Insights on coding agents, user feedback, and building what matters.
A user submits a support ticket. Three sprints later, someone builds something adjacent to what they asked for. What if the entire pipeline — from ticket to shipped code — happened in one sprint? Here's how.
Read more →Sprint planning fails because priorities are guesses, feedback is stale, and user signals get lost in translation. Here's how AI-powered feedback loops fix the pipeline from user voice to shipped code.
Read more →Your NPS surveys collect gold — feature requests, pain points, churn signals. Your coding agent never sees any of it. Here's how to automatically route NPS insights into your development workflow.
Read more →Cursor, Copilot, and Claude Code are incredibly powerful — but they're building in a vacuum. Here's how to feed real user signals into your coding agent's context so it stops guessing and starts solving real problems.
Read more →A team's AI coding agent spent three weeks building a perfectly engineered feature that no user wanted. The real bug wasn't in the code — it was in the feedback loop. Here's the $50K lesson.
Read more →Cursor, Claude Code, and Copilot write amazing code — but they're building in the dark. They have access to code, docs, and tickets, but not to what users are actually saying. The feedback loop is broken.
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