Sunday, February 22, 2026
Saturday, February 21, 2026
Friday, February 20, 2026
Thursday, February 19, 2026
Wednesday, February 18, 2026
Tuesday, February 17, 2026
Monday, February 16, 2026
New top story on Hacker News: Show HN: Nerve: Stitches all your data sources into one mega-API
Show HN: Nerve: Stitches all your data sources into one mega-API
3 by mprast | 0 comments on Hacker News.
Hi HN! Nerve is a solo project I've been working on for the last few years. It's a developer tool that stitches together data from multiple sources in real-time. A lot of high-leverage projects (AI or otherwise) involve tying data together from multiple systems of record. This is easy enough when the data is simple and the sources are few, but if you have highly nested data and lots of sources (or you need things like federated pagination and filtering), you have to write a lot of gnarly boilerplate that's brittle and easy to get wrong. One solution is to import all your data into a central warehouse and just pull it from there. This works, but 1) you need a warehouse, 2) you have an extra copy of the data that can get stale or inconsistent, 3) you need to write and manage pipelines/connectors (or outsource them to a vendor), and 4) you're adding an extra point of failure. Nerve lets you write GraphQL-style queries that span multiple sources; then it goes out and pulls from whatever source APIs it needs to at query-time - all your source data stays where it is. Nerve has pre-built bindings to external SAAS services, and it's straightforward to hook it into your internal sources as well. Nerve is made for individual developers or two-pizza teams who: -Are building agents/internal tools -Need to deal with messy data strewn across different systems -Don't have a data team/warehouse at their disposal, (or do, but can't get a slice of their bandwidth) -Want to get to production as quickly as possible Everything you see in the demo is shipped and usable, but I'm adding a little polish before I officially launch. In the meantime, if you have a project you'd like to use Nerve on and you want to be a beta user, just drop me a line at mprast@get-nerve.com (it's free! I'll just pop in from time to time to ask you how it's going and what I can improve :) ) If you want to get an email when Nerve is ready from prime-time, you can sign up for the waitlist at get-nerve.com. Thanks for reading!
3 by mprast | 0 comments on Hacker News.
Hi HN! Nerve is a solo project I've been working on for the last few years. It's a developer tool that stitches together data from multiple sources in real-time. A lot of high-leverage projects (AI or otherwise) involve tying data together from multiple systems of record. This is easy enough when the data is simple and the sources are few, but if you have highly nested data and lots of sources (or you need things like federated pagination and filtering), you have to write a lot of gnarly boilerplate that's brittle and easy to get wrong. One solution is to import all your data into a central warehouse and just pull it from there. This works, but 1) you need a warehouse, 2) you have an extra copy of the data that can get stale or inconsistent, 3) you need to write and manage pipelines/connectors (or outsource them to a vendor), and 4) you're adding an extra point of failure. Nerve lets you write GraphQL-style queries that span multiple sources; then it goes out and pulls from whatever source APIs it needs to at query-time - all your source data stays where it is. Nerve has pre-built bindings to external SAAS services, and it's straightforward to hook it into your internal sources as well. Nerve is made for individual developers or two-pizza teams who: -Are building agents/internal tools -Need to deal with messy data strewn across different systems -Don't have a data team/warehouse at their disposal, (or do, but can't get a slice of their bandwidth) -Want to get to production as quickly as possible Everything you see in the demo is shipped and usable, but I'm adding a little polish before I officially launch. In the meantime, if you have a project you'd like to use Nerve on and you want to be a beta user, just drop me a line at mprast@get-nerve.com (it's free! I'll just pop in from time to time to ask you how it's going and what I can improve :) ) If you want to get an email when Nerve is ready from prime-time, you can sign up for the waitlist at get-nerve.com. Thanks for reading!
Sunday, February 15, 2026
New top story on Hacker News: Show HN: Knock-Knock.net – Visualizing the bots knocking on my server's door
Show HN: Knock-Knock.net – Visualizing the bots knocking on my server's door
17 by djkurlander | 7 comments on Hacker News.
17 by djkurlander | 7 comments on Hacker News.
New top story on Hacker News: Scientists observe a 300M-year-old brain rhythm in several animal species
Scientists observe a 300M-year-old brain rhythm in several animal species
7 by PaulHoule | 0 comments on Hacker News.
7 by PaulHoule | 0 comments on Hacker News.
Saturday, February 14, 2026
Friday, February 13, 2026
New top story on Hacker News: Show HN: Moltis – AI assistant with memory, tools, and self-extending skills
Show HN: Moltis – AI assistant with memory, tools, and self-extending skills
10 by fabienpenso | 2 comments on Hacker News.
