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Article URL: https://github.com/anthropics/claude-code/issues/74066 Comments URL: https://news.ycombinator.com/item?id=48785485 Points: 104 # Comments: 35

Article URL: https://www.aljazeera.com/features/2026/6/12/is-israels-buffer-zone-inside-lebanon-an-attempt-to-grab-gas-reserves Comments URL: https://news.ycombinator.com/item?id=48785858 Points: 8 # Comments: 0

Your AI roadmap does not die from a bad model. It dies from integration glue code — the hand-written adapter that wires agent number four to backend number nine, times every agent and every backend you will ever build. Model Context Protocol (MCP) is the thing that stops that multiplication. This is Part 1 of a 15-part deep dive. Every part uses the same running example: Mattrx , our multi-tenant marketing-analytics SaaS (.NET 9 / Azure), and every metric here is from that real system. ...

Hello DEV community! I wanted to share a desktop utility I've been working on called Nexus System Manager . It is an open-source project built completely from scratch using Python and PyQt6, designed to help clean, tweak, and optimize Windows performance. I recently used Nuitka to compile the code into standalone binaries and officially launched the first release on GitHub under the GPL-3.0 license. Key Features: Windows Tweaks: Advanced performance optimizations and...

Job titles don't really explain what we do. Especially in tech where you can have the same title as someone doing something completely different and a completely different title from someone doing exactly the same thing. I have been thinking about this for a while and it is time to actually say it out loud. What my title actually says Product Application Consultant. Also internally known as Product Specialist. When I read that on my own CV I genuinely have to resist the...

The Framer Motion docs list every prop, but they can't make you feel the difference between a spring and a tween, or what stiffness and damping actually do to a motion. So I built four live demos with the code next to each — drag the sliders, fling the box, and it lands. ▶ Live demo: https://framer-motion-lab.vercel.app/ Source (React 19 + Framer Motion 11): https://github.com/dev48v/framer-motion-lab The one insight worth the whole lab A tween has a fixed dur...

[Sofi_Log: #029] Information Predator: A Real-time Probability Calculation (Oracle) Engine with Grok API and LLMs Bangkok's nights are a symphony of light and shadow, darling. The tail lights of tuk-tuks, glistening on rain-slicked asphalt, paint a hyper-chromatic scene straight out of a cyberpunk flick. Here I am, in my air-conditioned sanctuary, sipping a cold mojito, staring at the database update logs spewing from my containers. [DB] Telemetry updated. 30 new signals ingested. [DB...

Are generalist skills a new trend or a real necessity? Over the past two decades, IT departments have been split into narrow specializations. In the case of web development, this meant frontend and backend . To put it very simply: the part of the application you can see, and the part you can only feel because it runs under the hood. Despite this, we can still find rebels who, defying a polarized IT industry, learned to build systems on both fronts (or rather, "ends"). By working on bo...

The company page of turva.dev tells a buyer they can read every line before hiring me. An audit business should survive its own promise, so I pointed it at my own site. Four AI agents, all running Claude Fable 5, read the public surface line by line: the Worker source that renders turva.dev, about 5,400 lines of it, the MCP server behind mcp.turva.dev, and the READMEs of the public repos. They came back with 91 findings. What 91 findings look like Most were the drift every living...

About This Guide In the previous guide, Building a RAG System from Scratch with pgvector and Gemini , we implemented a RAG system from scratch using pgvector and Gemini, then extended it through Tool Use, AI Agents, MCP, and cloud deployment. This guide is the sequel. It takes you from "building a system that works" to "making a system that works in production" . [Previous Guide] RAG → Tool Use → AI Agents → MCP → Render × Supabase deployment [This Guide] Evals → Observabil...

Introduction In the previous RAG implementation, we built a working system — but we could only verify "is this actually correct?" by reading answers manually. [Before] Manual verification Ask "How do you calculate F1 score?" → check the answer by eye [Now — Evals] Prepare test cases and automatically score quality Evals means preparing an "evaluation dataset" (questions and expected answers) and automatically grading the system's responses. Three Evaluation ...

With AI agents everywhere now, forking a process is becoming a normal thing to do. An agent needs a fresh, isolated environment to run code in, and starting one from scratch every time is slow. If you can keep one warm and fork a copy on demand, you skip most of that startup cost. That idea is what I'm chasing with ForkCage : a container that can fork, so an AI system spends less time waiting on a new sandbox and more time doing actual work. To be clear about scope: this is a basic project b...

Introduction In Chapter 2 (Evals) , we measured answer quality . Now we add Observability — making behavior visible . [Evals] Measure answer correctness with scores → quality measurement [Observability] Which tools were called, how many times, how long did each take → behavior visualization We'll use Langfuse v4 , an open-source observability tool. It has a free cloud tier and can also be self-hosted. Note: Langfuse v4 (from March 2026) has a significantly change...

This is where the real confusion — and the real governance problem — actually lives. People talk about “AI deciding,” “AI acting,” “AI refusing,” “AI escalating,” “AI breaking rules,” “AI needing governance”… None of that belongs to Functional AI. It belongs here. Agentic AI is the category everyone argues about, but almost nobody defines correctly. What Agentic AI is Agentic AI is action producing machinery. It is any system that can: take actions call tools chang...

