Launch HN: Hyper (YC P26) – Company brain to power agentic development
16 by shalinshah | 6 comments on Hacker News.
Hey HN, we’re Shalin & Kanyes, best friends who've been hacking together for 10+yrs, and now founders of Hyper ( https://heyhyper.ai/ ). Hyper is a shared “company brain” that plugs into information flowing inside a company to make AI agents and automations better and ultimately save people time. Models have gotten good enough that they can (mostly) take on long-horizon, complex tasks. We believe the bottleneck now is that these smart-enough models often lack information about your company, which is scattered in people's heads, Slack threads, stale docs, and in back-and-forth convos with AI. MCP is useful for getting some info in front of an agent, but there are problems: (1) Once the session dies, so does the insight, so instead of copy-pasting a whole doc each time you're telling the agent to dig through Drive each time - not much of a win; (2) Even when MCP works, what it gathers isn't comprehensive, because people decide things on a whiteboard, brainstorm out loud, post a little in Slack, and scribble the rest in a doc, which leaves the agent working from partial information; (3) And even if it had everything, it doesn't do the meta-reasoning required to do a great job. If you paste in a Notion doc and it won't learn your design taste or your writing style unless you tell it to, and it won't know why a decision was made or when. As undergrads 5 years ago, we were into the tools-for-thought wave and became power users of Notion, Obsidian, Roam, Anki, real believers in building a second brain. After GPT-3.5 came out we started to realize how much more powerful that second brain could be if an AI could actually read it, because suddenly it would know our backstory, our taste, our preferences, and unlock genuinely new capabilities. That’s why we’re building Hyper. We know it’s not for everybody! But for people who do want to be on the cutting edge, this is a force multiplier that makes agents faster and better. It increases the number of tasks they can do, and how effectively they do them. Hyper works by ingesting everything you give it access to, Docs, Slack, Email, Calendar, Granola, and synthesizes it into a knowledge graph of facts and their relationships with embeddings for semantic search. The memory system we’ve built is hybrid, with two modalities. Episodes are the raw source items kept as the source of truth. Facts are the meaning pulled out of each episode, stored as subject-predicate-object records with a plain summary and timestamps for when the fact was introduced and when it was invalidated (subject=person, predicate=works_at, object=company). Facts form a graph with typed edges between them: X is in tension with Y, A is derived from B, J supersedes K. Every time a new fact comes in we update the facts in its neighborhood, so the graph stays current, and that's how we handle stale information. When "we'll ship Friday" is later contradicted by "we're shipping Monday," the new fact supersedes the old one instead of both looking equally true, and we never auto-discard the superseded version, so you can still ask how you landed on Monday. Every fact carries provenance back to its source and access-control tags for who is allowed to see it. At retrieval we query-expand, then fuse semantic search over embeddings with Postgres full-text search using reciprocal rank fusion, and we only ever evaluate a query against the facts and episodes that person has access to, which means two people on the same team can ask the same question and get different answers. We keep information fresh with webhooks where they exist and polling where they don't, hashing contents to catch changes for sources that don’t handle native dedupe. Agents read and write through two paths: lifecycle hooks in tools like Claude Code, Cowork, Codex, and Cursor, where we inject relevant context on every prompt and pull interesting facts out of every response, and plain MCP tool calls for everything that doesn't expose hooks. We love it! and so do our early users: one CEO uses Hyper to draft emails in his voice with full company context. What took hours/week now takes minutes and gets sharper each time Hyper learns more how he thinks and how his company is changing. Another YC founder one-shotted a launch video script because Hyper already knew their product, voice, positioning accumulated over months. We have a 3-day free trial, explained more on our pricing page ( https://ift.tt/z23S1fc ) and there are more details in our FAQ ( https://heyhyper.ai/faq ), including things like privacy, compliance, and how we’re different from other “memory” companies.. Give it a spin! break it! and tell us where it falls short: https://heyhyper.ai/ . We'd love to build you a 10-star experience :) Comments welcome!
Wednesday, June 3, 2026
Tuesday, June 2, 2026
New top story on Hacker News: Show HN: RePlaya – self-hosted browser session replay with live tailing
Show HN: RePlaya – self-hosted browser session replay with live tailing
4 by shikhar | 0 comments on Hacker News.
Hi HN, I'm one of the founders of s2.dev. RePlaya ( https://ift.tt/6yGE3X5 ) is a self-hosted browser session replay tool using rrweb ( https://ift.tt/2oas0K5 ). It occurred to me that a durable stream per session would be a much neater architectural foundation for much of what you'd want from such a tool. As a unique feature, it also made live tailing straightforward because the player can read from the same stream the recorder is appending to. The alternative architecture is likely an ingest firehose which is then indexed, with associated complexity and latency. You'd have to string together multiple data systems like a message queue, a metadata database, and blob storage and/or an OLAP database. Here the only dependency is S2, which has an open source version you can self-host called s2-lite ( https://ift.tt/LOkswu2 ). How it works: - one S2 stream per browser session - large rrweb events (like a full snapshot) get framed across multiple binary S2 records and reassembled on read - active sessions are tailed with an S2 read session, and bridged to the browser over SSE - session listing relies on stream names encoding reverse timestamps, as S2 returns a lexicographic order listing - relying on fencing tokens so a stopped session can't be written to again by a late recorder - retention and GC are handled via S2 stream config, so no background job needed Curious to hear from folks on the tool or the stream-per-session model!
4 by shikhar | 0 comments on Hacker News.
Hi HN, I'm one of the founders of s2.dev. RePlaya ( https://ift.tt/6yGE3X5 ) is a self-hosted browser session replay tool using rrweb ( https://ift.tt/2oas0K5 ). It occurred to me that a durable stream per session would be a much neater architectural foundation for much of what you'd want from such a tool. As a unique feature, it also made live tailing straightforward because the player can read from the same stream the recorder is appending to. The alternative architecture is likely an ingest firehose which is then indexed, with associated complexity and latency. You'd have to string together multiple data systems like a message queue, a metadata database, and blob storage and/or an OLAP database. Here the only dependency is S2, which has an open source version you can self-host called s2-lite ( https://ift.tt/LOkswu2 ). How it works: - one S2 stream per browser session - large rrweb events (like a full snapshot) get framed across multiple binary S2 records and reassembled on read - active sessions are tailed with an S2 read session, and bridged to the browser over SSE - session listing relies on stream names encoding reverse timestamps, as S2 returns a lexicographic order listing - relying on fencing tokens so a stopped session can't be written to again by a late recorder - retention and GC are handled via S2 stream config, so no background job needed Curious to hear from folks on the tool or the stream-per-session model!
New top story on Hacker News: Trump signs downsized AI order after weeks of reversals
Trump signs downsized AI order after weeks of reversals
33 by _alternator_ | 16 comments on Hacker News.
https://ift.tt/aoGUtEY... https://ift.tt/fR0xvYL...
33 by _alternator_ | 16 comments on Hacker News.
https://ift.tt/aoGUtEY... https://ift.tt/fR0xvYL...
Monday, June 1, 2026
New top story on Hacker News: Superintelligence: The Idea That Eats Smart People (2016)
Superintelligence: The Idea That Eats Smart People (2016)
20 by thoughtpeddler | 3 comments on Hacker News.
20 by thoughtpeddler | 3 comments on Hacker News.