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The end of 'shadow AI' at enterprises? Kilo launches KiloClaw for Organizations to enable secure AI agents at scale
As generative AI matures from a novelty into a workplace staple, a new friction point has emerged: the "shadow AI" or "Bring Your Own AI (BYOAI)" crisis. Much like the unsanctioned use of personal devices in years past, developers and knowledge workers are increasingly deploying autonomous agents on personal infrastructure to manage their professional workflows. "Our journey with Kilo Claw has been to make it easier and easier and more accessible to folks," says Kilo co-founder Scott Breitenother. Today, the company dedicated to providing a portable, multi-model, cloud-based AI coding environment is moving to formalize this "shadow AI" layer: it's launching KiloClaw for Organizations and KiloClaw Chat, a suite of tools designed to provide enterprise-grade governance over personal AI agents. The announcement comes at a period of high velocity for the company. Since making its securely hosted, one-click OpenClaw product for individuals, KiloClaw, generally available last month, more than
The latest AI news we announced in March 2026
Salesforce announces an AI-heavy makeover for Slack, with 30 new features
Models & Gen AI
Meta's new structured prompting technique makes LLMs significantly better at code review — boosting accuracy to 93% in some cases
Deploying AI agents for repository-scale tasks like bug detection, patch verification, and code review requires overcoming significant technical hurdles. One major bottleneck: the need to set up dynamic execution sandboxes for every repository, which are expensive and computationally heavy. Using large language model (LLM) reasoning instead of executing the code is rising in popularity to bypass this overhead, yet it frequently leads to unsupported guesses and hallucinations. To improve execution-free reasoning, researchers at Meta introduce "semi-formal reasoning," a structured prompting technique. This method requires the AI agent to fill out a logical certificate by explicitly stating premises, tracing concrete execution paths, and deriving formal conclusions before providing an answer. The structured format forces the agent to systematically gather evidence and follow function calls before drawing conclusions. This increases the accuracy of LLMs in coding tasks and significantly
OpenAI raises $122B to accelerate the next phase of AI
Article URL: https://openai.com/index/accelerating-the-next-phase-ai/ Comments URL: https://news.ycombinator.com/item?id=47593432 Points: 12 # Comments: 1
I Asked ChatGPT What WIRED’s Reviewers Recommend—Its Answers Were All Wrong
Want to know what our reviewers have actually tested and picked as the best TVs, headphones, and laptops? Ask ChatGPT, and it'll give you the wrong answers.
Runway launches $10M fund, Builders program to support early stage AI startups
Runway is launching a $10 million fund and startup program to back companies building with its AI video models, as it pushes toward interactive, real-time “video intelligence” applications.
Nvidia-backed ThinkLabs AI raises $28 million to tackle a growing power grid crunch
ThinkLabs AI, a startup building artificial intelligence models that simulate the behavior of the electric grid, announced today that it has closed a $28 million Series A financing round led by Energy Impact Partners (EIP), one of the largest energy transition investment firms in the world. Nvidia’s venture capital arm NVentures and Edison International, the parent company of Southern California Edison, also participated in the round. The funding marks a significant escalation in the race to apply AI not just to software and content generation, but to the physical infrastructure that powers modern life. While most AI investment headlines have centered on large language models and generative tools, ThinkLabs is pursuing a different and arguably more consequential application: using physics-informed AI to model the behavior of electrical grids in real time, compressing engineering studies that once took weeks or months into minutes. "We are dead focused on the grid," ThinkLabs CEO Josh W
AI can push your Stream Deck buttons for you
If you're tired of controlling Stream Deck devices by manually pushing buttons, then good news: Elgato will now let you delegate that task to a chatbot instead. The Stream Deck 7.4 software update released today introduces Model Context Protocol (MCP) support, allowing AI assistants like Claude, ChatGPT, and Nvidia G-Assist to find and activate Stream Deck actions on your behalf. "You still set up actions in Stream Deck app the same way you always have. MCP adds a new way to trigger them," Elgato said in its announcement. "Once everything is connected, you can type or speak requests and your AI tool will trigger the matching Stream Deck act … Read the full story at The Verge.