Hey HN. I'm Fabien, principal engineer, 25 years shipping production systems (Ruby, Swift, now Rust). I built Moltis because I wanted an AI assistant I could run myself, trust end to end, and make extensible in the Rust way using traits and the type system. It shares some ideas with OpenClaw (same memory approach, Pi-inspired self-extension) but is Rust-native from the ground up. The agent can create its own skills at runtime. Moltis is one Rust binary, 150k lines, ~60MB, web UI included. No Node, no Python, no runtime deps. Multi-provider LLM routing (OpenAI, local GGUF/MLX, Hugging Face), sandboxed execution (Docker/Podman/Apple Containers), hybrid vector + full-text memory, MCP tool servers with auto-restart, and multi-channel (web, Telegram, API) with shared context. MIT licensed. No telemetry phoning home, but full observability built in (OpenTelemetry, Prometheus). I've included 1-click deploys on DigitalOcean and Fly.io, but since a Docker image is provided you can easily run it on your own servers as well. I've written before about owning your content ( https://ift.tt/Ega43jT ) and owning your email ( https://ift.tt/zjw75IJ ). Same logic here: if something touches your files, credentials, and daily workflow, you should be able to inspect it, audit it, and fork it if the project changes direction. It's alpha. I use it daily and I'm shipping because it's useful, not because it's done. Longer architecture deep-dive: https://ift.tt/EqlH2xW... Happy to discuss the Rust architecture, security model, or local LLM setup. Would love feedback.
10 by fabienpenso | 2 comments on Hacker News.
Hey HN. I'm Fabien, principal engineer, 25 years shipping production systems (Ruby, Swift, now Rust). I built Moltis because I wanted an AI assistant I could run myself, trust end to end, and make extensible in the Rust way using traits and the type system. It shares some ideas with OpenClaw (same memory approach, Pi-inspired self-extension) but is Rust-native from the ground up. The agent can create its own skills at runtime. Moltis is one Rust binary, 150k lines, ~60MB, web UI included. No Node, no Python, no runtime deps. Multi-provider LLM routing (OpenAI, local GGUF/MLX, Hugging Face), sandboxed execution (Docker/Podman/Apple Containers), hybrid vector + full-text memory, MCP tool servers with auto-restart, and multi-channel (web, Telegram, API) with shared context. MIT licensed. No telemetry phoning home, but full observability built in (OpenTelemetry, Prometheus). I've included 1-click deploys on DigitalOcean and Fly.io, but since a Docker image is provided you can easily run it on your own servers as well. I've written before about owning your content ( https://ift.tt/Ega43jT ) and owning your email ( https://ift.tt/zjw75IJ ). Same logic here: if something touches your files, credentials, and daily workflow, you should be able to inspect it, audit it, and fork it if the project changes direction. It's alpha. I use it daily and I'm shipping because it's useful, not because it's done. Longer architecture deep-dive: https://ift.tt/EqlH2xW... Happy to discuss the Rust architecture, security model, or local LLM setup. Would love feedback.
Thursday, February 12, 2026
New top story on Hacker News: Show HN: Pgclaw – A "Clawdbot" in every row with 400 lines of Postgres SQL
Show HN: Pgclaw – A "Clawdbot" in every row with 400 lines of Postgres SQL
9 by calebhwin | 6 comments on Hacker News.
Hi HN, Been hacking on a simple way to run agents entirely inside of a Postgres database, "an agent per row". Things you could build with this: * Your own agent orchestrator * A personal assistant with time travel * (more things I can't think of yet) Not quite there yet but thought I'd share it in its current state.
9 by calebhwin | 6 comments on Hacker News.
Hi HN, Been hacking on a simple way to run agents entirely inside of a Postgres database, "an agent per row". Things you could build with this: * Your own agent orchestrator * A personal assistant with time travel * (more things I can't think of yet) Not quite there yet but thought I'd share it in its current state.
Wednesday, February 11, 2026
Tuesday, February 10, 2026
New top story on Hacker News: Show HN: HN Companion – web app that enhances the experience of reading HN
Show HN: HN Companion – web app that enhances the experience of reading HN
10 by georgeck | 2 comments on Hacker News.
HN is all about the rich discussions. We wanted to take the HN experience one step further - to bring the familiar keyboard-first navigation, find interesting viewpoints in the threads and get a gist of long threads so that we can decide which rabbit holes to explore. So we built HN Companion a year ago, and have been refining it ever since. Try it: https://ift.tt/xfLv1rp or available as an extension for Firefox / Chrome: [0]. Most AI summarization strips the voices from conversations by flattening threads into a wall of text. This kills the joy of reading HN discussions. Instead, HN Companion works differently - it understands the thread hierarchy, the voting patterns and contrasting viewpoints - everything that makes HN interesting. Think of it like clustering related discussions across multiple hierarchies into a group and surfacing the comments that represent each cluster. It keeps the verbatim text with backlinks so that you never lose context and can continue the conversation from that point. Here is how the summarization works under the hood [1]. We first built this as an open source browser extension. But soon we learned that people hesitate to install it. So we built the same experience as a web app with all the features. This helped people see how it works, and use it on mobile too (in the browser or as PWA). This is now a playground to try new features before taking them to the browser extension. We did a Show HN a year ago [2] and we have added these features based on user feedback: * cached summaries - summaries are generated and cached on our servers. This improved the speed significantly. You still have the option to use your own API key or use local models through Ollama. * our system prompt is available in the Settings page of the extension. You can customize it as you wish. * sort the posts in the feed pages (/home, /show etc.) based on points, comments, time or the default sorting order. * We tried fine tuning an open weights model to summarize, but learned that with a good system prompt and user prompt, the frontier models deliver results of similar quality. So we didn’t use the fine-tuned model, but you can run them locally. The browser extension does not track any usage or analytics. The code is open source[3]. We want to continue to improve HN Companion, specifically add features like following an author, notes about an author, draft posts etc. See it in action for a post here https://ift.tt/BDGO6bJ We would love to get your feedback on what would make this more useful for your HN reading. [0] https://ift.tt/6cVvBh3 [1] https://ift.tt/hejxazP [2] https://ift.tt/I2KSTly [3] https://ift.tt/qxC1rR5
10 by georgeck | 2 comments on Hacker News.
