AI Agents & Automation
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Lightpanda Browser Loads 100 Pages in 2.3 Seconds — Chrome Needs 25
Every AI agent that browses the web right now is dragging around a full desktop browser. CSS rendering, GPU compositing, image decoding — all the visual machinery that exists so humans can look at pretty web pages. Machines don’t look at web pages. They parse the DOM, execute JavaScript, and move on. Lightpanda Browser is… Continue reading
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27K GitHub Stars in Weeks: learn-claude-code (by shareAI-lab) Breaks Down AI Coding Agents Into 12 Lessons
Claude Code has become one of the most talked-about developer tools in 2026. But while millions of developers use it daily, very few understand what actually happens under the hood. How does it decide which tool to call? How does it manage context when a codebase has thousands of files? How does it coordinate multiple… Continue reading
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LangChain’s GTM Agent Drove 250% More Conversions — Now the Framework Behind It Is Open Source
Most AI agent frameworks work fine for quick, single-step tasks. Ask an LLM to call an API, summarize a document, or answer a question — no problem. But hand it a multi-step workflow that runs for minutes or hours, requires juggling context from a dozen data sources, and needs to coordinate multiple sub-tasks in parallel?… Continue reading
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Can 3 Files Solve AI’s Agent Portability Problem? GitAgent Thinks So
Every major AI framework has its own way of defining agents. Claude Code uses CLAUDE.md. OpenAI’s Codex reads AGENTS.md. CrewAI has its YAML configs. Google ADK does its own thing. If you’ve built an agent for one platform and wanted to move it to another, you already know the answer: start over. GitAgent is a… Continue reading
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Nyne raised $5.3M to scan 250 million websites and tell AI agents who you really are
“How do I know you’re pregnant and sell you A, B, or C as early as possible?” That’s not a line from a dystopian novel. It’s how Nichole Wischoff, general partner at Wischoff Ventures, described the value proposition of Nyne — a startup she helped fund to the tune of $5.3 million in a seed… Continue reading
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OneCLI Puts a Security Gateway Between Your AI Agents and Your API Keys
AI agents are calling more APIs than ever — and most of them are doing it with raw, unscoped API keys sitting in environment variables. If a prompt injection attack tricks your agent into exfiltrating data, those keys go with it. OneCLI, an open-source credential vault written in Rust, offers a different architecture: agents never… Continue reading
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ChatGPT App Integrations: OpenAI’s Second Attempt at Becoming an App Platform
OpenAI has been quietly turning ChatGPT into something much bigger than a chatbot. With the rollout of ChatGPT App Integrations, you can now order dinner from DoorDash, queue up a Spotify playlist, hail an Uber, and browse Zillow listings — all from the same conversation window where you’d normally ask about Python syntax or meal… Continue reading
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$13B into OpenAI, yet Microsoft Copilot Cowork runs on Anthropic Claude
Microsoft has spent $13 billion backing OpenAI. It built Copilot around GPT models. It made OpenAI the default brain of its entire productivity suite. And then, on March 9, 2026, it launched the most ambitious AI agent feature in Microsoft 365 history — powered by Anthropic’s Claude. That decision alone tells you everything about where… Continue reading
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Hindsight (by Vectorize) Hits 91% on LongMemEval — the Case for Giving AI Agents Human-Like Memory
RAG was supposed to be the answer to AI’s memory problem. Feed your agent a vector database full of documents, let it retrieve relevant chunks at query time, and you’ve got context-aware responses. Except when you don’t. RAG falls apart when agents need to operate across multiple sessions, track how facts change over time, or… Continue reading
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OpenViking Treats AI Agent Memory Like a File System — and 9K GitHub Stars Say It’s Working
Every AI agent has the same embarrassing problem: it forgets everything the moment a session ends. Traditional RAG tries to fix this by chunking documents into vectors and hoping semantic search pulls back the right pieces. But anyone who’s built a production agent knows the reality — fragmented context, ballooning token costs, and retrieval that… Continue reading
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