AI agents are getting new capabilities via skills, modular packages of instructions that an agent loads on demand to handle specific tasks. But a skill is only as good as the context the agent runs on. If your agent doesn't know your customer history, your compliance rules, or your data lineage, even a well-written skill is derailing.
Furthermore, context drift, skill hierarchy and ai ready data impact agent accuracy and performance.
This session looks at what happens when you pair smart skills with a curated context layer.
We'll walk through how DataGOL's ContextOS feeds live organizational context into agent workflows, how skills can be hierarchically organized such that agents are not confused, skills and context are not self conflicting, and designed correctly.
Expect a live build: a custom skill wired to real context, running an actual enterprise task end to end.
Who should attend: engineering leader, AI platform developers, and anyone evaluating how to move from one-off prompts to durable, context-aware automation.
We'll close with a discussion: what's the one workflow at your company that keeps breaking because the AI doesn't have the right context at the right moment?
