Nicheloom

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FixBugs

Reproduce production bugs and verify fixes

Details

External ID
48900465
Source
HN
Company
—
Product
FixBugs
Website domain
fixbugs.ai
Launched
July 13, 2026
Cohort
—
Upvotes
43
Upvotes percentile
0.8279569892473119
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

I built FixBugs, an agent that ingests the rich context surrounding production bugs to reproduce them in a sandbox and generate verified fixes. It's available in the form of a self-hosted VSCode extension and as a Github app:VSCode Extension: https://fixbugs.ai/go/vscode-extension - full code and data privacy. - zero data retention models opted out of training. GitHub App: https://fixbugs.ai/go/github-app - we do access your code temporarily. - pick a repo to install FixBugs on. What motivated me to build FixBugs were my years being on-call at Google and VMware. How many hours did I spend gathering logs, traces, reviewing metrics, and reading code only to find that,* Some context was missing.* The bug wasn't reproducible.* The alert was caused by a transient infrastructure issue.Too many. Inefficiency in investigating staging/production bugs has a real cost, and it's paid both by developers and customers.Current capabilities: - Reproduce the bug. - Identify the root cause. - Generate a fix. - Verify the fix. - Review the generated code using multiple AI models to help catch potential regressions. Do try it and let me know what you think!I'd especially love feedback from engineers who work with distributed systems or handle high-volume production bug triage.

Enrichment

Theme
AI agent frameworks and developer tools
Vertical
Horizontal
Function
Dev tools
Audience
Developer
AI stance
AI feature
Project type
Commercial product
Normalized one-liner
reproduce and verify production bug fixes
Manually corrected
False

Could you build this?

Partial The VS Code UI and LLM code-fix pipeline are easy, but orchestrating isolated, deterministic production sandbox reproduction environments requires sophisticated infrastructure.

What it would actually take: Requires a containerized sandbox execution environment (e.g., Docker, Firecracker microVMs) capable of safely provisioning arbitrary project stacks, mocking network/database dependencies from production logs, running test suites to replicate failures, and verifying patch stability. Integrating robust sandbox lifecycle management and log-to-test reconstruction is the core infrastructure challenge.

Discussion

20 comments analyzed.

Competitors mentioned: Copilot, Claude, GPT, NewRelic, Datadog

Concerns raised: How it differs from Copilot for bug fixing, Reproducibility on large distributed systems with intermittent bugs, Handling services with multiple dependencies and production environment recreation, Reliability for non-frontier models and codebases without test harnesses

Feature requests: Direct integration with alerting platforms (NewRelic, Datadog) for on-call workflows, Better benchmarks for investigating alerts with huge context amounts

Competitors

Other products that read as similar to this one — 147 launches clear the similarity bar, closest 8 shown.

Attention rank: #23 of 148 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 252 days after the earliest competitor.

Other launches for this product

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