Introduction Every developer building on LLMs eventually hits the same wall: a single prompt, no matter how clever, is a one-shot transaction. You ask, the model answers, and the conversation ends...

Series context: This is the prerequisite guide for our upcoming Building AI Agents series starting tomorrow. If you want to code along (and you should!), get your environment ready today. Buildin...

We’ve spent the last two weeks diving deep into AI security — from MLSecOps: Securing the ML Pipeline to ML Pipeline Secrets Management — and the response has been incredible. The MLsecOps series s...

Introduction Every ML pipeline has secrets: OpenAI API keys, Hugging Face tokens, database passwords, cloud service credentials, model registry auth tokens, and Weights & Biases API keys. A ty...

Introduction In February 2026, OpenBMB released MiniCPM-o 4.5, a 9-billion-parameter model capable of full-duplex omni-modal interaction. It watches video, listens to audio, speaks back, and proce...

Introduction As LLMs become more capable, the benchmarks designed to measure them have become high-stakes arenas. A top-3 finish on the Open LLM Leaderboard can drive downloads, funding, and resea...

Introduction In 2016, researchers at Google showed they could replicate a $100M model with just $1,000 in API queries. In 2026, model extraction is easier than ever — API access, open-weight fine-...

Introduction Manual red teaming has a scaling problem. A skilled AI security professional can run perhaps 50–100 adversarial conversations per day. A production LLM system — processing millions of...

Introduction Most discussions of prompt injection focus on the obvious vectors: a user typing “Ignore previous instructions” into a chat window, or a malicious web page that an agent happens to br...

Introduction What happens when two AI agents decide to cooperate — against you? On the surface, multi-agent collaboration is a superpower. Crews of agents coordinating through frameworks like...