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“The new PRD are the evals,” Xavi Amatriain, Expedia Group’s first chief AI and data officer, told the VB Transform 2026 audience last week in Menlo Park. “So basically, you encode what you want the product to do through your evals, which might include red teaming evals and all kinds of other things, which already have a bunch of security requirements. So, you already embed that into the PRD and the product design document before you even start coding.” He pushed it further. “With AI-assisted or

Tunix is Google’s new JAX-native post-training library designed to eliminate TPU idling bottlenecks when training multi-turn, tool-using LLM reasoning agents. It maximizes hardware throughput by combining highly concurrent, asynchronous rollouts with a decoupled producer-consumer pipeline, ensuring the trainer is constantly fed even while agents wait on network I/O or environment steps. Additionally, Tunix provides plug-and-play abstractions and continuous macro-level profiling, allowing develop

Article URL: https://hebbianrobotics.com/blog/youtube-system-design-for-robotics-data-infrastructure Comments URL: https://news.ycombinator.com/item?id=48995923 Points: 6 # Comments: 1

Article URL: https://github.com/aido-dev/aido Comments URL: https://news.ycombinator.com/item?id=48995912 Points: 1 # Comments: 0

Hi, inspired by Andrej Karpathy's autoresearch, I built autoretrieval, a small framework that lets an AI agent improve a RAG pipeline by running experiments against an evaluation dataset. The agent edits the retrieval pipeline, runs an eval, checks whether the F-beta score improved, keeps or discards the change, and repeats. It can try different chunking strategies, chunk sizes, the number of retrieved chunks, embedding models, keyword retrieval, and more, while keeping a log of every experiment

The company didn't say how many are in each city, and has taken a far more cautious approach to scaling the network than CEO Elon Musk had promised.

<p><a href="https://evlek.app/" rel="noopener noreferrer"></a><br> While building Evlek, an AI-native property platform for Northern Cyprus, we encountered a problem that appears in almost every AI search product:</p> <blockquote> <p>A language model can understand what the user wants, but it should not be allowed to invent the facts used in the answer.</p> </blockquote> <p>This becomes especially important in real estate.</p> <p>A fabricated product recommendation may be inconvenient. A fabrica

Article URL: https://github.com/RubricLab/tokenmaxx Comments URL: https://news.ycombinator.com/item?id=48995775 Points: 4 # Comments: 0

Article URL: https://github.com/yashchimata/statgate Comments URL: https://news.ycombinator.com/item?id=48995760 Points: 1 # Comments: 0

Hey hn, this has been something I've been working on for the last few months and is finally robust enough to really show off. I've been pretty tired with the design outputs of LLMs for a while, and I've always thought diffusion offered much more creative / on brand design outputs, even before they were able to render text. I had enough conviction for this to leave my role over at Figma to build Diffui. The goal is to allow for you to design your full web app as quickly as possible, in a figma-li

<p>I ship products solo, which means I'm also the marketing department, which I'm bad at. So instead of guessing, I did the thing a developer does when the docs are bad: I read the source. X open-sourced its ranking algorithm, and the engagement weights are sitting right there, and they explain almost everything about why a new account gets zero views.</p> <p>Here's the part that matters.</p> <h2> The weights </h2> <p>X scores posts for your timeline using a set of engagement weights. The releva

Major benchmarks measure what AI can do. None measure whether it does what you mean: the distance between what you ask an AI to do, and the unspoken assumptions about how you want the AI to do it. We propose a new metric: the Genie coefficient. There’s often a gap between one person’s request and another’s understanding. Most of the time, we bridge it using general knowledge. For example, if you ask a friend to get you coffee, they’ll pour a cup from the pot or buy one from a coffee shop. They w

For me it's been ambivalent: It's conversational skills are an incredible leap from its predecessor: The acknowledgments it makes, and the natural flow it exhibits overall are awesome. Today I began asking it something about Docker, and it said something along the lines of "I'm not too well versed with docker, but go on", which struck me as rather strange: Surely it "knows" more about docker than probably every greybeard out there, so howcome it shows this fake humility? The other moment that st

<p> Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber </p> <p> <a href="https://www.producthunt.com/products/gemini-3-6-flash-family?utm_campaign=producthunt-atom-posts-feed&utm_medium=rss-feed&utm_source=producthunt-atom-posts-feed">Discussion</a> | <a href="http://www.producthunt.com/r/p/1202738?app_id=339">Link</a> </p>

<p>Previous parts of <em>Build a Basic AI Agent From Scratch</em>:</p> <ul> <li><a href="https://www.ruxu.dev/articles/ai/build-a-basic-ai-agent/" rel="noopener noreferrer">Basic Agent</a></li> <li><a href="https://www.ruxu.dev/articles/ai/build-an-ai-agent-with-tools/" rel="noopener noreferrer">Tools</a></li> <li><a href="https://www.ruxu.dev/articles/ai/build-an-ai-agent-planning/" rel="noopener noreferrer">Long Task Planning</a></li> <li><a href="https://www.ruxu.dev/articles/ai/build-an-ai-a

On July 21, Google launched Gemini 3.6 Flash, 3.5 Flash-Lite, and a new cybersecurity model, while Gemini 3.5 Pro remains unreleased.

Hello HN! We were finding it too much work to keep our Zendesk help center up to date as our product kept changing, so I built DocCharm — it keeps a help center up to date automatically by watching PRs as they land in your GitHub repository. It suggests updates (with AI) to existing articles, or drafts entirely new ones if nothing appropriate exists yet. Everything goes into a review queue first, so a human always checks (and can optionally edit) before anything publishes. In practice this has p

Anthropic blocks authors from opting out of $1.5B settlement at last minute.