Known Intents, New Combinations: Clause-Factorized Decoding for Compositional Multi-Intent Detection
arXiv:2603.28929v1 Announce Type: new Abstract: Multi-intent detection papers usually ask whether a model can recover multiple intents from one utterance. We ask a harder and, for deployment, more useful question: can it recover new combinations of familiar intents? Existing benchmarks only weakly test this, because train and test often share the same broad co-occurrence patterns. We introduce CoMIX-Shift, a controlled benchmark built to stress compositional generalization in multi-intent detection through held-out intent pairs, discourse-pattern shift, longer and noisier wrappers, held-out clause templates, and zero-shot triples. We also present ClauseCompose, a lightweight decoder trained only on singleton intents, and compare it to whole-utterance baselines including a fine-tuned tiny BERT model. Across three random seeds, ClauseCompose reaches 95.7 exact match on unseen intent pairs, 93.9 on discourse-shifted pairs, 62.5 on longer/noisier pairs, 49.8 on held-out templates, and 91.
Xenv.sh – the first secrets manager built for AI agents
Article URL: https://xenv.sh/ Comments URL: https://news.ycombinator.com/item?id=47593562 Points: 1 # Comments: 0
Midjourney engineer debuts new vibe coded, open source standard Pretext to revolutionize web design
For three decades, the web has existed in a state of architectural denial. It is a platform originally conceived to share static physics papers, yet it is now tasked with rendering the most complex, interactive, and generative interfaces humanity has ever conceived. At the heart of this tension lies a single, invisible, and prohibitively expensive operation known as "layout reflow." Whenever a developer needs to know the height of a paragraph or the position of a line to build a modern interface, they must ask the browser’s Document Object Model (DOM), the standard by which developers can create and modify webpages. In response, the browser often has to recalculate the geometry of the entire page — a process akin to a city being forced to redraw its entire map every time a resident opens their front door. Last Friday, March 27, 2026, Cheng Lou — a prominent software engineer whose work on React, ReScript, and Midjourney has defined much of the modern frontend landscape — announced on
Sandflare – I built a sandbox that launches AI agent VMs in ~300ms
I've been building Sandflare for the past few months — it launches Firecracker microVMs for AI agents in ~300ms cold start. The idea came from running LLM-generated code in production. Docker felt too risky (shared kernel), full VMs too slow (5–10s). Firecracker hits the middle: real VM isolation, fast boot. I also added managed Postgres because almost every agent I built needed persistent state. One call wires a database into a sandbox. There are great tools in this space already (E2B, Modal, Daytona) — I wanted something with batteries-included Postgres, and simpler pricing What I'm trying to figure out: how do I get cold start below 100ms? Currently the bottleneck is the Firecracker API + network setup. Would love to hear from anyone who's pushed Firecracker further. https://sandflare.io Comments URL: https://news.ycombinator.com/item?id=47583255 Points: 2 # Comments: 3
Gradient Labs gives every bank customer an AI account manager
Gradient Labs uses GPT-4.1 and GPT-5.4 mini and nano to power AI agents that automate banking support workflows with low latency and high reliability.
Claude Code leak exposes a Tamagotchi-style ‘pet’ and an always-on agent
After Anthropic released Claude Code's 2.1.88 update, users quickly discovered that it contained a package with a source map file containing its TypeScript codebase, with one person on X calling attention to the leak and posting a file containing the code. The leaked data reportedly contains more than 512,000 lines of code and provides a look into the inner workings of the AI-powered coding tool, as reported earlier by Ars Technica and VentureBeat. Users who have dug into the code claim to have uncovered upcoming features, Anthropic's instructions for the AI bot, and insight into its "memory" architecture. Some things spotted by users inclu … Read the full story at The Verge.
You can now use ChatGPT with Apple’s CarPlay
ChatGPT is now accessible from your CarPlay dashboard if you have iOS 26.4 or newer and the latest version of the ChatGPT app, 9to5Mac reports. Apple's recently-launched iOS 26.4 update added support for "voice-based conversational apps" in CarPlay, opening the door to let you use AI chatbots with voice features through Apple's in-car platform. When using ChatGPT through CarPlay, the app doesn't show text conversations, according to 9to5Mac - instead, you can only have conversations with the app using your voice. (Apple's developer guidelines ask that apps don't show text or imagery as responses.) The CarPlay app isn't completely devoid of … Read the full story at The Verge.
New - Apple Neural Engine (ANE) backend for llama.cpp
This just showed up a couple of days ago on GitHub. Note that ANE is the NPU in all Apple Silicon, not the new 'Neural Accelerator' GPU cores that are only in M5. (ggml-org/llama.cpp#10453) - Comment by arozanov Built a working ggml ANE backend. Dispatches MUL_MAT to ANE via private API. M4 Pro results: 4.0 TFLOPS peak at N=256, 16.8x faster than CPU MIL-side transpose, kernel cache, quantized weight support ANE for prefill (N>=64), Metal/CPU for decode Code: https://github.com/arozanov/ggml-ane Based on maderix/ANE bridge. submitted by /u/PracticlySpeaking [link] [comments]
AI news from 200+ sources
Get Started FreeGeneral AI
OpenAI, not yet public, raises $3B from retail investors in monster $122B fund raise
OpenAI's latest funding round, led by Amazon, Nvidia, and SoftBank, values the AI lab at $852 billion as it nears an IPO.
