Robert Hommes’ Post

I just launched Inspectly.dev a free toolbox for developers 🚀 👉 https://inspectly.dev/ Built to simplify everyday dev tasks in one place: • JSON Debugger format & validate with smart error detection • API Tester test APIs with code generation • Regex Tester real-time pattern testing • JWT Analyzer decode & verify tokens • Timestamp Converter instant timezone conversion • GraphQL Playground schema explorer + autocomplete • Code Converter cURL ⇄ code ⇄ SQL • Mock Data Generator realistic test data • HTTP Headers Analyzer security + CORS insights • WebSocket/SSE Debugger real-time inspection • Log Analyzer detect patterns instantly No login. No setup. Just fast tools ⚡ Would love your feedback 🙌

https://lnkd.in/eS26_HqT Polling drains resources and WebSockets can be a nightmare to manage. This article covers a pattern for syncing client-side state through a custom hook and backend service that manages event queuing, so your users get real-time progress updates without the lag or infrastructure cost. i explore the technicalities in this article

Every API call returns a status code… But most developers only know 200 & 404. Here’s a simple breakdown of HTTP status codes you should actually understand.

Early Codex CLI observations, compared with Claude Code * Token limits are muuuuuch more generous, oh my goodness night and day * Plan mode seems strong based on limited interactions * Agents are super clunky compared to Claude Code. - Must be triggered explicitly - I triggered one and Codex got impatient and did the work in parallel, defeating the purpose. Had to create some global guidance about that which should be baked in by default - Agents also seem slower than in CC * Restore session and generous permissions mode (yolo / auto) work well * Rewinding session controls are clunky, and you can only rewind to the most recent session restore. Lame. * So far the models seem really good for development tasks. Early days, but they seem pretty functional. I'm basically slowly rebuilding my Claude Arcanum open source library as a Arcanum-for-Codex open source library with the same tools. I'm a little anxious how feasible my hybrid skill/agent workflows will work. We'll see how it goes.

Better performance, plus far better debugging and observability at the transport layer, all thanks to Rust. We built an alternative QUIC and HTTP/3 backend for the NGINX web server using quiche, the Rust-based library. Our solution lets us switch between the native implementation and the quiche-based backend while adapting connection establishment, stream lifecycle management, or connection migration. This gives us a lot more control than just relying on the server’s default behavior, and lets us fine-tune things such as congestion control algorithms based on what actually makes sense for real CDN traffic. The implementation involved modifying the NGINX components responsible for QUIC connection and packet handling, without changing the overall HTTP/3 request processing model. The result is not just better performance, but also a safer implementation and much better debugging and observability, whether we’re digging into issues using qlog/keylog or testing HTTP/3 edge cases.

localsandbox now supports tools within code execution Heavily inspired by Cloudflare's codemode and DSPy (Community) RLM - this gives your sandbox agents the ability to programmatically explore and call tools. Rather than spamming the context window with every tool definition and tool result, let your agent decide how to compose the tools and manage its own context!

Most browser-based scraping projects don’t break all at once. They slowly get harder to run. A script that worked fine last week starts behaving inconsistently, sessions clash, results vary, and things fail in ways that are difficult to reproduce. The bigger you scale, the worse it gets. That’s exactly the kind of problem we’ve been working through with rayobrowse. Our latest update (v0.1.33) focuses on making large-scale browser workloads more stable and easier to operate in production: 🔵 Support for multiple Chromium versions (including v146), so you’re not locked to a single browser build or caught out by updates 🔵 Improvements to canvas + ClientRect handling, making browser output more consistent and realistic 🔵 Hardened Docker setup (non-root user, sandboxing, improved security config) for safer production deployments Plus a number of smaller updates around performance, debugging, and reliability. We’re already running this at scale internally, and each release is about making that experience more predictable and easier for others to replicate. If you’ve ever wrestled with browser automation, you’ll know why this matters. Read more here: https://bit.ly/3PNnOtL

🚨Breaking : THIS CLI PROXY CUTS YOUR CLAUDE CODE TOKEN USAGE BY 60-90% it sits between Claude Code and your terminal. when Claude runs a command, the proxy strips all the noise from the output before sending it back. normal terminal output is full of junk Claude doesn't need. progress bars, warnings, formatting, verbose logs. all of that eats tokens. this tool filters it down to just the information Claude actually needs to do its job 10M tokens saved across sessions with 89% reduction AND its just a single Rust binary with zero dependencies plus its open source if your usage limits have been burning faster than expected, a huge chunk of that is Claude reading terminal output it doesn't even use. this fixes that

Raw HTTP gives you a status code and a body. That’s it. No standard shape, no consistent error format, no metadata. Left to their own devices, teams end up with endpoints that return wildly different structures. Response wrappers establish a single contract for your entire API surface.

Just launched a new project — JAMA 🚀 It’s a full-stack web app I built to monitor website availability and response times, with a clean dashboard-style interface. The goal was to create something that blends both IT/networking concepts with full-stack development in a practical way. One thing I found really interesting while building this is using AI prompting as a development tool. With the right prompts and direction, I was able to go from idea → working product in just a few hours. It didn’t replace understanding the code, but it definitely accelerated the process and helped me focus on building and learning faster. From a technical side, this project touches a lot of areas I’ve been focusing on: React + Node/Express full-stack development API design and real-time data handling Networking concepts like latency and availability Deployment using GitHub Pages (frontend) and Render (backend) It was also a good reminder of how important it is to actually ship projects and not just build locally, but get them live and working across real environments. This is just the starting point. I’m planning to expand JAMA into more of a full network diagnostics and monitoring tool over time. If you want to check it out: 🔗 https://lnkd.in/epxDJAaS Would love any feedback 👍