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Showing 381–400 of 6085 tools
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July 17, 2026 at 12:00 PM
The circuit that lets your brain think and see
Hacker News (score: 12)The circuit that lets your brain think and see
David Potter, the man who put Psion in the palm of your hand, logs off at 82
Hacker News (score: 12)David Potter, the man who put Psion in the palm of your hand, logs off at 82
GitFut β Your GitHub stats turned into a World-Cup-style player card
Hacker News (score: 33)GitFut β Your GitHub stats turned into a World-Cup-style player card
Why Vancouver is always a stand-in for San Francisco in movies and TV shows (2021)
Hacker News (score: 21)Why Vancouver is always a stand-in for San Francisco in movies and TV shows (2021)
Software, from First Principles
Hacker News (score: 14)Software, from First Principles
Show HN: ContextCodeCache in Rust
Show HN (score: 8)Show HN: ContextCodeCache in Rust
Show HN: How clanker are you? A reverse Turing test
Show HN (score: 5)Show HN: How clanker are you? A reverse Turing test You write 8 text completions and open models score how predictable each word was too them. Predictable => clanker. You can share results with your friends.<p>The scoring checks every word you write against the model's logprobs. Right now I'm using Llama3.1, Deepseek v3 and Qwen3 to keep costs low. I tried to calibrate it so other models (chatgpt/claude) score 100% and interesting human responses score in the 10-30% range.<p>Totally free, no signup
Giving a domain a hill to climb: benchmarking as data activation
Hacker News (score: 10)Giving a domain a hill to climb: benchmarking as data activation
Kagi Changelog (July 2): Heads, tails, and an AI toggle
Hacker News (score: 50)Kagi Changelog (July 2): Heads, tails, and an AI toggle
Egypt Is Building a New Nile
Hacker News (score: 83)Egypt Is Building a New Nile
Meta reuses old RAM in new servers with custom bridge chip
Hacker News (score: 291)Meta reuses old RAM in new servers with custom bridge chip <a href="https://aisystemcodesign.github.io/papers/isca26/vistara_camera_ready.pdf" rel="nofollow">https://aisystemcodesign.github.io/papers/isca26/vistara_cam...</a>
Show HN: Kontext β Move an AI chat's full context to another AI in one click
Show HN: StillUpTo β Keep track of the side projects if they are still alive
Show HN: Opbox β CRDT based sync for text files on disk
Show HN (score: 8)Show HN: Opbox β CRDT based sync for text files on disk Hi! Iβm one of the founders of s2.dev, and recently have been hacking on opbox, which is an open-source daemon that turns directories of text files (code, markdown, etc) into collaborative, multi-player workspaces.<p>This started as a bit of an intellectual curiosity, to see if it was possible to do real-time sync at the filesystem level (i.e., in an editor-agnostic way).<p>The idea is pretty simple:<p><pre><code> - Opbox workspaces are roughly analogous to git repositories (and can be used alongside existing git repos, to share live changes between commits) - When the opbox daemon is running in a workspace (ob start), it listens for local filesystem events within its directory (writes, deletes, new files), and translates them into operations (the titular βopβ) on shadow CRDT documents (Yrs) corresponding to each text file (as well as one doc for the namespace as a whole, which handles paths) - These shadow CRDT docs are maintained in a workspace-local sqlite db (Turso) - The ops, which represent diffs on a corresponding CRDT document, are then appended to a durable stream (S2) that acts as a shared journal for all sync participants - Opbox also reads from that journal, receiving ops from other participants, which are then used to update the local documents, first in the db, then by materializing them into actual files on disk </code></pre> This has worked surprisingly well for sharing things like Obsidian graphs in real-time.<p>Itβs most helpful in cases where you want the ability to edit local files from arbitrary editors, but still collaborate live. The experience is best from editors where you can configure an aggressive autosave policy, and where edits to an open file are reflected in the editor in a timely way.<p>To gain confidence in the correctness of the core opbox flows (particularly all the nuances around bidirectional sync) I invested in wiring up deterministic simulation testing using the turmoil library, which has been incredibly helpful (see the opbox-sim crate in the repo).
Show HN: Dockside β I turned unused space around the macOS Dock into a workspace
Show HN (score: 5)Show HN: Dockside β I turned unused space around the macOS Dock into a workspace
Show HN: Pull Claude Code transcripts into your Codex session, and vice versa Hi HN, I'm Rob. Contextify indexes every Claude Code and Codex session on your machine into one local, searchable database. The current session, in either tool, can search all of it: /total-recall in Claude Code, $total-recall in Codex.<p>Demo: <a href="https://www.youtube.com/watch?v=FvrvRGp4C9M" rel="nofollow">https://www.youtube.com/watch?v=FvrvRGp4C9M</a> | Mac app: <a href="https://contextify.sh" rel="nofollow">https://contextify.sh</a> (App Store or DMG) | Linux: CLI with a one-line installer, same search. No signup.<p>I split my work between Claude Code and Codex. When I burn through rate limits on one, I switch to the other, and new models keep leapfrogging each other, so the switching is not going away.<p>But each tool keeps its own history, in its own format, in its own directory structure, and Claude Code deletes local transcripts after 30 days by default.<p>Piecing together work I had done across Claude Code and Codex on one machine is the problem Contextify started as.<p>How it works: the Mac app (or a systemd timer on Linux) watches ~/.claude/projects/ and ~/.codex/sessions/, parses each tool's transcript format, and ingests every turn into SQLite with full-text search.<p>My DB is currently at 366,734 entries across 13,920 sessions, pooled from two Macs. An entry is one turn: a message, tool call, or subagent step.<p>A CLI (contextify search / context / activity) sits on top, and bundled skills (/total-recall, /live-recall) teach each agent to use it on demand mid-session. There is also an MCP server (contextify serve-mcp) if you'd rather use that.<p>On macOS, summaries are generated on-device by Apple Intelligence. By default your transcripts and entry database stay on your machine.<p>I use more than one laptop, and found I would often want to reference prior work that I did on one computer that I did not have in my local database.<p>To solve this, I built Contextify Cloud: opt-in sync that pools each machine's entries, so a search from the laptop I'm on also finds work I did on the other one.<p>Hosted sync is paid, $12/mo. It is free if you self-host the sync server, keeping the pooled database on infrastructure you control. The server is source-available under the Functional Source License.<p>The same pooling works for workgroups on a per-seat commercial license, hosted or self-hosted: teammates' shared projects become searchable across the group, each result labeled with who did the work, and sharing is per-project, so each member decides what the group sees.<p>What it's not: the Mac app is not open source, Windows is not supported, and Gemini CLI, Pi, and OpenCode are not ingested yet (all are planned). Free for personal use; using it for work is $8/mo.<p>I'd love to hear how you handle history across more than one coding agent.
Show HN: Origin Myth Map-creation myths of civilizations on a world map
Show HN (score: 5)Show HN: Origin Myth Map-creation myths of civilizations on a world map I've always been fascinated by origin myths, and by how civilizations had similar origin stories. The flood myth is the famous example (Mesopotamia, Genesis, India, the Americas).
60% Fable cost cut by converting code to images and having the model OCR it
Hacker News (score: 123)60% Fable cost cut by converting code to images and having the model OCR it
Jamesob's guide to running SOTA LLMs locally
Hacker News (score: 17)Jamesob's guide to running SOTA LLMs locally
AI coding is addictive. Engineers are paying the price
Hacker News (score: 10)AI coding is addictive. Engineers are paying the price