FixBugs
Reproduce production bugs and verify fixes
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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.
HN · launched Jul 13, 2026 · 43 upvotes (top 17%) · 0 views
Niche: software debugging tools · 80 launches, 6 in the last 7 days ▼ -40% · Explore this niche →
Category and tags
- Horizontal
- Dev tools
- Developer
- AI feature
- Commercial product
Visit website ↗ Source listing ↗
More like this: all 80 launches in software debugging tools →
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 : 371 launches clear the similarity bar, closest 8 shown.
Attention rank: #68 of 372 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 252 days after the earliest competitor.
- Make every bug perfectly reproducible · hn · 2026-06-20 · 13 upvotes · similarity 0.56
- Give your coding agent production bug context · hn · 2025-11-13 · 5 upvotes · similarity 0.51
- Faylee · ph · 2026-10-30 · 102 upvotes · similarity 0.47
- KeelTest · hn · 2026-01-07 · 30 upvotes · similarity 0.47
- Loopedin Labs · ph · 2026-10-28 · 1 upvotes · similarity 0.47
- Replay QA · ph · 2026-07-20 · 415 upvotes · similarity 0.47
- BugSpray · ph · 2026-11-06 · 1 upvotes · similarity 0.47
- heal.dev · ph · 2026-10-22 · 195 upvotes · similarity 0.46
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