The Indie Founder Bug-to-Shipped-Fix Playbook
Capture, triage, and ship bug fixes without a QA team
Built for solo founders running live SaaS products who drown in Slack screenshots and vague user complaints. This playbook turns any bug report into a triaged spec, diagnosed root cause, and shipped fix — without a QA engineer or product manager. Go from 'it's broken' to merged PR in one focused session.
Goal
Capture user-reported bugs, auto-triage them, diagnose root causes, and ship fixes fast
Who this is for
Solo SaaS founders running live products with real users and no QA team
When to use
When bugs are piling up in Slack, email, or user reports and you need a systematic fix pipeline
When NOT to use
Pre-launch or pre-user — use a simpler testing checklist instead
How to set it up
Install the bug capture widget
Embed the IssueCapture widget on your live app. Configure it to auto-attach screenshots, browser info, and user context. Connect it to your Jira or JSM project so every report lands triaged.
Auto-generate a fix spec from the bug report
When a bug lands in Jira, use SpecSource to pull in the related Sentry error, GitHub history, and any Slack mentions. Let it write a structured fix spec with repro steps and expected behaviour.
Diagnose the root cause
Run Kelet against your LLM app logs or API traces for the failing session. It will identify the exact failure point and suggest a remediation path, so you skip manual log archaeology.
Write the fix in Cursor
Open the relevant file in Cursor with your spec and Kelet diagnosis in context. Use inline AI to write the patch, iterating until the fix matches the expected behaviour from your spec.
Review and merge the PR
Push the fix and open a PR. Use Stage to break the diff into logical review chapters. Verify nothing regressed, approve, and merge with confidence.
AI-powered bug capture widget for Jira with smart triaging and screenshots
Embeds a widget in your app so users report bugs with screenshots and auto-generates triaged Jira issues, cutting the back-and-forth out of every report.
AI diagnoses and fixes failures in LLM apps and agents in production
Diagnoses why a failure happened in your LLM app or backend and surfaces the exact fix, saving hours of log-diving on every incident.
Auto-generate detailed specs from Sentry, GitHub, and Slack errors
Pulls the triaged bug into a detailed fix spec automatically from your Sentry errors and GitHub context so you start coding with full clarity.
Write and iterate on the bug fix inside an AI-first editor that understands your codebase context and suggests patches inline.
AI code review that organizes pull requests into logical chapters for clarity
Organises the bug-fix PR into logical chapters so you can review your own changes clearly before merging, catching regressions you'd otherwise miss.
Expected outcome
A live bug capture widget, automatic Jira triage, AI root cause diagnosis, and a code fix reviewed and merged same day
Related playbooks
The Indie Founder Spec-to-Shipped Feature Playbook
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The AI-Assisted Code Review Playbook
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The Solo Founder Upwork Pipeline Playbook
Win more Upwork contracts and deliver client work faster by automating proposals, communications, and reporting so you spend more time on billable work.
The Solo SaaS Playbook
Launch a revenue-generating SaaS product solo by combining AI-assisted development, automation, and streamlined customer communication — without hiring engineers or assistants.
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