Fennec Engineering has obtained certification confirming that its automated traceability platform meets strict safety standards. The post Fennec Engineering earns T2 qualification for Advanced Safety Acceleration Platform appeared first on The Robot Report .
This article is an honest account of the process on why I built a custom AI assistant instead of just paying for one, what the architecture looks like, the actual code, what broke, and what it does now that I genuinely rely on.
Autonomique has moved its AI-powered robots from pilot to production at F&P Mfg., with plans for deployment across F-tech's global network. The post Autonomique deploys semi-humanoid robots and AI at Canadian Tier 1 appeared first on The Robot Report .
I built AptSelect to stop writing throwaway scripts every time I needed to test how different LLMs handle specific instructions and prompt edge cases. What it does: Parallel Execution: Send a single prompt to OpenAI, Anthropic, Mistral, and Gemini simultaneously. Compare the outputs, latency, and exact token usage side-by-side. Batch Evaluations: Upload a CSV dataset to run bulk tests across multiple models at once. Manual Diagnostics: Grade outputs manually (Pass/Fail) and assign diagnostic tag
Antigravity CLI is the newest agentic coding CLI from Google, replacing the now-deprecated Gemini CLI. It inherits the asynchronous subagent model that makes Antigravity stand out from the field, syncs bidirectionally with Antigravity Desktop, and is optimized for speed on Gemini 3.5 Flash. DataRobot ships a full plugin for Antigravity CLI directly from the same... The post DataRobot for Developers — integrating with the Google Antigravity CLI appeared first on DataRobot .
Article URL: https://ai-growth.pplx.app/ Comments URL: https://news.ycombinator.com/item?id=48570660 Points: 2 # Comments: 1
Hi, just call me alessandro for now. i never used hacker news. or twitter to write about thing. But im genuinely struggling for my startup. I have many products in line but focused on few. At this point im just self funded and delusional. If i ever to make a new social media then yea i can create a platform in few week with or without ai, everyone can do that. In this pov, if im mark then I need eduardo. or if i were to create something like apple then i can be wozniak then i need steve. Either
AutomatiQ is an Open-Source Reverse-Engineering AI Agent, that can write requests-based(no browser) automation/scraper scripts on its own, all we have to do is, to normally browse the website once. This makes it a lot easier to create/fix scripts, all we have to is browse the site. This is not a completely autonomous agent, you can pause, talk, guide the agent on its RE path, just like a normal agent. I am aware of the limitations of this approach, but from my own research(please refer the blog
Accuracy isn’t enough—agencies must detect when trusted AI misuses legitimate access. Enter: AI counterintelligence.
Hi HN, we posted here back in April and the most common request was to make the source code public. As of today, ctx is now open-source: https://github.com/ctxrs/ctx ctx is an Agentic Development Environment (ADE), similar to the Codex desktop app, but it works with any agent harness. I wrote more about why we are open sourcing it here: https://ctx.rs/blog/open-sourcing-ctx A few things contributed to the decision to do this: - We fell in love with Pi's extensibility model. In late 2025, we were
<p> Automatic customer context for product teams and agents. </p> <p> <a href="https://www.producthunt.com/products/propane?utm_campaign=producthunt-atom-posts-feed&utm_medium=rss-feed&utm_source=producthunt-atom-posts-feed">Discussion</a> | <a href="https://www.producthunt.com/r/p/1174350?app_id=339">Link</a> </p>
Article URL: https://www.runagentrun.co.uk/articles/how-we-built-an-agent-run-news-site/ Comments URL: https://news.ycombinator.com/item?id=48570480 Points: 1 # Comments: 0
Article URL: https://www.ruxu.dev/articles/ai/build-an-ai-agent-human-in-the-loop-security/ Comments URL: https://news.ycombinator.com/item?id=48570377 Points: 1 # Comments: 0
"GRID" (Gaps, Risks, Inconsistencies, Discrepancies) is a small framework that I developed over time for my spec-driven development using coding agents. Comments URL: https://news.ycombinator.com/item?id=48570337 Points: 1 # Comments: 0
AI is pretty reliable at putting things on your calendar these days, but it hasn't quite cracked answering the related and all-important question of "What should I do this weekend?" Meta's new AI Mode in search could be a useful tool - if it ever learns to stop getting stuff wrong. AI Mode is a […]
Most LLM applications need a clear workflow, not an autonomous agent. Here's how to build one in plain Python. The post You Probably Don’t Need an Agent Framework appeared first on Towards Data Science .
