🔄 Migration Tools

Format Conversion, Legacy System Bridging, Automated Translation, Preservation Workflows

<p>Just for the record, I&rsquo;m not going to stop using em dashes just because LLMs use them too. But to proove my authenticity, I&rsquo;ll occasionally use &...
lmika.org·14h
🖋Typography
Running River as a systemd service
devork.be·1d
⚙️WASM Runtime
Using Radicle CI for Development
blog.liw.fi·3d
🌳Git Internals
Comparison of Tribblix and Other Illumos Distributions
tribblix.org·18h·
Discuss: Hacker News
🔌Operating system internals
Embedded Systems Roadmap: Bridging the Gap
interrupt.memfault.com·1d·
Discuss: Hacker News, r/embedded
🦀Embedded Rust
Top Trends in Endpoint Management in 2025
techradar.com·1d
🔌Interface Evolution
Serverless single tenant RAG with DuckDB
summer.io·2d·
Discuss: Hacker News
📰Feed Readers
Intel to throw networking biz over the side of its rapidly shrinking ship
theregister.com·15h
🧲RISC-V Archaeology
HA OTel in Kubernetes - practical demo
reddit.com·1d·
Discuss: r/kubernetes
📦Container Security
Smart Routing Saved Exa 90% on LLM Costs
inference.net·3d·
Discuss: Hacker News
🌀Brotli Internals
Python Fundamentals: click
dev.to·3d·
Discuss: DEV
💧Liquid Types
AI Ticket Summarizer: How to Add AI Features to Your Web or SaaS App (Without Training a Model)
dev.to·1d·
Discuss: DEV
🌊Streaming Systems
Python Fundamentals: cloudpickle
dev.to·2d·
Discuss: DEV
💧Liquid Types
We Built An Entire Newsroom with LLMs – Then We Showed The Print To the Real One
medium.com·3d·
Discuss: Hacker News
📋Document Layout
Code-Buddy
dev.to·2h·
Discuss: DEV
🎙️Whisper
Scoping Freelance Dev Projects with GPT: My Workflow
dev.to·18h·
Discuss: DEV
⚙️Batch Processing
Which CMPs Are Most Recommended by Developers and Site Owners?
dev.to·2d·
Discuss: DEV
💾Persistence Strategies
🔄 Introducing Galus: A Lightweight and Blazing-Fast Live Reload Tool for Go Developers
dev.to·2h·
Discuss: DEV
🔄Reproducible Builds
Incentivised Orchestrated Training Architecture (IOTA): A Technical Primer for Release
arxiv.org·1d
🌊Streaming Systems
A Supervised Machine Learning Framework for Multipactor Breakdown Prediction in High-Power Radio Frequency Devices and Accelerator Components: A Case Study in P...
arxiv.org·1d
🧠Machine Learning