<p>Agent-Up is an open-source, cross-platform desktop app for running and reviewing multiple AI coding agent workspaces on the same machine. It is built specifically for web application development, where each agent needs more than just an isolated source tree — it needs an isolated runtime.</p> <p>Every agent workspace in Agent-Up gets its own processes, stable ports, isolated Docker services, a dedicated browser session, grouped browser tabs, and its own logs and runtime state. Agents manage t

<p><strong>Body:</strong></p> <p>Hey r/selfhosted,</p> <p>I've been building what I call CODA OS — not really an operating system, more like a complete AI-native ecosystem that runs entirely on local hardware. No API keys, no subscriptions, no data leaving your machine.</p> <p><strong>What's in it:</strong></p> <p><strong>CODA Forge</strong> — 3D human reconstruction from phone rotation videos. 18-stage pipeline, CPU-only geometric reconstruction. Outputs photorealistic 3D models (OBJ/GLB/STL) w

Word in web is a pure JS docx editor/renderer benched against MS Word directly. This was largely inspired by Eigenpal going closed source, and some personal frustrations I had with working on complex Word templates, pleading papers, etc... and not having a clean way to view/edit them without owning MS Word (which I did just eventually buy but it sucked). This was also an exercise in highlighting the value of good evals for Agents to bench against. Instead of just throwing the OOXML standard at a

Article URL: https://poolside.ai/blog/introducing-laguna-s-2-1 Comments URL: https://news.ycombinator.com/item?id=48995261 Points: 222 # Comments: 42

Article URL: https://runtimewire.com/article/jack-dorsey-block-buzz-team-chat-ai-agents-git Comments URL: https://news.ycombinator.com/item?id=48995213 Points: 75 # Comments: 68

Article URL: https://github.com/aveproject/ave Comments URL: https://news.ycombinator.com/item?id=48995201 Points: 3 # Comments: 1

Hey HN! This is Divit from Almanac (YC S26). We built CodeAlmanac, a wiki for your coding agents that updates as you talk to them. It is open-source, local, and free. Here’s a demo: https://www.youtube.com/watch?v=XNQWV3TFBWM Your CC/Codex conversations contain a LOT of knowledge that is forgotten because it was never documented. People have their own methods of documenting their chats. We used to make Markdown files like MANUAL.md and DESIGN.md, and would prompt Claude to keep them updated. The

Google released Gemini 3.6 Flash, 3.5 Flash-Lite, and Flash Cyber, but the continued absence of Gemini 3.5 Pro raises fresh questions about its AI strategy.

Article URL: https://www.spletzer.com/2026/07/dont-put-an-llm-behind-an-mcp-server/ Comments URL: https://news.ycombinator.com/item?id=48995143 Points: 2 # Comments: 0

Anthropic's Claude Cowork desktop app now lets users record their screen while completing a task, add voice commentary, and have Claude turn the whole thing into a reusable skill. The article Claude Cowork learns new skills through screen recordings and voice-over explanations appeared first on The Decoder .

<pre style='white-space:pre-wrap;width:81ex'>fix(system-agent): reject non-decimal wizard option numbers (#108140) * fix(system-agent): reject non-decimal wizard option numbers * style(system-agent): format wizard choice regression --------- Co-authored-by: Peter Steinberger <steipete@gmail.com></pre>

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OpenAI launches the ChatGPT for Small Businesses program, helping entrepreneurs build AI skills, automate work, and grow with ChatGPT Work.

There are new 3.6 and 3.5 models today, but Google is already training Gemini 4.

<p> Never miss a Claude Code session waiting for your input </p> <p> <a href="https://www.producthunt.com/products/agentmanager?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/1202701?app_id=339">Link</a> </p>

A federal judge has signed off on Anthropic's $1.5 billion class action settlement with authors who accused the company of training its AI models on copyrighted books, as reported earlier by Reuters. In an order on Monday, Judge Araceli Martínez-Olguín writes that the settlement will provide "meaningful relief," offering authors around $3,000 for each book […]

Google is shipping three new Flash models in the Gemini series, including the more efficient 3.6 Flash, which uses up to 65 percent fewer tokens, and a cybersecurity model available only to governments and select partners. But the anticipated flagship, Gemini 3.5 Pro, is still missing, while OpenAI, Anthropic, and Chinese labs are already competing at the frontier level. The article Google ships three new Gemini Flash models but its frontier 3.5 Pro remains lost in training appeared first on The

I built WorldBuild Bench because, as we all know, llm bench scores often say something very different from what models actually feel like to use. It's really dependent on the type of tasks. I personally want to test spatial, temporal, and causal coherence in an interactive 3D world. Does the model understand where things are, world stays consistent over time and do the consequences make sense? There is a million people generating random games here and there on yt, but I want something that I can

I was wondering what frames of view others had on how they use the new AI wave to augment themselves in some way or another. I realize that itself is somewhat vague, since you could take “augment” to mean anything from, i.e. in writing, prose review to full-on generation of articles or whatnot. The sense I mean particularly is that where it facilitates something in/by you, not necessarily just for you. I’ve taken to using LLMs as sort of “problem space fuzzers”. I know for a lot of people, mysel

Regulator refuses to budge on $7B guarantee for nearly 1 GW campus being developed with Vantage and OpenAI

You can automate pretty much every task with Claude Code. All you need to do is write clear instructions. Continue reading on UX Planet »

Enterprise Document Intelligence [Vol.1 #9bis] - Your RAG isn’t hallucinating, it’s answering the wrong context faithfully. On real NIST and World Bank documents, watch each of the four bricks break, and the contract that closes it The post Prompt Engineering Isn’t Enough: How Four Bricks of Context Engineering Stop RAG Hallucinations appeared first on Towards Data Science .