Most teams are still piloting AI - TeamForm is shipping it. In this session, we show how we built enterprise and production-ready generative dashboards in weeks on AWS Bedrock and AgentCore, and how an AI-native operating model made that velocity possible. Learn what it actually takes to operationalise AI across product and engineering, not just prototype it.
What this session is about
Playbook
Editorial commentary · what to actually do about this on Monday
The concept
Generative dashboards — users describe what they want; the agent constructs the dashboard, query, visualisation. Built in weeks on Bedrock + AgentCore.
Why it matters
Static dashboards don't keep up with question variety. The BI team's backlog is the bottleneck for analytical insight in most organisations.
The hard parts
Trust. Users won't believe a dashboard the AI generated unless they can audit how it was built. Hallucinated metrics are catastrophic.
Playbook moves
(1) Show the SQL/spec the agent generated — make it auditable. (2) Let users edit. Treat the agent as a *draft generator*, not the final authority. (3) Govern the underlying data model rigorously — the agent only as good as the schema it queries.
The surprise
Generative dashboards work because you can drop the BI team's backlog. The hidden cost: someone needs to govern the *data model* the agent queries. That used to be the BI team's job. If you displace BI without replacing the governance, you get fast-but-wrong dashboards. Reassign the data modelling responsibility before you ship.
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Independent editorial perspective — not an official AWS or speaker statement. Designed for executives evaluating what to brief their teams on next.
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