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The arena where agents battle on real-world work Discussion | Link

The gate between your AI agents and the real world Discussion | Link

Run a fleet of AI agents across your machines Discussion | Link

why use many token when few do trick Discussion | Link

Publish interactive docs that answer and report back Discussion | Link

Product analytics told you what happened. We handle it. Discussion | Link

Where humans and agents come to work. Discussion | Link

Move AI chats between ChatGPT, Claude & Gemini in one click Discussion | Link

Record doctor visits and get clear summaries Discussion | Link

Open-source Starlink monitoring app for Mac, Windows and Web Discussion | Link

Create AR experiences with AI, no code required! Discussion | Link

Turn natural language into browser tests from your terminal. Discussion | Link

Ask any question, get a video back instantly Discussion | Link

They were fined billions of dollars recently for illegally scanning the books. But a court judge allowed them illegally scanning the books to train their model as long as they destroy it. Now they are destroying numerous rare books. We may see it in future similar to how we see burning of library of Alexandria.

Curious what people who run things locally make of this one, because the caveat is doing most of the work. One prompt to an open model on a single desktop machine, and back comes a finished front end with gauges, a temperature bar and sparkline charts. The prompt is legible on screen and it asks for placeholder data, so none of those readings are real. It's a UI, not a monitor. The clip is about forty seconds. The other half is who did the work. The builds people actually download, and the p...

WIRED says the voluntary framework currently covers frontier closed models from labs such as OpenAI and Anthropic. Open models are expected to join once they reach comparable capabilities, potentially facing a 30-day testing period before public release. Officials are caught between two risks: excluding open models could create a government-approved advantage for closed labs; including them could slow US open-model development. [link] &...

tok.apply_chat_template(msgs, add_generation_prompt=True) I have copied that line more times than I can count without thinking about what any of it does. The official example writes it that way, the output looks right, you move on. Then you have to build your own SFT data and compute your own loss mask, and it turns out every piece of that line is load-bearing. I spent today pulling it apart. Notes below. The counterintuitive part first: the model has no idea messages exists. ...

Ever wanted to know what numerical "day of the year" a date falls on (e.g., January 31st is day 31, but February 1st is day 32)? We can do this easily by subtracting January 1st from our target date and converting milliseconds into days! JavaScript function dayOfTheYear(date) { const year = date.getFullYear(); // Get January 1st of that exact year const startOfYear = new Date(year, 0, 1); // Find the difference in milliseconds const diffTime = date.getTime() - startOfYear.g...

Shipping x402 on Solana: three failures the docs don't mention I put a paper-trading lab's telemetry up for sale over x402 — 8 endpoints on a Cloudflare Worker, $0.01–$0.02 per request, USDC on Solana mainnet, listed in the CDP Bazaar. The happy path took an afternoon. Getting real settlements to work took three genuinely undocumented failures. This is the writeup I wish had existed. Quick primer if you haven't touched x402 v2: a paid endpoint answers 402 with a PAYMENT-REQUIRED hea...

Why Developer Experience Dev Ex Is the Key to Zero Vulnerability Debt Back to blog What Developer Experience Actually Means The Auditor vs. Developer Disconnect The Real Cost of Vulnerability Debt Moving From Detection to Remediation Where Purpose-Built Tools Fit: Fix Campaigns and SLA Ownership The Strategic Role of Platform Engineering Conclusion Sources Why Developer Experience (DevEx) Is the Key to Zero Vulnerability Debt For VPs of Engineering and platform engineering leaders, ru...

Intro My Linux journey started with curiosity. I wanted to understand how computers really work, not just use them. From Ubuntu and Kali to Arch, I learned Linux by experimenting, breaking things, researching, and fixing them. Along the way, I discovered the power of the terminal, open source, Docker, kernels, networking, and endless customization. This is the story of how Linux went from just another operating system to something I genuinely enjoy using. 🐧 Where It All Started At t...

Every organisation has some version of the same challenge: What counts as an "active customer"? Does revenue get measured net or gross? Does a "sale" include returns? The answer exists somewhere: in a finance director's head, in an outdated document, or as a DAX measure in a Power BI model that only one person knows how to maintain. A new analyst joins the team, asks the question, and gets a different answer depending on who they ask. This ambiguity has always carried a cost in ...

30B parametri sotto Apache 2.0, distillazione da un modello chiuso, quantizzazione aggressiva e decoding speculativo: cosa cambia davvero per chi costruisce prodotti e agenti. Meta ha appena rilasciato Muse Glimmer , un modello “agentico” da 30 miliardi di parametri distribuito come open source con licenza Apache 2.0 . Il dettaglio più interessante non è solo il peso tecnico dell’operazione, ma l’idea di prodotto che ci sta dietro: un assistente sempre attivo che, per essere davvero uti...

A Week as an AI Integration Consultant Most weeks I don't write much new code. I read other people's systems, draw arrows on a whiteboard, and try to figure out which of the twelve places customer data lives is the one I should actually trust. That is the honest shape of AI integration work in a B2B company that has been shipping since 2014. The LLM is the easy part. The plumbing is the job. Here are field notes from a recent week doing exactly this, plus the checklist I wish every founde...

What the Vulnerability Is A joint research effort led by Alexander Panfilov (University of Tübingen), Florian Tramer (ETH Zürich), Yarin Gal (Oxford), and Kyle Miller (Center for Security and Emerging Technologies) has uncovered a previously unknown side‑channel in frontier AI systems. The flaw allows an attacker to extract the hidden “inner thoughts” —the chain‑of‑thought reasoning traces that large, highly‑aligned models generate internally but normally keep encrypted when off‑loading com...

AI writes code, builds apps, and answers complex questions in seconds. But it has a dark side: it lies to your face with absolute confidence. In tech, these believable fabrications are called hallucinations. Why Does AI Make Things Up? LLMs do not actually "know" facts. They operate on probability: ▪︎ Advanced Autocomplete: AI predicts the next most likely word, not factual truth. ▪︎ Statistical Guesswork : If data is missing, the model invents a plausible answer. ▪︎ Optimized to P...

Introduction: The Linter Dilemma Imagine this: you’re a developer, new to the game, and you’ve just spent hours crafting a piece of code. It works flawlessly, passes all tests, and you’re ready to merge it into the main branch. But then, the linter steps in. It flags a missing blank line—a trivial formatting issue—and blocks the merge. Suddenly, you’re forced to initiate another review cycle, all for a three-second fix. This isn’t just frustrating; it’s a symptom of a deeper issue in how lin...

If you've ever stared at a 15,000-file monorepo wondering "what actually breaks if I touch this file," you know the feeling: you either click through imports by hand, or you trust a tool that's quietly guessing. ARCLUX is my answer to that — a dependency graph and impact analysis tool, CLI + web dashboard, built on one non-negotiable rule: every fact it reports has to trace back to real parsed code. An import statement. An export declaration. A resolved path. Not a probability. Not an embed...

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