The personal site and blog of a Toronto-based open source developer known for Amfora, a terminal browser for the Gemini protocol, and for image dithering tools (dither, didder, Dithertime). Posts cover small-internet protocols, open source projects, voting systems, and software design. Free to read.
Why I recommend it: A good example of the "small web" corner of the internet: one person, useful open source tools, thoughtful writing. Follow if you are interested in protocols and software outside the big platforms.
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An open-source engine for serving large language models with high throughput and efficient memory use. Its PagedAttention approach helps reduce wasted GPU memory during inference.
The methodology page for the TIOBE Programming Community Index, a monthly measure of programming language popularity calculated from search engine result counts for queries like "+<language> programming." The page explains which search engines qualify, which languages are included, and how ratings are calculated. The current index is free; long-term historical data is sold.
Why I recommend it: TIOBE measures search chatter, not code quality or job postings — read it as a popularity signal, not a skills roadmap. Pair it with job board data before advising anyone on which language to learn.
A local-first workspace from DXOS combining documents, spreadsheets, tables, and sketches with real-time peer-to-peer collaboration, custom plugins, custom functions, and AI agent workflows. Data syncs between devices without centralized servers. Composer is in early access; the product site and documentation are free.
Why I recommend it: Worth watching if data ownership matters to you or your clients: everything stays on your own devices and syncs peer to peer. It is early access, so expect rough edges before recommending it for daily work.
Blog posts by Iris van Rooij, a cognitive scientist whose writing covers cognition, computation, and critical perspectives on AI claims.
Site of Cal Newport, computer science professor and author of Deep Work, with his long-running blog on focus, productivity, and technology's role in work and life.
InfoQ's report on AX, Google's newly open-sourced system for running fleets of autonomous AI agents. It explains how AX treats each agent as a long-lived task that can be paused and resumed to save computing resources, using control ideas borrowed from Kubernetes.
Why I recommend it: Free to read, though InfoQ asks you to register for some content. The performance claims come from Google's own announcement, so treat them as the company's figures until others test the system.
