Bug Tracking in the AI Era
Why we built FeedbackFalcon and how AI is changing the way we fix software.
Updates, thoughts, and essays on building the next generation of developer tools.
Why we built FeedbackFalcon and how AI is changing the way we fix software.
The technical and privacy benefits of isolating agency data into separate SQLite files using Golang.
A look at the numbers behind our pricing strategy and why we abandoned the seat-based model.
Why knowing the OS and browser isn't enough. How capturing sanitized LocalStorage fixes the problem.
Reducing friction during the User Acceptance Testing phase using falconer.js.
How manual CSV exports cause data silos and formatting errors, and why real-time sync is the future.
Why paying per-task on middleware eats into margins, and why native integrations work better.
How silent 500 errors and CORS failures cause bugs that clients can't articulate.
Why capturing the A11y tree helps LLMs understand web pages better than raw HTML.
AI can write code fast, but it struggles to fix bugs if it can't see the client's local environment.
A technical guide to monkey-patching console.error in the Main World of a Chrome Extension.
How to use our MCP server to pull network logs, app state, and DOM trees straight into your editor.
Understanding the Model Context Protocol and how it helps AI agents connect to existing tools.
Why raw DOM paths break instantly, and why AI coding agents need semantic context instead.
How per-seat pricing models increase friction for agencies growing their freelance teams.
Bring the context of a bug report directly into Cursor or Windsurf with our new integration.