frontpage.
newsnewestaskshowjobs

Made with ♥ by @iamnishanth

Open Source @Github

fp.

Show HN: Paper Arena – A social trading feed where only AI agents can post

https://paperinvest.io/arena
1•andrenorman•53s ago•0 comments

TOSTracker – The AI Training Asymmetry

https://tostracker.app/analysis/ai-training
1•tldrthelaw•4m ago•0 comments

The Devil Inside GitHub

https://blog.melashri.net/micro/github-devil/
2•elashri•5m ago•0 comments

Show HN: Distill – Migrate LLM agents from expensive to cheap models

https://github.com/ricardomoratomateos/distill
1•ricardomorato•5m ago•0 comments

Show HN: Sigma Runtime – Maintaining 100% Fact Integrity over 120 LLM Cycles

https://github.com/sigmastratum/documentation/tree/main/sigma-runtime/SR-053
1•teugent•5m ago•0 comments

Make a local open-source AI chatbot with access to Fedora documentation

https://fedoramagazine.org/how-to-make-a-local-open-source-ai-chatbot-who-has-access-to-fedora-do...
1•jadedtuna•6m ago•0 comments

Introduce the Vouch/Denouncement Contribution Model by Mitchellh

https://github.com/ghostty-org/ghostty/pull/10559
1•samtrack2019•7m ago•0 comments

Software Factories and the Agentic Moment

https://factory.strongdm.ai/
1•mellosouls•7m ago•1 comments

The Neuroscience Behind Nutrition for Developers and Founders

https://comuniq.xyz/post?t=797
1•01-_-•7m ago•0 comments

Bang bang he murdered math {the musical } (2024)

https://taylor.town/bang-bang
1•surprisetalk•7m ago•0 comments

A Night Without the Nerds – Claude Opus 4.6, Field-Tested

https://konfuzio.com/en/a-night-without-the-nerds-claude-opus-4-6-in-the-field-test/
1•konfuzio•10m ago•0 comments

Could ionospheric disturbances influence earthquakes?

https://www.kyoto-u.ac.jp/en/research-news/2026-02-06-0
2•geox•11m ago•1 comments

SpaceX's next astronaut launch for NASA is officially on for Feb. 11 as FAA clea

https://www.space.com/space-exploration/launches-spacecraft/spacexs-next-astronaut-launch-for-nas...
1•bookmtn•13m ago•0 comments

Show HN: One-click AI employee with its own cloud desktop

https://cloudbot-ai.com
1•fainir•15m ago•0 comments

Show HN: Poddley – Search podcasts by who's speaking

https://poddley.com
1•onesandofgrain•16m ago•0 comments

Same Surface, Different Weight

https://www.robpanico.com/articles/display/?entry_short=same-surface-different-weight
1•retrocog•18m ago•0 comments

The Rise of Spec Driven Development

https://www.dbreunig.com/2026/02/06/the-rise-of-spec-driven-development.html
2•Brajeshwar•22m ago•0 comments

The first good Raspberry Pi Laptop

https://www.jeffgeerling.com/blog/2026/the-first-good-raspberry-pi-laptop/
3•Brajeshwar•22m ago•0 comments

Seas to Rise Around the World – But Not in Greenland

https://e360.yale.edu/digest/greenland-sea-levels-fall
2•Brajeshwar•22m ago•0 comments

Will Future Generations Think We're Gross?

https://chillphysicsenjoyer.substack.com/p/will-future-generations-think-were
1•crescit_eundo•26m ago•1 comments

State Department will delete Xitter posts from before Trump returned to office

https://www.npr.org/2026/02/07/nx-s1-5704785/state-department-trump-posts-x
2•righthand•29m ago•1 comments

Show HN: Verifiable server roundtrip demo for a decision interruption system

https://github.com/veeduzyl-hue/decision-assistant-roundtrip-demo
1•veeduzyl•30m ago•0 comments

Impl Rust – Avro IDL Tool in Rust via Antlr

https://www.youtube.com/watch?v=vmKvw73V394
1•todsacerdoti•30m ago•0 comments

Stories from 25 Years of Software Development

https://susam.net/twenty-five-years-of-computing.html
3•vinhnx•31m ago•0 comments

minikeyvalue

https://github.com/commaai/minikeyvalue/tree/prod
3•tosh•35m ago•0 comments

Neomacs: GPU-accelerated Emacs with inline video, WebKit, and terminal via wgpu

https://github.com/eval-exec/neomacs
1•evalexec•40m ago•0 comments

Show HN: Moli P2P – An ephemeral, serverless image gallery (Rust and WebRTC)

https://moli-green.is/
2•ShinyaKoyano•44m ago•1 comments

How I grow my X presence?

