HN Showcase
Back to browse
AutoBrief – Generate post-incident briefs from a structured form

AutoBrief – Generate post-incident briefs from a structured form

by SoloShipper·Feb 25, 2026·2 points·0 comments
Visit ProjectView on HN

AI Analysis

●●SolidSolve My ProblemSlick

One form, four outputs—replaces messy Slack threads with audience-specific incident docs.

Strengths
  • •Genuinely addresses real friction: incident writing (hours) after resolution (minutes) is a known bottleneck in incident review.
  • •Thoughtful design: application-layer encryption, Postgres RLS isolation, no model training on incident data—privacy taken seriously.
  • •Clean, functional product with clear UX; free tier removes barrier to experimentation; API-based stack (Supabase, Claude) is maintainable.
Weaknesses
  • •Claude dependency means no offline operation or model flexibility; latency/cost tied to API provider.
  • •Solves a real problem but in a well-served space (incident management); Opsgenie, PagerDuty, and internal wikis already partially address this.
Category
SaaS
Target Audience

SREs, DevOps engineers, incident commanders, on-call teams at mid-to-large companies

Similar To

Opsgenie (incident alerting + response) · PagerDuty (incident lifecycle) · Rundeck (runbook automation)

Post Description

Hi HN,

I built AutoBrief after noticing that resolving incidents wasn’t the longest part — writing about them was.

After every incident we would write: • An engineering postmortem • An executive summary • A status page update • Runbook changes

Same incident, multiple documents.

AutoBrief lets you fill out one structured form (timeline, impact, root cause, mitigation, uncertainties) and generates tailored drafts for each audience.

A few design decisions: • Sensitive fields encrypted at the application layer • Workspace isolation using Postgres RLS • Incident data is not used to train AI models • Meant as a draft accelerator, not a replacement for review

Stack: Next.js 15, Supabase (Postgres + RLS), Claude API, deployed on Vercel.

I’d especially appreciate feedback from engineers who run incident reviews. Would this reduce overhead in your workflow, or just add another tool?

Similar Projects

SaaS●●Solid

A "content compiler" that turns LLM output into validated artifacts

Treating LLM output like compiler input — with typed style guides, required-section enforcement, and explicit Confidence/LostElements on transformations — is a clever, non-obvious approach that could actually raise the signal-to-noise on generated content. The product shows useful practical features (export to PDF/HTML/JSON, jurisdiction-aware legal drafting, slide generation), but the real test will be how maintainable and authorable those rule sets are in messy, real-world workflows.

Big BrainBold Bet
hardikparikh29
103mo ago
Developer Tools●●Solid

Everdone CodeSecurity and CodePerformance

The product's real selling point is the iterative verification loop: AI inspects PRs/branches, surfaces exploitable issues with file+line and severity, and then re-runs reviews to confirm fixes — that workflow (Open → In Progress → Resolved → Closed/Rejected) is practical and would reduce issues slipping through. Promising as a unified place for docs, review, security and perf, but success depends heavily on low false-positive rates and transparent evidence for security findings; without that, it risks feeling like another noisy scanner.

SlickSolve My Problem
vinitmaniar
103mo ago