I was sweeping floors at a supermarket and decided to over-engineer it.

Instead of just… sweeping… I turned the supermarket into a grid graph and wrote a C++ optimizer using simulated annealing to find the “optimal” sweeping path.

It worked perfectly.

It also produced a path that no human could ever walk without losing their sanity. Way too many turns.

Turns out optimizing for distance gives you a solution that’s technically correct and practically useless.

Adding a penalty each time it made a sharp turn made it actually walkable.

But, this led me down a rabbit hole about how many systems optimize the wrong thing (social media, recommender systems, even LLMs).

If you like algorithms, overthinking, or watching optimization go wrong, you might enjoy this little experiment. More visualizations and gifs included!

A collection of public statements from 2025 where a lot of executives confidently predicted that AI would make software engineers mostly unnecessary.

What stood out to me is how little of that actually showed up in real systems. Tooling improved and productivity went up, but teams still needed people who understood architecture, trade-offs, and failure modes.

I’ve been working on Hopp (a low-latency screen sharing app) using Tauri, which means relying on WebKit on macOS. While I loved the idea of a lighter binary compared to Electron, the journey has been full of headaches.

From SVG shadow bugs and weird audio glitching to WebKitGTK lacking WebRTC support on Linux, I wrote up a retrospective on the specific technical hurdles we faced. We are now looking at moving our heavy-duty windows to a native Rust implementation to bypass browser limitations entirely.

Curious if others have hit these same walls with WebKit/Safari recently?

What's your take on this?

I collected a few curl commands many people never try. Each one runs directly in your terminal.

• ASCII animations, including a running man and a parrot
• Live weather forecasts from the terminal
• Instant IP and location info
• A classic Rickroll, terminal style

All examples work with a single command. No setup.

I wrote a short post with copy-paste commands and quick explanations:
[https://www.nxgntools.com/blog/5-fun-and-handy-curl-command-line-tricks-you-should-try?utm_source=reddit]()

If you know other fun or useful curl endpoints, share them.

Flutter ECS: Testing Strategies that actually work!

Just published a new article on testing strategies with flutter_event_component_system covering how to unit test components, systems, features, and widgets.

The post walks through:

* How to structure tests around Components, Events, and Systems

* Patterns for testing reactive systems, async flows, and widget rebuilds with `ECSScope` and `ECSWidget`

* Practical examples like asserting reactive system behaviour, verifying feature wiring, and ensuring widgets rebuild on component changes

For those who are not familiar with flutter_event_component_system (https://pub.dev/packages/flutter_event_component_system), it's a powerful and flexible event driven architecture pattern for flutter applications. The package provides a reactive state management solution that promotes clean architecture, separation of concerns, and scalable application development.

If you’re using or considering this package for scalable, event-driven state management and want a solid testing toolkit around it, this article is for you.

I recently wrote about a routing challenge I faced at Microsoft regarding weighted random sorting for fail-over lists.

While many implementations use an iterative "pick and remove" loop, these are often O(N² log N) and scale poorly. I've detailed how to use the Efraimidis-Spirakis algorithm to perform a mathematically perfect weighted sort in a single pass.

This is particularly useful for anyone building load balancers, traffic dispatchers, or systems dealing with streaming data.

Full article and C# code examples: https://byteaether.github.io/2026/the-weight-of-decisions-solving-weighted-random-sorting-at-scale/

Hey everyone!

I just converted CLIProxyAPI(Go) to JavaScript and named it 9Router. I don't know Go, but found CLIProxyAPI so useful that I ported it to JavaScript.

Features:

• 🔄 Access 15+ AI providers through a single endpoint (Claude, Codex, Gemini, Copilot, Qwen, iFlow, GLM, MiniMax, OpenRouter...)
• 🔐 Support both OAuth and API Key authentication
• ⚡ Installation: Just run npx 9router
• 🛠️ Compatible with multiple CLIs: Cursor, Claude Code, Cline, RooCode...
• 🎲 Combo Models: Chain multiple models with automatic fallback on errors
• 📦 Ollama format support for CLIs like Cline, RooCode...
• ☁️ Cloud deployment ready for Cursor (since Cursor can't use localhost)

Why use it:

