Practical engineering perspectives from the engineers who build, scale, and secure enterprise software every day.
Learn how Generative Engine Optimization helps businesses get cited in AI search answers from ChatGPT, Google AI Overviews, and Perplexity with practical steps.
Autonomous AI agents that browse the web, write code, call APIs, and execute multi-step workflows are no longer a research demo. They are running in enterprise production right now. Here is what we have learned building and deploying them at scale — what works, what breaks, and what you need in place before you ship.
Running large language models in production is expensive. After managing AI infrastructure for dozens of enterprise clients, we have developed a systematic playbook for reducing LLM costs dramatically while keeping response quality high.
As enterprises rush to deploy AI agents, a new class of vulnerabilities is emerging that most security teams have never seen before. Prompt injection, insecure tool use, and data exfiltration through model outputs are real threats we are actively defending against in production.
Gartner's research shows that the vast majority of enterprise AI initiatives fail before they ship. After running dozens of enterprise AI programmes, we've identified why, and what the successful 13% do differently.