HN is all about the rich discussions. We wanted to take the HN experience one step further - to bring the familiar keyboard-first navigation, find interesting viewpoints in the threads and get a gist of long threads so that we can decide which rabbit holes to explore. So we built HN Companion a year ago, and have been refining it ever since. Try it: https://ift.tt/xfLv1rp or available as an extension for Firefox / Chrome: [0]. Most AI summarization strips the voices from conversations by flattening threads into a wall of text. This kills the joy of reading HN discussions. Instead, HN Companion works differently - it understands the thread hierarchy, the voting patterns and contrasting viewpoints - everything that makes HN interesting. Think of it like clustering related discussions across multiple hierarchies into a group and surfacing the comments that represent each cluster. It keeps the verbatim text with backlinks so that you never lose context and can continue the conversation from that point. Here is how the summarization works under the hood [1]. We first built this as an open source browser extension. But soon we learned that people hesitate to install it. So we built the same experience as a web app with all the features. This helped people see how it works, and use it on mobile too (in the browser or as PWA). This is now a playground to try new features before taking them to the browser extension. We did a Show HN a year ago [2] and we have added these features based on user feedback: * cached summaries - summaries are generated and cached on our servers. This improved the speed significantly. You still have the option to use your own API key or use local models through Ollama. * our system prompt is available in the Settings page of the extension. You can customize it as you wish. * sort the posts in the feed pages (/home, /show etc.) based on points, comments, time or the default sorting order. * We tried fine tuning an open weights model to summarize, but learned that with a good system prompt and user prompt, the frontier models deliver results of similar quality. So we didn’t use the fine-tuned model, but you can run them locally. The browser extension does not track any usage or analytics. The code is open source[3]. We want to continue to improve HN Companion, specifically add features like following an author, notes about an author, draft posts etc. See it in action for a post here https://ift.tt/BDGO6bJ We would love to get your feedback on what would make this more useful for your HN reading. [0] https://ift.tt/6cVvBh3 [1] https://ift.tt/hejxazP [2] https://ift.tt/I2KSTly [3] https://ift.tt/qxC1rR5
Monday, February 9, 2026
Sunday, February 8, 2026
Saturday, February 7, 2026
Friday, February 6, 2026
Thursday, February 5, 2026
Wednesday, February 4, 2026
Tuesday, February 3, 2026
New top story on Hacker News: Show HN: PII-Shield – Log Sanitization Sidecar with JSON Integrity (Go, Entropy)
Show HN: PII-Shield – Log Sanitization Sidecar with JSON Integrity (Go, Entropy)
7 by aragoss | 2 comments on Hacker News.
What PII-Shield does: It's a K8s sidecar (or CLI tool) that pipes application logs, detects secrets using Shannon entropy (catching unknown keys like "sk-live-..." without predefined patterns), and redacts them deterministically using HMAC. Why deterministic? So that "pass123" always hashes to the same "[HIDDEN:a1b2c]", allowing QA/Devs to correlate errors without seeing the raw data. Key features: 1. JSON Integrity: It parses JSON, sanitizes values, and rebuilds it. It guarantees valid JSON output for your SIEM (ELK/Datadog). 2. Entropy Detection: Uses context-aware entropy analysis to catch high-randomness strings. 3. Fail-Open: Designed as a transparent pipe wrapper to preserve app uptime. The project is open-source (Apache 2.0). Repo: https://ift.tt/qrKRv4E Docs: https://pii-shield.gitbook.io/docs/ I'd love your feedback on the entropy/threshold logic!
7 by aragoss | 2 comments on Hacker News.
What PII-Shield does: It's a K8s sidecar (or CLI tool) that pipes application logs, detects secrets using Shannon entropy (catching unknown keys like "sk-live-..." without predefined patterns), and redacts them deterministically using HMAC. Why deterministic? So that "pass123" always hashes to the same "[HIDDEN:a1b2c]", allowing QA/Devs to correlate errors without seeing the raw data. Key features: 1. JSON Integrity: It parses JSON, sanitizes values, and rebuilds it. It guarantees valid JSON output for your SIEM (ELK/Datadog). 2. Entropy Detection: Uses context-aware entropy analysis to catch high-randomness strings. 3. Fail-Open: Designed as a transparent pipe wrapper to preserve app uptime. The project is open-source (Apache 2.0). Repo: https://ift.tt/qrKRv4E Docs: https://pii-shield.gitbook.io/docs/ I'd love your feedback on the entropy/threshold logic!