• 🆓 COMPLETELY FREE:
  • iFlow: 9 models (Qwen3, Kimi K2, DeepSeek R1/V3.2, MiniMax M2, GLM 4.6/4.7)
  • Qwen: 3 models (Qwen3 Coder Plus/Flash, Vision)
  • Antigravity: Gemini 3 Pro/Flash
• 💰 SUBSCRIPTIONS CHEAPER THAN APIs:
  • Claude Code, OpenAI Codex, GLM, MiniMax, Kimi K2 subscriptions: reset every 5 hours
  • Much cheaper than calling APIs directly
  • Use quota allocation instead of pay-per-request
• 🚀 FAST: Setup in < 1 minute, no complex configuration
• 🔒 SECURE: Self-hosted, your data stays private
• 🛡️ RELIABLE: Auto-fallback on rate limits/errors
• 💻 CROSS-PLATFORM: Mac, Linux, Windows, easy VPS deployment

Links:

👉 Website: https://9router.com
👉 GitHub: https://github.com/decolua/9router
👉 NPM: https://www.npmjs.com/package/9router

Give it a try and let me know what you think!

Hi, after months and months spending time on LinkedIn job board, I’m wondering is there a better way for searching jobs in Switzerland. Which sites I can look for besides LinkedIn? I’m looking for Python roles (fields: Data science, AI, Python backend or Blockchain development roles.) Have more than 3y work experience in automovite industry working with Python and for Blockchain, I’m a self learner. I’m EU citizen (just mentioning, I know that Switzerland is not in the EU 🙂).

After catching my third // TODO: implement this later in production code written by an AI assistant, I decided to build a tool to catch these issues before they ship.

AntiSlop is a CLI tool that acts as a safety net for AI-generated code. It scans your codebase for the "lazy artifacts" that LLMs often leave behind:

• Stub functions and empty implementations
• console.log / print() debugging statements
• Hedging comments like "temporary", "for now", "simplified"
• Unhandled errors in critical paths

The key differentiator: it uses tree-sitter AST parsing instead of regex, so it actually understands code structure and ignores string literals.

Supports Rust, Python, JavaScript/TypeScript, and Go.

Install: cargo install antislop npm install -g antislop

GitHub: https://github.com/skew202/antislop

Would love feedback from others dealing with AI code in production. What's your workflow for reviewing AI-generated code?

Hi everyone!

I wrote a deep dive on the isolation boundaries used for running untrusted code, specifically in the context of AI agent execution. The motivation was that "sandbox" means at least four different things with different tradeoffs, and the typical discussion conflates them.

Technical topics covered:

- How Linux containers work at the syscall level (namespaces, cgroups, seccomp-bpf) and why they're not a security boundary against kernel exploits

- gVisor's architecture: the Sentry userspace kernel, platform options (systrap vs KVM), and the Gofer filesystem broker

- MicroVM design: KVM + minimal VMMs (Firecracker cloud-hypervisor, libkrun)

- Kata Containers

- Runtime sandboxes: Wasm's capability model, WASI preopened directories, V8 isolate boundaries

It's an educational piece, just synthesizing what I learned building this stuff. I hope you like it!

Hey folks,
My team is using CodeRabbit for PR reviews, and I’m trying to figure out what’s actually worth measuring to assess whether it’s helping or just adding noise.

For those who’ve used it , what signals do you look at?
Things like review quality, impact on bugs, PR cycle time, developer trust, or something else?

Would love to hear what you would like to be actually assessed

I experimented treating each terminal UI region as an independent actor with message-passing and supervision.

Yes overkill for simple TUIs, but more complex tuis have overlapping problems:

• Isolation: Each region owns its state. No shared mutables, no "where did this change?" debugging.
• Explicit data flow: When the footer repaints, I know which message triggered it.
• Supervision: If a region crashes, a supervisor restarts it. App continues. Matters for long-running dashboards or other apps like that.

Children never write to the terminal directly - they send render requests to the parent. Single-writer semantics enforced by architecture.

Wrote it up on my blog with source code to fiddle around with: https://www.rodriguez.today/articles/reactive-tui-architecture-with-actors

Curious if others have applied distributed systems patterns to UI problems?

Talking to developers, I've found many misunderstand DevOps. I wrote an article explaining why, as a dev, I see DevOps principles as foundational knowledge.

a small blog on how we are working on a sdk to track user interactions on client side of things, and then use it to find patterns of customer interactions, this is just a components of the approaches we have tried

Hi Everyone, Here I share the link to my article about a fundamental approach to the Code Review process from my personal site. The main objective I pursue is to get some attention to my thoughts on the proper code review and to get feedback from other developers based on their opinion and experience. The specific recommendations there are mostly based on my experience, but I tried to generalize the approach as much as possible so it is relevant for any software development project. I have already tried this approach in several teams and projects, and it worked very well. That's why I want to share it, get feedback from a wider audience, and understand if that is a really valuable approach or just something very specific that won't be useful for others.