familiarity with agent evaluation frameworks.

Competitors

Other products that read as similar to this one : 4209 launches clear the similarity bar, closest 8 shown.

Attention rank: #3353 of 4210 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 121 days after the earliest competitor.

The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.