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Article URL: https://grapheneos.social/@GrapheneOS/117231186011306184 Comments URL: https://news.ycombinator.com/item?id=49622042 Points: 127 # Comments: 71

Article URL: https://gwern.net/on-really-trying Comments URL: https://news.ycombinator.com/item?id=49622305 Points: 17 # Comments: 3

Article URL: https://twitter.com/sama/status/2097385167002415140 Comments URL: https://news.ycombinator.com/item?id=49622377 Points: 8 # Comments: 0

Article URL: https://openai.com/index/codex-quantum-computing-experiments/ Comments URL: https://news.ycombinator.com/item?id=49622561 Points: 8 # Comments: 0

I spend a lot of time in the AI space -- reading papers, building things, talking to engineers who are actually shipping. And there is a gap between what the demos show and what production systems actually look like that nobody is being fully honest about. So here is my honest take on where things actually are. The Problem With How We Talk About AI Agents Everyone is calling everything an "agent" right now. A function that calls a tool? Agent. A chatbot with memory? Agent. ...

Quick Answer context length cost for .NET developers: This guide shows .NET developers how to control LLM context costs by trimming prompts, reusing KV cache, and monitoring token usage to keep latency and budgets predictable. Context Length Cost for .NET Developers: A Production‑Ready Playbook Context Length Cost for .NET Developers: A Production‑Ready Playbook When the cost of a single LLM call starts to eclipse the value of the feature you’re shipping, the problem is n...

Let's be honest, deploying AI models can feel like navigating a minefield. You've trained the perfect model, but getting it reliably into production, ensuring it performs, and iterating quickly? That's where things often fall apart. For years, I've seen teams struggle with manual handoffs, inconsistent environments, and the sheer velocity of changes. This is why automation in MLOps isn't just a nice-to-have; it's the non-negotiable bedrock for any serious AI initiative. From my experience b...

The push to run large language models directly on phones and tablets is driven by three hard requirements: latency, privacy, and offline availability. But the physics of mobile hardware creates a ceiling. NPUs and DSPs on flagship SoCs are powerful, yet thermal design power and battery capacity turn long-context inference or multi-turn reasoning into a rapid drain. The practical path forward is not all-edge or all-cloud. It is a tiered architecture where small, quantized models handle sensitive,...

I spend a lot of time in the AI space -- reading papers, building things, talking to engineers who are actually shipping. And there is a gap between what the demos show and what production systems actually look like that nobody is being fully honest about. So here is my honest take on where things actually are. The Problem With How We Talk About AI Agents Everyone is calling everything an "agent" right now. A function that calls a tool? Agent. A chatbot with memory? Agent. ...

Problem My script failed when try lacked an explicit import from dw::Runtime . The runtime reported Unable to resolve reference of: try during execution. The documentation describes try as a function that returns a Result object for handling errors docs . Input { "order" : { "id" : "ORD-2001" , "total" : "12.5O" } } Working configuration %dw 2.0 // try() lives in dw::Runtime — not import...

Short answer: for a beginner-friendly SaaS login in the US or EU, SMS OTP is the simplest managed starting point; authenticator apps are stronger, while an email code is a fallback you must build and evidence yourself. The decision is less about a clever factor comparison than about what your compliance file can prove six months later. A password-reset message with a short expiry is a useful test case: the user needs reach, the security team needs an audit trail, and the storage owner needs a...

Two executors on the main line, one on fixes, and a lead who only cuts, hands over and accepts. The moment the lead starts writing code, the facts stop being prepared - and the next batch of tasks costs more than the hour that got saved. 👋 I'm Anton - a software engineer working mostly in PHP/Symfony and Go, currently carving a live PHP monolith into Go services. The earlier parts of this series were about what a task must contain and how small it has to be cut. This one is about who does...

Fail-open is the default failure mode of agent hooks I'm the author of Handrail, a free, MIT-licensed hook pack for Claude Code and other agent-CLI hook systems. Handrail works with Claude Code and other agent CLIs in plain text only; it is not affiliated with, endorsed by, or a product of Anthropic. This post is about one specific design bug I keep finding in hook scripts, including early drafts of my own: they fail open. What "fail open" means here An agent-CLI hook is a...

A player opens a warehouse guide because deliveries are not working. The page explains warehouses, lists equipment, and mentions staffing. Yet the player still has to work out which condition to check first. For developers building documentation sites, that gap is worth designing around: a reader needs an explanation that leads to a decision. Start with the question the page must resolve The warehouse page on my independent fan site, Big Ambitions Wiki bigambitionswiki.com, provides a ...

No new commands to learn, just pick it up and use it By this August, our team had been writing code with AI for more than half a year. The biggest thing I noticed during this time was that our development speed went up, but code quality stayed pretty rough. Development often took just half a day, but hunting down bugs could take several days. So recently I spent more than a month restructuring our team's AI coding workflow. I replaced OpenSpec with the AIDLC workflow, using a more detailed...

A reader searches for help opening a puzzle box. The result supplies the answer in its preview, includes a later character reveal in the heading, and never explains whether the solution was actually verified. A horror-game guide can fail in two separate ways: it can reveal more than the reader wanted, or express more certainty than its evidence supports. I would treat those as distinct content properties. Identify the two editorial decisions The puzzle page on The Skin Stapler Wiki https://t...

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Specialized team of AI agents that discover, attack, and validate web vulnerabilities, leveraging pre-existing site context to eliminate noise and speed remedia

Google Cloud policy, banking limits, seller verification, and sandbox setup delayed Kotohira Digital Residents after its code was ready.

Lightsage has raised a $4 million seed round led by Nexus Venture Partners, with operator angels from Salesforce, Postman, Apollo, DocuSign, GitLab, Resend.

AI agents can write compilers and negotiate SaaS deals, so why can't they renew your driver's license? Inside the legacy plumbing breaking civic AI.

Adversary is built and submitted to Apple. Now the real Shipaton test begins: finding out whether anyone actually wants to download and play it.

Why asking an LLM to "find team disagreements" is a fatal design flaw, and how we replaced probabilistic reasoning with deterministic set theory.

I announced my app, got a brutal reality check, and pulled it from review. Here’s how I pivoted Dogear, what I learned, and why slowing down saves months.

How Slovo uses WidgetKit timelines, App Groups, tinted rendering, and Live Activities to turn Russian vocabulary into recurring recall prompts.

Article URL: https://hackaday.com/2026/09/07/the-helicopter-with-radioactive-blades/ Comments URL: https://news.ycombinator.com/item?id=49600901 Points: 159 # Comments: 49

Article URL: https://copperhead.sh/ Comments URL: https://news.ycombinator.com/item?id=49610059 Points: 213 # Comments: 85

Article URL: https://gpu-lexer.vercel.app/ Comments URL: https://news.ycombinator.com/item?id=49619464 Points: 31 # Comments: 8

Article URL: https://twitter.com/hilbertspaess/status/2097476196791709843 Comments URL: https://news.ycombinator.com/item?id=49619639 Points: 65 # Comments: 14