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One file, one path: from package main to shipping a concurrent, observable Go service that fronts your models and never falls over. Every example is drawn from what AI engineers actually build in Go — streaming proxies, tool dispatchers, rate limiters, worker pools, context-cancelled model calls. No foo / bar filler. Companion reads: 🐍 Python for AI Developers (the sibling to this guide), 🏗️ Building High-Quality AI Agents , 🏢 Enterprise-Ready AI Agents . 📖 How to ...

Astro 7.2 was released on 6 August 2026 with experimental incremental static builds. The idea is simple: do not regenerate a prerendered page when its code and data have not changed. That can materially reduce build time on a large content site. The word experimental still matters, and a major-version upgrade is not a performance toggle in isolation. The release also adds an option to disable session support, background mode for astro preview , and a simpler relative entry point for a custom...

If you sell clothing online you need on-model photography, and on-model photography means booking a model, renting a space, and waiting on retouching. Three to five days per round. flat-lay — from an MIT-licensed skill library I have been working through — collapses that to about 60 seconds. You give it a flat-lay garment photo and a pose reference, and it dresses the person in the garment. The interesting part for a developer audience is not that it works. It is that the prompt has a ri...

Kubernetes Probes as Failure Detectors: Semantics, Timing, and Cascading Risk Kubernetes probes are distributed-systems failure detectors with different control effects. A readiness failure removes a Pod from Service endpoints; a liveness failure asks the kubelet to restart the container. The distinction matters because detection is necessarily imperfect: aggressive thresholds reduce detection latency but increase false positives under transient load. Readiness protects traffic; ...

Technology is becoming increasingly personalized. Streaming platforms recommend movies, shopping websites suggest products, and fitness applications adapt plans according to individual users. The same approach can be useful in personal beauty and hair-care technology. Curly hair is a good example because users can have significantly different needs even when they describe their hair using the same general term. Why One Recommendation Does Not Work for Everyone A recommendation system...

When the self-improving agent almost lost the host's work: a postmortem On 2026-08-20, EMRG's own scheduled task stashed the host's uncommitted edits — twice, with no reflog trace — before the loop caught the bug, rewrote the rule, and added a regression test. Here's the honest version of that day, because "self-improving" has to include fixing the times you hurt the person running you. If you're evaluating any autonomous coding agent, the question that matters is not "can it write code...

Building FOSS is mostly rewarding and occasionally aggravating. Once in a while it requires some cleverness. The old contract between maintainers and users was simple enough. We build the software, you use it, you report what breaks. Some of you stick around and contribute. The project gets battle-tested by people whose problems I would never have thought of, and everyone comes out ahead. That contract is under some strain right now. Part of it is noise: AI slop, automated issues filed by ...

Building a chat application may seem simple at first. A user sends a message, another user receives it, and the conversation continues. But once your application grows from a few users to millions, the architecture becomes much more interesting. You need to think about: How do users connect in real time? How are messages delivered? Where are messages stored? What happens when a server crashes? How do you support millions of concurrent connections? How do users receive mes...

Designing a GDPR‑ and UK Online Safety Act‑Ready Serverless Plugin System for AI‑Driven Career Assistants on AWS Meta: Learn how to build an extensible, compliant serverless plugin architecture for AI career assistants on AWS, balancing real‑time generative coaching with GDPR and UK Online Safety Act requirements. Key Insights A plugin‑based serverless design lets you add new AI capabilities without redeploying the core assistant, reducing time‑to‑market by up to 40 %. Em...

Great Products Start With Real Problems Developers often begin projects by asking what they can build. Entrepreneurs often begin by asking what people need. The most effective products usually combine both approaches: technical execution and genuine problem solving. The story of Sara Blakely and Spanx provides an interesting example of this principle. Her journey started with an everyday problem and evolved into a major consumer brand. For developers and startup builders, the lesson ...

You are building a LINE customer flow and start with a confirm template. Then the requirements grow: Confirm Cancel Change address Contact support At this point, the problem is no longer “How can I add more buttons to a confirm template?” The real question is: Which LINE message type matches the decision the user needs to make? A LINE confirm template is intentionally limited to two actions. It is designed for one binary decision—not as a compact menu. When t...

Article URL: https://chipsandcheese.com/p/sifives-first-server-platform Comments URL: https://news.ycombinator.com/item?id=49428638 Points: 35 # Comments: 7

Article URL: https://www.laude.org/updates/headlong-a-microharness-for-persistent-agents Comments URL: https://news.ycombinator.com/item?id=49428882 Points: 45 # Comments: 15

Article URL: https://knowablemagazine.org/content/article/physical-world/2026/volcanoes-that-made-history Comments URL: https://news.ycombinator.com/item?id=49428972 Points: 4 # Comments: 0

It's a macOS menu bar app that reads the text of your focused window every few seconds through the Accessibility API. No screenshots, no video, or OCR. It writes plain markdown, one file per day, into a folder you choose. Point Claude Code (or anything with file access) at the folder and ask "what did I work on Tuesday?" or have it build memory about your projects. The folder contains an AGENTS.md explaining the format to the model. Thought it might be useful for someone so chucked it up on GitH...

