nowfound

AI · August 11, 2026

Tracely

Production failures become regression tests for AI agents

Tracely launched on August 11, 2026 with 9 votes, #1,116 of 23,274 launches that month and more than 90% of that year's launches.

What it does

Tracely grades every agent trace as it lands, clusters failures into issues, freezes bad runs into hermetic replayable test cases — and blocks the PR that would ship them again. The trace is the test: no hand-authored datasets. Open source, MIT.

Trace your AI agents, grade every run, and turn production failures into regression tests that block the pull request which would ship them again.

LLM observability that closes the loop: every agent trace graded as it lands, failures clustered into issues, bad runs frozen into tests that block the PR. Four moves, no hand-authored datasets. Each one is derived from the last, and the trace starts it all. Every production run streams in over OTLP — durable blob first, one indexed row per span. Agent, conversation and tool semantics are first-class columns, not strings. Online evaluators grade each trace as it lands — LLM-as-judge at conversation, run or span level. One FAIL on a blocking evaluator flips the verdict. One click promotes a failing trace into a hermetic case: recorded input, tool and LLM fixtures bundled, a fail-to-pass…from tracely-ai.com

Does a similar job

all alternatives →
  • Trace2025 · trace.so · ▲1,555

    Workflow Automations for the Human 👾 AI Workforce

  • Trace-AIOct 2025 · trace-ai.dev · ▲146

    Know What You Ship. Secure What You Depend On.

  • TraceaMay 2026 · tracea.dev · ▲80

    Datadog for AI agents with traces, RCA, and team memory

  • TraceRoot.AI2025 · traceroot.ai · ▲342

    Fix bugs faster with open source, AI native observability

  • Progress AI ObservabilityAug 2026 · telerik.com · ▲168

    Hi HN! We’re the team behind Fiddler, and we recently built an Agent Cache feature. It works by capturing an LLM request/response pair and, once caching is enabled, serving subsequent matching calls locally so duplicate requests never hit the provider. It’s meant to reduce three pains that show up together in agent development: token cost, feedback-loop latency, and output non-determinism. We’d love to hear your thoughts.

  • TrailsJan 2026 · trails-red.vercel.app · ▲81

    Hey all, Justin here. I previously built Phind, the AI search engine for developers. One of the biggest problems we had there was figuring out what went wrong with bad searches. We had tons of searches per day, but less than 1% of users gave any explicit feedback. So we were either manually digging through searches or making general system improvements and hoping they helped. This problem gets harder with agents. Traces are longer and more complex. It takes more effort to review them, so I'm building a tool that lets you analyze LLM outputs directly to help developers of LLM apps and agents…

More ai this month

the category →
  • Video model that turns script into viral social media videos

    AI · 17d ago · spira.ai

  • The browser where Claude Code and Codex work beside you

    AI · 17d ago · rill.love

  • Kolibri is Aleph Alpha

    AI · 18d ago · tej.as

  • Paintings by AI models: programs run through a simulation of oil paint.

    AI · 20d ago · stillwet.art

  • Onepin▲384

    AI voiceover with every name, price and date said right

    AI · 30d ago · onepin.ai

  • A real-time world model you can explore and change

    AI · 28d ago · world.pixverse.video

Source: Product Hunt launch ↗

Launched alongside, August 2026

the whole month →
  • TL

    Life & fun · Aug 2026 · louisabraham.github.io

  • Hey Noah▲656

    A proactive AI executive assistant for founders

    AI · Aug 2026 · heynoah.io

  • Hey HN, We recently built Clipto. It’s a tool that lets you search over terabytes of video, audio, and images on your computer, without relying on the cloud. Motivation: we probably all had this similar experience, we know a moment exists in a video or audio, but finding it takes hours scrubbing the timeline. You can send all the media to process in the cloud, but it’s slow, expensive and raises privacy concerns. So we decided to build our own on-device media search engine. How it works (high level): 1. We ingest video, audio, image; normalize formats via ffmpeg; run content analysis to…

    Work · Aug 2026 · clipto.com

  • Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…

    Life & fun · Aug 2026 · toneyalexander.github.io

  • AdAnt AI▲620

    Claude for viral, high-converting social ads

    AI · Aug 2026 · adant.ai

  • Astute▲606

    Automate your B2B brand going viral, with new media creators

    AI · Aug 2026 · company-app.joinastute.com