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Mirrors

test AI agent changes by replaying production traces

Details

External ID
48768200
Source
HN
Company
—
Product
Mirrors
Website domain
runmirrors.com
Launched
July 2, 2026
Cohort
—
Upvotes
8
Upvotes percentile
0.46176821983273597
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Enrichment

Theme
ai agent infrastructure and tooling
Vertical
Horizontal
Function
Observability & eval
Audience
Developer
AI stance
AI feature
Project type
Commercial product
Normalized one-liner
test ai agent changes by replaying production traces
Manually corrected
False

Could you build this?

No Mirrors requires building synthetic sandboxed digital twins of enterprise third-party APIs from production traces and orchestrating deterministic session replay across arbitrary LLM tools. Developing mock synthesis, state tracking, and network interception across multiple languages demands deep distributed systems and compiler/runtime expertise.

What it would actually take: The architecture requires SDK collectors (eBPF or language-level HTTP/gRPC middleware in TS/Python/Go) that stream request-response traces to an event ingestion engine (Kafka/ClickHouse). The system must analyze recorded traces, generate stateful synthetic mock servers with relational schema inference, and manage dynamic mock orchestration across transient test environments, coupled with diffing engines to evaluate model drift on non-deterministic tool calls.

Discussion

No comments on this launch.

Competitors

Other products that read as similar to this one — 1866 launches clear the similarity bar, closest 8 shown.

Attention rank: #874 of 1867 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 246 days after the earliest competitor.

Other launches for this product

Same idea, different domain

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