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Want to tap into the energy of 1,100+ startup founders, investors, and tech leaders descending on Boston for the Founder Summit 2026 on June 9? Host your own Side Event during “Founder Summit Week,” happening June 4-10!
Apple is working on a feature that will allow users in the European Union to copy content on their iPhone and paste it onto their Windows PC (or vice versa), as spotted earlier by MacRumors. The move comes in response to an interoperability request from Microsoft that asks Apple to open up its Universal Clipboard […]
AI systems can change without the code changing. That makes “is this correct?” a much harder question. I talked with Diana Pfeil about evals, input drift, prompt versioning, model deprecations, and the maintenance work hiding behind all this new capability. Curious how teams here are handling it in production. https://maintainable.fm/episodes/diana-pfeil-building-confidence-in-probabilistic-systems submitted by /u/robbyrussell [link] [留言]
Surely nobody you know will overuse this...
It’s time for yet another giveaway. We raided The Verge’s closet full of tech in New York City to stuff as much can fit into a Nomatic Messenger Bag. It’s overstuffed, to say the least, and if you’re chosen as the winner of this sweepstakes on August 18th, the bag and its contents (valued at […]
Notably, the company saw its subscriber base swell by 9% in the second quarter despite raising prices in several regions this year.
“We do not have, nor want, any of their trade secrets,” the ChatGPT maker says.
The legislation lays the groundwork for a potential overhaul of India's zero-merchant-discount-rate regime, under which businesses have not paid fees to accept UPI payments since 2020.
Condensation plus electronics are a bad combo.
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I have 312 docs in my personal knowledge DB. Tweets, arxiv abstracts, Zenn articles, blog posts, YouTube transcripts. Claude Code writes to it, reads from it, and cites out of it every day. That number is not a brag. It is the reason I finally have data on which retrieval strategy holds up in an LLM-native workflow. I tried four. The one I ship is the one I tried last and expected to lose. Three of the four broke in ways that are worth naming, because the broken versions are what most tutorials will tell you to build. The setup, so we agree on what got benchmarked The knowledge DB is called context-forge internally. It is a folder, some markdown files, and a SQLite table. Claude Code adds to it via CLI, searches via CLI, and reads the underlying markdown directly when it needs the full text. It took eight hours to build the CLI, three months to accumulate the 312 documents at a pace of one to five per day, and about 15 minutes a day of my time to keep it flowing. Each doc has metadata: source URL, a credibility score 1-5, one to three categories, a short summary. The autoregistration pipeline is Claude Code itself: I paste a URL, it fetches, summarizes, scores, categorizes, writes the markdown, commits, and updates the SQLite index. The pipeline is not the interesting part. The retrieval strategy is. I ran each of the four strategies for two weeks against the same day-to-day tasks: writing a chapter, answering "what did that person say about X," and building an argument for a decision. Same me, same DB, different retriever. Layer 1: pure semantic RAG (vector embeddings). Broke at 200 docs The first version was the textbook answer. Embed every document with a sentence transformer, store the vectors in SQLite with a similarity index, retrieve the top-k on every query. This is the pattern Silicon Slopes covers for code-level RAG and Anthropic itself has an issue open for a built-in version . It worked at 50 docs. It worked at 100. Around 200 documents it started retrie