Auto-aggregated global tech articles · 163 posts
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