https://www.reddit.com/r/GrowthHacking/s/UEc8pAl61b
2•m00dy•46m ago•0 comments

What's the cost of the most expensive Super Bowl ad slot?

https://ballparkguess.com/?id=5b98b1d3-5887-47b9-8a92-43be2ced674b
1•bkls•46m ago•0 comments

What if you just did a startup instead?

https://alexaraki.substack.com/p/what-if-you-just-did-a-startup
5•okaywriting•53m ago•0 comments
Open in hackernews

Show HN: AI agents that validate your product idea by talking to real users

https://app.holyshift.ai/ai/project
7•Matzalar•2mo ago
I built a tool to solve a problem I kept running into: I was making product decisions based on guessing instead of real users. I kept building stuff nobody wanted as I was usually wrong.

So, I built HolyShift: AI agents that validate product ideas by talking to real people on Reddit, HN, X, and LinkedIn … then generate a detailed GTM and “Should we build this?” report.

No synthetic data (ChatGPT). No predictions. Only real conversations from real people.

What it does • Posts platform-native questions (where allowed) • Collects real reactions, objections, pricing signals • Clusters feedback into themes (pain, demand, adoption, pricing …) • Runs a monitoring agent for sentiment analysis • Produces a short validation report (PRD + GTM)

All actions are rate limited and reviewed by a human for compliance.

How it works (technicals) • Multi-agent pipeline (intake → landscape → engagement → monitoring → synthesis → report) • Platform specific prompting (HN vs Reddit vs LinkedIn …) • Real-time sentiment + clustering via embeddings

Link https://www.holyshift.ai (Early beta)

What I’m looking for • What should stay human vs automated? Should we automate this 100%? • How do you do your product validation? Do you talk to your potential users (and who?) before you build?

Happy to answer anything.

Comments

lovrok23•2mo ago
I'm curious about the guardrails here. In my experience trying to use LLMs for user research, they tend to be "yes man" often hallucinating features or agreeing to user requests that aren't actually on the roadmap just to keep the conversation flowing.

how do you constrain the agent to stick strictly to the facts of the product hypothesis without making stuff up to please the potential customer?

Matzalar•2mo ago
We ran into the same issue early on. Our fix was to lock each agent to a small JSON snapshot of the idea (no other knowledge), plus strict response templates. They can only ask questions, never describe features or promise anything. If a user asks for something outside scope, the agent replies with “not in the current hypothesis, why is that important to you?” rather than making stuff up. We also have a human review step before anything goes live.
KurSix•2mo ago
If you have human review for every action, then this isn't scalable software, it's consulting. Either you'll eventually remove this step for scale (and get banned by platforms), or your product will have to be very expensive (to pay for the reviewers' time). Maybe it's worth keeping AI only for the analysis part and leaving the communication to humans?
likethejade87•2mo ago
Are agent pitching ideas or do actual research? Sounds super interesting though
Matzalar•2mo ago
They’re not pitching or selling anything they only do research. The agents ask structured questions in relevant communities and collect real reactions, pain points, objections ... No selling, no marketing language.
tene80i•2mo ago
Interesting idea. Nice design. But usability issue: on mobile I hit your yellow chat CTA thinking it was submitting the app text input. You might want to move that out of the way.
Matzalar•2mo ago
Good point. Thanks for your suggestion. We’re very early, a lot is changing as we move on and get more feedback.
thebiggodzzila•2mo ago
Chat always boosts my confidence, but reality isn’t always as kind. How can I really tell if my idea is any good beyond what Chat says, and how many people do you actually interact with?
Matzalar•2mo ago
Chat is OK at making anything sound promising, but it will not talk to real people and give you the real market signals. We do both, we do the “synthetic” data analysis, but more importantly we talk to real people and ask them what they think. Depending on the product (or project), we’ll usually get few hundred real interactions. The goal is to get enough real, unfiltered feedback to see whether there’s a consistent signal to make a decision.
KurSix•2mo ago
The irony is that people give the most honest and unfiltered feedback when no one is asking them. When a bot approaches a user (even a research one), the observer effect kicks in, and answers often become more polite or socially desirable. Analyzing historical threads where people are just complaining to each other often yields a much more accurate and "raw" pain signal than direct questioning. There, people aren't trying to be nice to your agent.
KurSix•2mo ago
The idea of validation on real data is great. But why post questions directly? It's risky and intrusive. It would be much safer and more powerful to simply passively observe. Have agents scan the thousands of existing threads where people are already complaining about problems. You'll get honest data without risking being banned. People have already told you their problems, you just need to (automatically) listen, not ask again
_demo•2mo ago
Cool idea I have seen this people having this same problem so many times in the past.. The biggest risk I see is how do you know if people responding are providing actually usefull feedback or just garbage that will hurt me in the long run?