AgentOps Briefing Agenda

From Agent Prototype to Production: AgentOps Readiness on Microsoft Foundry

Other options:

  1. AgentOps for Production-Ready AI Agents on Microsoft Foundry
  2. Evaluate, Ship, Observe, Operate: An AgentOps Model for AI Agents
  3. From Agent Demos to Reliable Operations: A Practical AgentOps Session
  4. Operationalizing AI Agents with Evaluation, Observability, and CI/CD Gates

Abstract

AI agents are moving quickly from prototypes into customer-facing and business-critical workflows. That shift creates a new operational challenge: teams need confidence that agents are evaluated consistently, monitored effectively, governed responsibly, and released through repeatable gates.

In this short (~1-hour) session, we introduce a practical AgentOps operating model for production AI agents on Microsoft Foundry. We cover evaluation strategy, CI/CD quality gates, observability, diagnostics, Responsible AI readiness, red-team follow-through, and Day-2 operations. The session includes a demo story showing a release-readiness flow: an existing Foundry agent is evaluated, a regression is blocked before release, the issue is fixed, readiness evidence is reviewed, and telemetry links the release decision back to runtime behavior.

Attendees leave with a production-readiness checklist and a practical starting path for moving one agent from “it works in testing” to “we can operate this safely.”

Timeboxed flow

Time Segment Purpose
0:00-0:02 Opening and promise Frame the shift from prototype success to production confidence.
0:02-0:06 The production gap Set urgency: prototypes are cheap, production needs proof.
0:06-0:10 Complexity from prompts to agents Show why agentic systems need stronger operating discipline.
0:10-0:15 AgentOps operating model Introduce the four pillars: Evaluate, Ship, Observe, Operate.
0:15-0:19 Maturity model Quick self-assessment for the audience.
0:19-0:24 Foundry as control plane Clarify roles across Foundry, Azure Monitor, repo, and CI/CD.
0:24-0:28 Production readiness checklist Make the release evidence contract concrete.
0:28-0:33 Evaluation strategy Show how release evidence is produced.
0:33-0:37 Red teaming and AI safety Separate safety from quality; reach governance audience.
0:37-0:42 CI/CD gates for agentic AI Show how gates enforce release evidence.
0:42-0:46 Observability for agents Traces, telemetry correlation, dashboards, alerting.
0:46-0:50 From telemetry to action Closed loop: trace - diagnosis - new eval row - gate.
0:50-0:52 Day-2 operations - four concerns Observe, govern, protect, optimize.
0:52-0:56 AI incident runbook Severity, triage flow, containment first.
0:56-0:58 Model lifecycle and canary Treat model changes as release candidates.
0:58-1:00 Adoption blueprint and close Start with one production-candidate agent.

Speaker guidance

Emphasize:

  • The customer problem is production confidence, not tooling novelty.
  • The strongest value moment is the failed gate: if the agent regresses, the release stops.
  • Foundry remains the control plane and system of record.
  • AgentOps adds the repeatable operating model around evaluation, repo, CI/CD, diagnostics, observability, and release evidence.
  • Observability must connect runtime traces to release decisions and future evaluations.
  • Safety and quality are different signals; both are required before release.
  • Day-2 operations turn signals into action through the incident runbook and model lifecycle discipline.
  • The deck stands on its own conceptually. An optional backup video may be recorded but is not part of the main session flow.

Avoid:

  • Making the session about AgentOps Toolkit.
  • Starting with installation details.
  • Spending too much time on command syntax.
  • Describing AgentOps as a replacement for Foundry.
  • Treating observability as generic infrastructure monitoring.
  • Treating Day-2 as a single afterthought slide; it deserves the incident runbook and model lifecycle depth.

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