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Show HN: I built a free UCP checker – see if AI agents can find your store

https://ucphub.ai/ucp-store-check/
1•vladeta•4m ago•1 comments

Show HN: SVGV – A Real-Time Vector Video Format for Budget Hardware

https://github.com/thealidev/VectorVision-SVGV
1•thealidev•6m ago•0 comments

Study of 150 developers shows AI generated code no harder to maintain long term

https://www.youtube.com/watch?v=b9EbCb5A408
1•lifeisstillgood•6m ago•0 comments

Spotify now requires premium accounts for developer mode API access

https://www.neowin.net/news/spotify-now-requires-premium-accounts-for-developer-mode-api-access/
1•bundie•9m ago•0 comments

When Albert Einstein Moved to Princeton

https://twitter.com/Math_files/status/2020017485815456224
1•keepamovin•10m ago•0 comments

Agents.md as a Dark Signal

https://joshmock.com/post/2026-agents-md-as-a-dark-signal/
1•birdculture•12m ago•0 comments

System time, clocks, and their syncing in macOS

https://eclecticlight.co/2025/05/21/system-time-clocks-and-their-syncing-in-macos/
1•fanf2•14m ago•0 comments

McCLIM and 7GUIs – Part 1: The Counter

https://turtleware.eu/posts/McCLIM-and-7GUIs---Part-1-The-Counter.html
1•ramenbytes•16m ago•0 comments

So whats the next word, then? Almost-no-math intro to transformer models

https://matthias-kainer.de/blog/posts/so-whats-the-next-word-then-/
1•oesimania•17m ago•0 comments

Ed Zitron: The Hater's Guide to Microsoft

https://bsky.app/profile/edzitron.com/post/3me7ibeym2c2n
2•vintagedave•20m ago•1 comments

UK infants ill after drinking contaminated baby formula of Nestle and Danone

https://www.bbc.com/news/articles/c931rxnwn3lo
1•__natty__•21m ago•0 comments

Show HN: Android-based audio player for seniors – Homer Audio Player

https://homeraudioplayer.app
2•cinusek•21m ago•0 comments

Starter Template for Ory Kratos

https://github.com/Samuelk0nrad/docker-ory
1•samuel_0xK•23m ago•0 comments

LLMs are powerful, but enterprises are deterministic by nature

2•prateekdalal•27m ago•0 comments

Make your iPad 3 a touchscreen for your computer

https://github.com/lemonjesus/ipad-touch-screen
2•0y•32m ago•1 comments

Internationalization and Localization in the Age of Agents

https://myblog.ru/internationalization-and-localization-in-the-age-of-agents
1•xenator•32m ago•0 comments

Building a Custom Clawdbot Workflow to Automate Website Creation

https://seedance2api.org/
1•pekingzcc•35m ago•1 comments

Why the "Taiwan Dome" won't survive a Chinese attack

https://www.lowyinstitute.org/the-interpreter/why-taiwan-dome-won-t-survive-chinese-attack
2•ryan_j_naughton•35m ago•0 comments

Xkcd: Game AIs

https://xkcd.com/1002/
1•ravenical•36m ago•0 comments

Windows 11 is finally killing off legacy printer drivers in 2026

https://www.windowscentral.com/microsoft/windows-11/windows-11-finally-pulls-the-plug-on-legacy-p...
1•ValdikSS•37m ago•0 comments

From Offloading to Engagement (Study on Generative AI)

https://www.mdpi.com/2306-5729/10/11/172
1•boshomi•39m ago•1 comments

AI for People

https://justsitandgrin.im/posts/ai-for-people/
1•dive•40m ago•0 comments

Rome is studded with cannon balls (2022)

https://essenceofrome.com/rome-is-studded-with-cannon-balls
1•thomassmith65•45m ago•0 comments

8-piece tablebase development on Lichess (op1 partial)

https://lichess.org/@/Lichess/blog/op1-partial-8-piece-tablebase-available/1ptPBDpC
2•somethingp•47m ago•0 comments

US to bankroll far-right think tanks in Europe against digital laws

https://www.brusselstimes.com/1957195/us-to-fund-far-right-forces-in-europe-tbtb
4•saubeidl•48m ago•0 comments

Ask HN: Have AI companies replaced their own SaaS usage with agents?

1•tuxpenguine•51m ago•0 comments

pi-nes

https://twitter.com/thomasmustier/status/2018362041506132205
1•tosh•53m ago•0 comments

Show HN: Crew – Multi-agent orchestration tool for AI-assisted development

https://github.com/garnetliu/crew
1•gl2334•53m ago•0 comments

New hire fixed a problem so fast, their boss left to become a yoga instructor

https://www.theregister.com/2026/02/06/on_call/
1•Brajeshwar•54m ago•0 comments

Four horsemen of the AI-pocalypse line up capex bigger than Israel's GDP

https://www.theregister.com/2026/02/06/ai_capex_plans/
1•Brajeshwar•55m ago•0 comments
Open in hackernews

Show HN: First autonomous ML and AI engineering Agent

https://marketplace.visualstudio.com/items?itemName=NeoResearchInc.heyneo
2•svij137•1w ago
Founder here. I built NEO, an AI agent designed specifically for AI and ML engineering workflows, after repeatedly hitting the same wall with existing tools: they work for short, linear tasks, but fall apart once workflows become long-running, stateful, and feedback-driven. In real ML work, you don’t just generate code and move on. You explore data, train models, evaluate results, adjust assumptions, rerun experiments, compare metrics, generate artifacts, and iterate; often over hours or days. Most modern coding agents already go beyond single prompts. They can plan steps, write files, run commands, and react to errors. Where things still break down is when ML workflows become long-running and feedback-heavy. Training jobs, evaluations, retries, metric comparisons, and partial failures are still treated as ephemeral side effects rather than durable state. Once a workflow spans hours, multiple experiments, or iterative evaluation, you either babysit the agent or restart large parts of the process. Feedback exists, but it is not something the system can reliably resume from. NEO tries to model ML work the way it actually happens. It is an AI agent that executes end-to-end ML workflows, not just code generation. Work is broken into explicit execution steps with state, checkpoints, and intermediate results. Feedback from metrics, evaluations, or failures feeds directly into the next step instead of forcing a full restart. You can pause a run, inspect what happened, tweak assumptions, and resume from where it left off. Here's an example as well for your reference: You might ask NEO to explore a dataset, train a few baseline models, compare their performance, and generate plots and a short report. NEO will load the data, run EDA, train models, evaluate them, notice if something underperforms or fails, adjust, and continue. If training takes an hour and one model crashes at 45 minutes, you do not start over. Neo inspects the failure, fixes it, and resumes. Docs for the extension: https://docs.heyneo.so/#/vscode Happy to answer questions about Neo.