Auto-aggregated global tech articles · 853 posts
I have a question for those who are using AI to write code. What is the basis for your "OK" during the review? There are 40 files changed, and there’s no time to read them all. The tests pass. It looks fine at a glance. So, merge it. — This is not a review; it is a ritual of approval. While build
How AI Agents Are Changing the Way We Use the Internet The internet is moving from a world where we search for information to a world where AI systems can help us find, understand, and act on that information. This shift is being driven by AI agents. What is an AI agent? An AI agent i
A lot of us run self-hosted gateways or use third-party relays to access OpenAI/Anthropic models. The problem is, you're trusting the relay to actually serve the model you're paying for. I built Relaylens to solve that. It's a deterministic probe that checks model authenticity using the provider's n
I am currently planning to use Golang for my project. I want to know which LLM provider works best to generate Golang code. Is it Anthropic or OpenAI or Google Models? submitted by /u/dikesm [link] [留言]
This article demonstrates how an LLM can produce a fully transparent chain of reasoning when guided by the A11 architecture. In many modern domains where AI agents are already being used—finance, healthcare support, autonomous operations, safety‑critical tooling—opaque “black box” behavior is no lon
AI coding agents like Claude Code read your .env files, cat command output, and run shell commands on your behalf. By design, every one of those actions gets written verbatim into a local session transcript (~/.claude/projects/**/*.jsonl) so the agent can resume sessions later. That means anything
A free model will write wrong C++ template code. That is not a problem when the compiler is the validator. In this experiment, a free model wrote ten SFINAE detectors; nine reached correctness after feeding compiler errors back into the prompt. The tenth needed one human sentence. Total cost: zero d
Agentic Security Testing Automation: From Vulnerability Discovery to Remediation-in-Loop (2025-2026) Intro: Security testing is undergoing a structural transformation driven by AI Agents. Autonomous penetration testing Agents topped the HackerOne leaderboard, defeating hourly-billed human experts
Agent Self-Evolution: A Comprehensive Survey from One-Shot Learning to Continuous Growth (2023–2026) Abstract: Large language models are static systems—trained once, capabilities frozen. But real-world tasks never repeat themselves. When agents begin to know what they don't know and actively self
The line came out of an essay about the app Cairn, at the end of a paragraph about visual restraint, and it was meant to stay there. The walls don't talk. Cairn is a room; you walk through it and notice what's there, and the walls carry color and texture and they don't address you. I wrote it to des
Every AI code review metric you track measures the hour before merge, and that is precisely the hour when the least information exists. Acceptance rate, test pass rate, and review approval all describe how a patch looked in isolation, not how it behaves under real traffic. Revert rate is the only si
A while ago I posted openGym here a self-hosted gym and body-weight tracker built with React + Node. It runs in two Docker containers, supports passkeys, has an Android APK, 14 languages and is AGPL licensed. The most common request I got since then was basically: "can you add some kind of coaching?
A developer needed a small notification service. GitHub pushes had to become short messages in a private chat. The budget was zero, and the tolerance for maintenance was lower than the budget. The obvious options were a hosted function or a cheap VPS. Both cost something, and both came with account
I've been building AI agents for a while now. Not chatbots. Not RAG demos. Real agents that take actions, make decisions, and run autonomously. Here's what nobody tells you. The gap between demo and production Every AI agent framework shows you a 5-line demo that works perfectly. Then y
I honestly am so confused rn as the ml community is overburst with people only caring about building rag modules and agentic ai for larger corporations. I have a passion for machine learning but honestly it feels really confusing as to what really counts today. I would love some advice on what exact
Our in-product RAG chatbot has two halves. The first is retrieval — hybrid BM25 + bge-m3 + a fine-tuned reranker, running locally as native .NET/ONNX, with zero API surface to anyone. The second is generation — turning the retrieved chunks into an answer, or into a proposed metadata change. That sec
Almost every AI lab now hands out a free tier. Google, Groq, Cerebras, Mistral, Cohere, NVIDIA, Cloudflare, OpenRouter, and a couple dozen more. Each one on its own is small. A few million tokens a month, a few thousand requests a day. Stacked together, they turn into something you can actually prot
Ryan chats with Greg Jennings, VP of Engineering for AI Products at Anaconda, about what it takes to build a secure-by-default AI coding agent, why prompts shouldn't be treated as strict security guardrails, and how Anaconda is using strategic acquisitions to secure the AI software supply chain.
I’m the author of a new preprint on repeated-query auditing of LLM brand recommendations, and the founder of Rankfor.AI. The practical question: how many times should we repeat a prompt before comparing results? The paper applies generalizability theory: estimate variance components from a pilot, th
FastDB is an (persistent) in-memory key/value store in Go. I made some updates to comments I've got (A big thank you to ShotgunPayDay) Test coverage : 96.54% https://codeberg.org/marcelloh/fastdb A test does the following: - Populate 1,000 items with rdom.Intn(1000000). - Inside for range b.N, exec
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![How does one approach towards machine learning?[D]](/storage/uploads/covers/2026/09/98972b45-0498-41d4-adda-21b42ff0a627.webp)
![How many repeated LLM queries are enough? Testing a pilot-based reliability protocol [R]](/storage/uploads/covers/2026/09/c78c7018-e7c8-4ad0-806d-47b070bb0a6f.webp)
