Memory safety is not just a privacy concern. In agent systems, bad memory changes future behavior. Learn how typed schemas, policy-gated writes, auditable reads, and safe deletion make memory part of runtime correctness.
Requirements are not just requests to implement. They are clues that help uncover the real problem users need solved.
xAPI support is not one feature. It can mean statement ingestion, launch, package handling, proxy delivery, reporting, or cmi5 workflow. This article shows how to evaluate each capability and ask for proof that matches your delivery model.
Personalization in agents works best when memory is narrow, typed, reviewable, and clearly separated from sensitive systems. This article explains how to store useful preferences without creating invasive or unsafe agent behavior.
Good names make intent visible, reduce cognitive load, and turn code into a language developers can understand without constant explanation.
Most xAPI reporting problems begin long before the dashboard. They start when teams emit valid statements without defining stable identity, IDs, context, registration, and result semantics that reporting can trust.
Memory bugs in AI agents usually come from bad writes, not weak recall. Learn how to design write policies that decide what an agent should persist, when it should write, and when it should not.
Security is strongest when it is built into every boundary, permission, and design decision instead of added at the end.
“HTTP success does not mean valid xAPI. Learn a layered debugging workflow for rejected statements, cmi5 contract issues, batch failures, and accepted data that still breaks reporting.
Procedural memory is not about facts or chat history. It is the reusable method an agent follows to complete recurring tasks. This article explains why skills matter, how they work, and why they make agents behave more like software systems than chat systems.