AIM201IntermediateBreakout sessionAI & Machine Learning Playbook 5 live updates

From demo to deployment: solving agentic AI's toughest challenges

What this session is about

Most AI agent projects stall when moving from prototype to production. This session tackles the top challenges builders face when deploying agentic AI at scale. You'll learn how to answer the fundamental question of whether to build custom agents or leverage pre-built agents for DevOps, security, development, and business productivity use cases. Then you'll discover how to address the critical production challenges of reliability, observability, cost management, security, and evaluation. Drawing from real customer deployments and AWS's portfolio of agentic AI capabilities, you'll gain actionable approaches for building agents that don't just demo well but ship and scale.

Playbook

Editorial commentary · what to actually do about this on Monday

The concept
The pilot-to-production gap for agents is real and the failure modes are predictable: reliability, observability, cost, security, evals. Build vs. buy decisions are harder than for SaaS because build-cost is hidden in ops.
Why it matters
Industry estimates suggest 70%+ of agent pilots never reach production. You'll be in that bucket if you don't pre-empt the predictable failures.
The hard parts
"It works in the notebook" is the new "it works on my machine." Demo environments hide everything that kills production: rate limits, cold starts, multi-user state, partial failures, cost runaway.
Playbook moves
(1) Write the production runbook *before* building. If you can't describe how to triage a failure, you're not ready to ship. (2) Pre-commit a budget per task. Cap it at the agent layer. (3) Define an offline eval suite on day one, even if small.
The surprise
The single highest-leverage practice in agent ops is the offline eval suite. It's tedious to build but it unlocks everything downstream — model upgrades, prompt iteration, regression testing, vendor swaps. Teams that skip evals end up trapped on a single model and prompt forever. ---

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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