by yokuze ·
Since coding agents have become more capable, I often have them working on 2-5 disparate tasks simultaneously during my work day. The tasks are often in separate or even unrelated repos. Or worse, sometimes the tasks are similar enough that they are easily mixed-up.
Much of my attention goes to switching: Checking on results, restarting stopped tasks, fixing errors or providing hints, etc.
The context-switching takes a toll in the form of distraction and inefficiency.
What do you do that helps with this?
I built devday because I use multiple AI coding tools (OpenCode, Claude Code, Cursor) and wanted a single command to see what I actually accomplished each day. It reads local session data, cross-references with git commits, and optionally generates standup-ready summaries via OpenAI or Anthropic.
Everything runs locally — no data leaves your machine unless you opt into LLM summaries.
Install with npm install -g devday.
Currently supports OpenCode, Claude Code, and Cursor on macOS. Would love feedback on what other tools to support.
Hi Everyone,
I created a mobile app called Accumoo and submitted it to the app store, and I would appreciate it if y'all can have a look, download and give me a favorable rating and review. Lots of blood, sweat, tears and love went into this app, and I hope you LOVE it as much as I do - it's the app I always needed and wanted. Anyhow, I've been a Rails developer and Software Engineer for a long time, and this is my first stab at a mobile app. It's a "habit tracker" app on steroids that's just fun to use - syncs across devices, local-first architecture - and an easter egg game for good measure.
Help a disabled vet out and give it a go!
Thank you for your support. GA
by whisprer ·
I’ve built a fully cross-platform SIMD-accelerated C++ pseudo-random number generation library designed for real-world deployment (Windows, Linux, macOS).
Repository: https://github.com/whisprer/c-simd-rng-lib/
The goal was to solve a practical gap:
Most high-performance SIMD RNG implementations are either:
academic prototypes
single-architecture
non-portable
incomplete
or not packaged for real deployment
This library provides:
• AVX2 / AVX-512 accelerated paths (with graceful fallback) • Deterministic, reproducible streams • Clean API surface • Zero external runtime dependencies • Works across Win / Linux / macOS • Production-ready build setup
In bulk generation scenarios it significantly outperforms std::mt19937 and standard <random> engines, and benchmarks competitively (or faster) than other SIMD-enabled RNG libraries.
A separate benchmarking repository contains:
• Full comparison suite • Competing library benchmarks • Throughput numbers • Architectural breakdowns • Methodology + raw results
Benchmark repo: https://github.com/whisprer/benchmark/
The focus is high-throughput generation for simulations, Monte Carlo, procedural systems, and statistical workloads where large batches matter more than single draws.
Interested in feedback from folks working in HPC, simulation, game engines, or scientific computing.
This comes after the recently added command autowiring:cache.