VibePad – New AI Padding Model
Article URL: https://www.npmjs.com/package/vibepad Comments URL: https://news.ycombinator.com/item?id=47600023 Points: 1 # Comments: 0
Advocacy groups urge YouTube to protect kids from ‘AI slop’ videos - AP News
Advocacy groups urge YouTube to protect kids from ‘AI slop’ videos AP News
Softr launches AI-native platform to help nontechnical teams build business apps without code
Softr, the Berlin-based no-code platform used by more than one million builders and 7,000 organizations including Netflix, Google, and Stripe, today launched what it calls an AI-native platform — a bet that the explosive growth of AI-powered app creation tools has produced a market full of impressive demos but very little production-ready business software. The company's new AI Co-Builder lets non-technical users describe in plain language the software they need, and the platform generates a fully integrated system — database, user interface, permissions, and business logic included — connected and ready for real-world deployment immediately. The move marks a fundamental evolution for a company that spent five years building a no-code business before layering AI on top of what it describes as a proven infrastructure of constrained, pre-built building blocks. "Most AI app-builders stop at the shiny demo stage," Softr Co-Founder and CEO Mariam Hakobyan told VentureBeat in an exclusive in
Former BP CEO takes over Wyoming data center developer, as first woman leader of Big Oil giant becomes new BP chief
The former BP chief is entering the AI age with American data center projects.
With its new app store, Ring bets on AI to go beyond home security
Ring's app store will allow the company to target broader use cases beyond security, like elder care or business needs.
AWS launches frontier agents for security testing and cloud operations
I'm excited to announce that AWS Security Agent on-demand penetration testing and AWS DevOps Agent are now generally available, representing a new class of AI capabilities we announced at re:Invent called frontier agents. These autonomous systems work independently to achieve goals, scale massively to tackle concurrent tasks, and run persistently for hours or days without constant human oversight. Together, these agents are changing the way we secure and operate software. In preview, customers and partners report that AWS Security Agent compresses penetration testing timelines from weeks to hours and the AWS DevOps Agent supports 3–5x faster incident resolution.
Amazon AI Blog
Treeline raises $25 million in Andreessen Horowitz-led funding to streamline IT services with AI
The round reflects growing investor interest in AI‑native platforms to modernize legacy outsourced IT.
Emerald AI raises $25 million from Nvidia and others to build a fast pass for data centers connecting to the grid
Emerald AI touts new fundraising success and partnerships with utilities and power generators.
I tried Firefox's new AI 'Smart Window' in a beta build
Article URL: https://www.omgubuntu.co.uk/2026/03/firefox-smart-window-hands-on Comments URL: https://news.ycombinator.com/item?id=47585853 Points: 1 # Comments: 0
Feds probe whether NYC Council member, Hochul aide took bribes to help migrant shelter provider - AP News
Feds probe whether NYC Council member, Hochul aide took bribes to help migrant shelter provider AP News
![[D] Got my first offer after months of searching — below posted range, contract-to-hire, and worried it may pause my search. Do I take it?](https://zmstgxtziqmvvwzllahg.supabase.co/storage/v1/object/public/article-images/reddit-machinelearning/d0dfd4a4-e282-49f1-8a70-0a1f543bb46c.jpg)
[D] Got my first offer after months of searching — below posted range, contract-to-hire, and worried it may pause my search. Do I take it?
I could really use some outside perspective. I’m a senior ML/CV engineer in Canada with about 5–6 years across research and industry. Master’s in CS and a few publications. I left my previous remote startup role about five months ago. The role gradually changed, I burned out, and decided to step away. I took around two months to decompress and have been actively searching for the last three months. It’s been tough. A few interview loops and a couple of final rounds, but no offers until now. Last week I finished a four-round process with a small pre-seed AI startup in healthcare. The work is genuinely interesting and very aligned with my background. The team also seems strong. Here’s the complication. The role was posted with a salary range, but the verbal offer came in roughly 20% below the bottom of that range. On top of that, it’s structured as a 3-month contract-to-hire instead of full-time. Since I’m in Canada and they’re in the US, I would be working as a contractor. That mean
Robotics
Nomadic raises $8.4 million to wrangle the data pouring off autonomous vehicles
The company turns footage from robots into structured, searchable datasets with a deep learning model.