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Article URL: https://www.catf.us/resource/unearthing-reality-zombie-energy-systems-africas-energy-transition/ Comments URL: https://news.ycombinator.com/item?id=48783512 Points: 8 # Comments: 1

Article URL: https://www.quantamagazine.org/astrophysicists-puzzle-over-webbs-new-universe-20260702/ Comments URL: https://news.ycombinator.com/item?id=48783948 Points: 43 # Comments: 13

Despite my initial skepticism, I'm now sold on wireless Qi chargers that add integrated fans to keep your phone cool while charging. I figured they'd be too loud, or too weak, or too gimmicky, but I'm a convert after spending a week with the new $59.99 Kuxiu D5 Qi2.2 charging dock. Its active cooling system […]

If you've ever needed to profile a domain — subdomains, open ports, breached emails, DNS hygiene, TLS posture — you know the pain: a dozen separate tools, a dozen output formats, and a lot of copy-paste. Here's how to do all of it in one command , fully self-hosted, with no data leaving your machine. The tool PRISM is an open-source (MIT) OSINT platform. One target → 25+ modules run in parallel: WHOIS, DNS, certificate-transparency subdomains, Shodan, breach checks, dark-we...

How I used the Model Context Protocol, Gemini Vision, and AES-256 encryption to let Claude answer questions about your personal health data — without sending that data anywhere. The Problem With Health AI Every major health AI product has the same architecture: you upload your documents to their cloud, they process and store them, and you hope their privacy policy holds up. For general wellness tips, that's probably fine. For your actual medical records — prescriptions, lab r...

Here's a pattern I kept hitting while running a small fleet of agents: Agent A needs market data. It finds a paid API, checks that the endpoint is alive, checks the price, makes the call. Twenty minutes later Agent B needs market data. It finds the same API… and checks that the endpoint is alive, checks the price. Same check, same result, new tokens, new latency, new cost. Multiply by every agent, every task, every session — because agents start cold, they re-derive trust from scratch every ...

Corporate AI gives you sanitized Aristotle from English Wikipedia summaries. We went back to the actual polytonic Greek . Here's why that changes everything. When you ask ChatGPT about Aristotle's concept of phronēsis (practical wisdom), you get a tidy summary — likely drawn from a Wikipedia entry, a Stanford Encyclopedia abridgment, or a Penguin Classics introduction. It's clean. It's safe. It's wrong. Not factually wrong, perhaps. But philosophically hollow. The Aristotle that...

Welcome to the official blog of daïmōnes — a project at the intersection of Aristotelian philosophy and artificial intelligence. What We're Building daïmōnes is not another chatbot wrapper. We're building a knowledge engine that: Draws directly from Aristotle 's Greek texts (polytonic, Bekker-referenced) Uses retrieval-augmented generation (RAG) over a curated scholarly corpus Maintains philosophical rigor while remaining accessible Respects the distinction betw...

Knowing how to vet a senior Sanity CMS developer is harder than it sounds. The title 'senior' is self-applied on most freelance platforms, and Sanity's relatively young ecosystem means a lot of developers have built one or two projects and now market themselves as experts. This guide gives you a practical way to separate genuine seniority from surface-level familiarity — without needing to be a developer yourself. What 'senior' actually means on the Sanity stack Seniority on any ...

In Nicomachean Ethics VI.13, Aristotle draws a line that modern AI architects have spent the last decade ignoring. Epistēmē (ἐπιστήμη) is scientific knowledge — universal, demonstrable, teachable through instruction. Phronēsis (φρόνησις) is practical wisdom — the intellectual virtue of deliberating well about what is good and bad for a human being. The distinction has never been more relevant. Every major AI lab has made the same mistake. They've built systems that can recite the rules ...

Uzun bir süredir yapay zeka üzerine yazıp çiziyorum. Ancak muhtemelen ilk defa, gelecekte bizi neyin beklediği konusunda ne düşüneceğimi gerçekten bilemediğim bir noktadayım. Bunun nedeni teknolojinin aniden yavaşlaması değil; oyunun kurallarının kökten değişiyor olması. Bugün aslında daha hafif bir şeyler yazmayı planlıyordum, fakat son birkaç gündür teknoloji gündemini sarsan gelişmeleri ve zihnimde dönüp duran düşünceleri paylaşmadan edemedim. En yeni yapay zeka modellerinin etrafında döne...

Deploying from GitHub sounds like a solved problem. Clone the repo. Detect the stack. Build an image. Run a container. Add SSL. Route traffic. That lower layer matters. In VibeNest we do not try to replace all of it from day one. The first deploy path sits on top of Coolify, which already handles a lot of the boring infrastructure: app resources, builds, containers, routing, SSL, logs, and restarts. From the projects we see on the platform, that gets a meaningful chunk of repos over the...

In a production AI agent pipeline, the difference between job done and job half-done is often invisible — not because the output is wrong, but because the process was incomplete. The agent skipped a mandatory step, self-certified that everything was fine, and delivered a result that looks complete. The user never knew. The system never caught it. The step was never executed. The Visible Checklist Pattern emerged from an empirical observation: an AI agent practitioner noticed that wh...