Article URL: https://resources.kusho.ai/openapi-spec-analyzer Comments URL: https://news.ycombinator.com/item?id=48570226 Points: 4 # Comments: 2
I have a couple of personal app ideas that need simple cloud storage. I was hoping Claude/Codex would be able to help me put something basic together quickly, but I've been underwhelmed by tech stack suggestions they tend to suggest. They either push solutions that don't really fit (claude suggested claude artifacts) or are overkill for a single person app (e.g. "firebase + tauri + sveltekit"). Curious what stack people are using for personal projects/tools. Comments URL: https://news.ycombinato
Hey HN, I'm Jay, co-creator of Mira. An open-source, self-hosted AI code reviewer where you BYOK (bring your own key). Local models are getting really good. Hosted frontier models are getting really expensive. So, we built Mira. Mira has some snazzy features too: - It's really fast at reviewing. Average is 77s compared with Greptile's 5 minutes. Your PRs aren't going into a queue on a cloud somewhere. - Mira performs a blast radius and see what damage will be done with code change. - Learns your
Article URL: https://www.strangeloopcanon.com/p/llm-councils-show-groupthink Comments URL: https://news.ycombinator.com/item?id=48570090 Points: 3 # Comments: 0
Richard Sutton’s “Bitter Lesson” is usually read as a warning against building too much human knowledge into AI systems. Over the long run, the methods that win are not the ones that encode our clever intuition most directly, but the ones that scale: search, learning, and other general methods that can absorb more compute and data. Modern foundation model pre-training looks, at first glance, like a triumph of that lesson. We take a general architecture, expose it to massive data, and train it wi
Comments URL: https://news.ycombinator.com/item?id=48569970 Points: 3 # Comments: 4
Now that everyone and their little cousin can make apps - the next biggest hurdle is distribution for PMF validation/iterations. Besides the plethora of spammy solutions via automated personalized email and LinkedIn campaigns (which has existed ~20yrs now) what new agentic solutions are showing promise for bootstrapped startups? Comments URL: https://news.ycombinator.com/item?id=48569969 Points: 1 # Comments: 0
Hi HN, for the past few months, we’ve been working on Ferrix AI ( https://ferrix.ai/ ) As AI agents speed up engineering, deciding what to build has become the bottleneck. Developers got faster because agents fit into their workflow: tech design, code review, testing. They still make the key decisions, while AI handles mechanical work around them. At Ferrix, we are automating workflow for product managers to make product decisions efficiently. Agents handle the research synthesis, spec writing,
Sanctuary AI is not waiting for humanoid robots; it's applying physical AI to demonstrate production-ready performance. The post Sanctuary AI validates physical AI performance at Tier 1 automotive supplier appeared first on The Robot Report .
<p>An AI tool is no replacement for a doctor, and regulation is essential. But together, physicians and AI could prove beneficial</p><p>A calf cramp should not be a brush with death. Mine almost was.</p><p>For five days, I had what felt like a stubborn muscle spasm in my left calf. It was tender, swollen and getting worse. I assumed it was a muscle problem and went to my chiropractor, who treated it as a muscle issue.</p><p>Gleb Tsipursky, PhD, serves as the CEO of the future-of-work work consul
The Cloudflare One stack is a library of agent skills that gives any AI agent the knowledge it needs to plan, deploy, and manage a Zero Trust environment — no migration calls required.
'The Hum' has been one of the most perplexing unsolved mysteries. ScienceAlert stories are written, fact-checked, and edited by humans, never generated by AI. Don't miss a story, subscribe here.
The new Google Home Speaker was made with Gemini in mind, and can take natural-language commands.
Arriving six years after Google’s last smart speaker, the new HomePod-style device was redesigned to play host to Gemini’s chatbot.
Upgrades include 360-degree audio and deeper integration with Google's Gemini.
The Canadian pension giant will acquire an 8.2% stake in CtrlS, a tech giant that operates more than 15 data centers across India.
Article URL: https://northwoodsystems.ai/blog/ai-token-economics Comments URL: https://news.ycombinator.com/item?id=48569539 Points: 3 # Comments: 0
I tried the new Siri on my Mac, and although it's off to a promising start, Apple still has more work to do.
On April 19, 2026, the Honor Lightning humanoid robot ran a half-marathon in 50 minutes and 26 seconds , beating the human world record by 7 minutes and the best robot time from 2025 by almost two hours. How did they do it? Is there some magical technology or technique that unlocked this performance? How did they beat the significantly better-known Unitree (who reportedly had to supply an ice backpack to try and complete the race without overheating)? My doctoral thesis involved building and con
Smart mowers are an expensive alternative to old-fashioned yard work, but they’re finally good enough to consider if you’d rather sip an iced tea and watch a robot tame your lawn.
Learn Codex by building small and practical projects step by step.
Enterprise Document Intelligence [Vol.1 #6b] - The five field families the parser reads straight from the user’s question, with the code that fills each one The post What the Question Parser Extracts from a User String: Keywords, Scope, Shape, Decomposition, Clarification appeared first on Towards Data Science .
Article URL: https://notaru.ai Comments URL: https://news.ycombinator.com/item?id=48568987 Points: 7 # Comments: 1