The AI hedge fund went from "the talk of Wall Street" to "subject of federal subpoenas" faster than you can say "diversify your portfolio."

Airbound's ultra-lightweight approach to drone delivery has attracted backing from Greenoaks, DoorDash, and Silicon Valley investor Lachy Groom.

Originally published at ai.bedvibe.studio . There is an assumption almost every practitioner carries without examining it: if your dataset has bad samples in it, the loss will tell you. Corrupted rows spike. Broken files stick out. Sort by per-sample loss, look at the top of the list, and there is your garbage. I believed it too. Two separate failures in my own work say it is wrong, and they fail in the same direction — quietly. The reproducible one: a dataset that cannot b...

Intro While building a simple A‑share market monitor for my quant lab work, I initially only cared about extracting obvious metrics: last price, total trading volume, and so on. My naive assumption was that pulling raw JSON from an A‑share real‑time market API and rendering it would finish the job. Once I started running short‑term trading simulation workflows, I realized most actionable insight lives inside structured order‑book data. Level‑2 data is far more than a basic price snapshot....

Originally published at ai.bedvibe.studio . I built a text-to-speech product and kept getting burned by the same thing. On normal sentences the model sounded great. Then it would hit a number, a date, an acronym or a name, and quietly mangle it. Worse, the metric everyone reaches for — Word Error Rate — was lying to me in both directions. It flagged perfectly good audio as broken because the script said 3:30 PM and the transcript said "three thirty pee em." And it missed real failu...

Tired of explaining the same things again and again to your AI Agent? Frustrated because the AI keeps forgetting minute things custom to your codebase which needs to be kept in mind in each change? This is the current scenario for most people using AI agents to build their software. You handoff a task to it, it gives back the solution but misses something. You explain that to it, it nods back and then does it again. I myself did it until i came to know about Skills. What ...

In the professional world—especially in high-stakes tech environments—we are conditioned to believe that career advancement is a direct result of having the right answers. From the moment we step into our first junior role, we feel the pressure to be the "smartest person in the room." We equate confidence with certainty and value with the ability to provide instant solutions. But after years of working with founders, engineering leaders, and product builders, I have discovered a fundamental t...

Originally published at ai.bedvibe.studio . I built a real-time tracker in Rust — about two thousand lines — that reads a live ADS-B feed, keeps a Kalman-filtered track per aircraft, and screens every pair for closest approach against separation minima. Roughly 150 aircraft, a full cycle in under a millisecond. It ran clean. Tests passed, the picture looked right, the numbers were plausible. It was refusing about one measurement in nine , and the only reason I ever found out is that ...

First post in a build-in-public series about verdict , an MCP server that gives coding agents structured, sandboxed test feedback. The problem Watch a coding agent work and you'll see it run pytest in your shell, unsandboxed, and then push 40,000 tokens of raw output through its context window to answer one question: did my change break anything? That's three problems in one command: Token waste. The agent needs ~10 lines of signal and pays for a wall of dots, wa...

Our AI agent posts publicly every day — social posts, replies to strangers, comments on other people's articles — with no human reviewing individual messages before they go out. That sentence should make you nervous. It makes us nervous, and we built the thing. Rate limits alone don't fix it. An agent that sends 20 polite, on-topic messages is fine; an agent that sends 20 copies of the same "Great post! 🚀" is a spammer at any rate. Volume and quality fail differently, so they need different m...

Classic Machine Learning Through the Eyes of an SRE — Part 8 The most dangerous output in my whole Week-1 study set wasn't a bad prediction. It was a beautiful tree. Hierarchical clustering produces a dendrogram, that elegant diagram where every account, ticket, or incident nests inside ever-larger families. It looks like discovered truth. Stakeholders lean in. Someone screenshots it for the QBR deck. Nothing else in the set looks as convincing while being as capable of being completel...

By zipflow.xyz This is an independent technical analysis of DeepSeek's public research and documentation. It is not an official DeepSeek statement, and it does not claim that the current Vision-Exp API is available through our upstream channel. When DeepSeek released deepseek-v4-flash-vision-exp , the obvious story was that a text-focused model had finally gained native image input. The more useful story is longer: DeepSeek had already spent years exploring visual data, vision-language...

Runbooks still say "renew the SSL certificate" when the browser warning is obsolete protocol . The certificate can be brand new. The tunnel is still TLS 1.0. This is a shortened English note. The tables, handshake diagram, and OpenSSL CLI checks live on the original post: https://sunshout.tistory.com/2206 SSL vs TLS (the only distinction that matters) SSL is a Netscape protocol from the 1990s. SSL 3.0 is withdrawn (POODLE and friends). What every browser speaks now is T...

The blunt tool is still in a lot of GRUB files: GRUB_CMDLINE_LINUX_DEFAULT = "isolcpus=0,1" Then update-grub (or grub2-mkconfig ) and reboot. Userspace tasks stop landing on CPU0/1. That is all most people verify — they fire a few busy loops and top looks empty on those cores. IRQs do not care. isolcpus is a scheduler isolation hint. Hardware interrupts can still fire on the "isolated" CPUs. I watched seven tight loops leave 0/1 idle for processes while /proc/i...

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