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
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
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
If this is useful, a ❤️ helps others find it. I debug Rust and TypeScript code daily. I've used all three major AI APIs for this — Gemini, Claude, and GPT-4. Here's the honest comparison for code debugging specifically. Not benchmarks. Actual use. I ran the same 5 bugs through each model: A Rust borrow checker error with async context A React state update causing infinite re-render An Android logc
If this is useful, a ❤️ helps others find it. I've shipped 7 Mac apps in the past year. Every AI feature in them runs on free tools. Here's the exact stack — what I use, why, and where the limits are. What: Gemini 2.5 Flash Preview via REST API Cost: Free tier — 500 requests/day, no credit card Use for: Log diagnosis, document analysis, text classification, anything needing strong reasoning The fr
If this is useful, a ❤️ helps others find it. Everything I keep looking up when building with Gemini — in one place. Model Context Best for gemini-2.5-flash-preview 1M tokens General use, thinking, fast gemini-2.5-pro-preview 1M tokens Complex reasoning, best quality gemini-1.5-flash 1M tokens Stable, production-ready gemini-1.5-pro 2M tokens Longest context gemini-2.0-flash-lite 1M