Industry insights from the people building AI.
How voice AI agents keep a conversation going while a backend handles real tasks like bookings: the delegation structure, when to answer or delegate, and what makes a good voice agent.
Prompt caching stores and reuses the work done on the unchanged opening of your prompt. Learn how it works, implicit vs. explicit caching, the break-even math, and four mistakes that break the cache.
What compaction means in AI, why long chats lose earlier details, automatic vs. manual compaction, three habits for long chats, and why you should keep the original alongside any summary.
How to improve speech recognition accuracy: compare batch, live, and translation setups, see a 4.8s vs. 32s airport test, and use keywords, context, and glossaries to get names and numbers right.
What context engineering means, how it differs from prompt and harness engineering, why AI answers drift in long chats, and four methods with before-and-after examples.
What prompt injection is, how direct and indirect attacks differ, three realistic scenarios, and an OWASP-based checklist to keep your AI agents safe.
Agent = model + harness. See what harness engineering means, how it differs from prompt and context engineering, the four parts of a harness, and a simple no-code harness you can build today.
