A couple of months ago, I was copy-pasting prompts into ChatGPT. Now I'm shipping features, running tests, managing branches, and keeping documentation alive, with a team of agents doing the heavy lifting. All by myself.
Legacy codebases are messy, undocumented, and full of decisions nobody remembers making. But if you can explain it to a new developer, you can onboard an AI and that changes everything.
Agile was supposed to free us from bureaucracy. Many teams just rebuilt it with better branding. Now, AI-driven development is forcing the uncomfortable question: Were we ever truly agile, or just managing slow feedback loops?
This is Part 2 of Bots and Boundaries, a three-part series on AI agents in open source.
Go for one codebase or multiple repositories? A question multiple CTOs and technical founders have asked. It can be a surprisingly expensive decision nobody warns you about.
Performance bugs erode trust quietly until users explode. Three pragmatic steps help you catch slowdowns early: explore real bottlenecks with Sentry, test with production-sized data, and add lightweight API load tests.
I recently encountered a issue with MySQL query performance. A particular query would perform very badly in production, but perform very well in the testing environments.
The most common mistake in mobile product launches is assuming the app store submission process is routine. It isn’t. From mismatched requirements between Apple and Google to last-minute policy changes, this is where launch plans unravel.
Tired of git blame pointing to useless formatting commits? Learn how to ignore revisions with --ignore-rev or .git-blame-ignore-revs to keep Git history accurate and helpful.