We're all learning how to ship more side projects. If you're "in the bubble" it can feel like everyone is repo-maxxing. Shipping weekly. Spinning up agents to scaffold full apps overnight. New OSS dropped every Friday. The reality I see with most developers is much more normal: They have six or seven repos sitting in various states of half-attention. A side project from last year that still gets a
Becoming a tech lead was the goal from pretty early in my career. I had a clear picture of what the role was. More responsibility, more influence over the work, more of the interesting problems landing on my desk because someone had to figure them out and that someone, finally, would be me. It read like the natural next step. The thing you graduate to once you're good enough. What that picture did
Hey dev.to community! I just launched CodeLens AI — an AI-powered code review tool that automatically reviews every pull request. Connect your GitHub repo Open a PR AI automatically reviews the code Detailed review comment posted on PR Bugs and logic errors SQL injection and security vulnerabilities Performance issues Code quality improvements Next.js + TypeScript NextAuth + GitHub OAuth Supabase
I use AI coding agents every day. I believe they are reshaping how we build software, and I think the teams that adopt them deliberately will outperform those that don't. I am not writing this to warn you away from AI-assisted development. I am writing this because the loudest voices in the AI enthusiasm camp are also the most allergic to discussing what can go wrong. And that worries me more than
Why We Open-Sourced Our AI Safety Layer When we built the AI safety layer for As You Wish (AYW), we faced a choice: keep it proprietary or open-source it to help the community. Here's why we chose the latter (and why it made our platform stronger). If you're building AI-assisted development tools, you need: Input validation (sanitizing prompts, preventing injection) Output filtering (catching u
If you want to Automate GitHub PRs, the real goal is not just adding another bot comment to a pull request. The goal is to give reviewers the context they usually have to gather manually: who owns the service, whether it is deployed, whether basic repository standards are in place, and whether the change looks safe to merge. A useful AI pull request workflow can do exactly that. When a PR opens, i
How I Used GitHub Actions to Auto-Publish to AMO on Every Release Manually uploading extension files to AMO (Mozilla's Add-On Observatory) is tedious. After the fifth time forgetting to increment the version number, I automated it with GitHub Actions. Here's exactly how I set up the pipeline for the Weather & Clock Dashboard extension. Trigger on new GitHub release Validate the manifest version
AI can write code. Good code. Clean code. Fast code. That doesn’t make development trivial. It shifts where the true value lives. When code was slow and expensive, writing it was the work. Decisions developed gradually. Architecture changed over time. Judgment was distributed throughout implementation. When the cost of code drops, that balance flips. The difficult part is no longer creating softwa