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AI for Agents Workshop

Event artwork for AI for Agents Workshop

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The AIE NetworkAll Things AIPeripety LabsAll Things Open
About this event

What to expect

Master the art of strategic AI agent deployment and learn to make better delegation decisions before costly mistakes happen. This intensive, full-day workshop moves beyond experimentation to give business and technical leaders a proven framework for deciding when AI agents create value—and when they introduce unnecessary risk.

Why This Workshop Matters

Many organizations have experimented with AI agents, but far fewer have moved confidently into sustained, responsible execution. You've likely seen the pattern: impressive prototypes that stall before production, uncertainty about where agents actually add value, late-breaking security and governance concerns, and misalignment between business and technical stakeholders about what success should look like. These issues typically surface only after cost, complexity, or risk have already compounded.

This workshop provides the blueprint for shifting from experimentation to execution—not by pushing agents everywhere, but by teaching you when agents make sense, when they don't, and how to make sound decisions when autonomy is on the table.

What You'll Learn

By the end of this session, you'll leave with a practical decision-making framework you can apply immediately to real initiatives:

  • Determine whether an agent is appropriate for a given problem—or whether a copilot or traditional automation is the better choice
  • Evaluate agent proposals with clear understanding of autonomy, risk, and tradeoffs
  • Anticipate organizational, architectural, and governance factors that separate successful deployments from stalled experiments
  • Identify common failure modes early—while they're still inexpensive to address
  • Distinguish between degrees of agency and understand how they change cost, risk, and accountability

Technical Ecosystem Overview

The workshop includes a high-level technical orientation to the AI agent ecosystem, covering platforms, Model Context Protocol (MCP), and model selection tradeoffs. You'll also get a balanced discussion of the benefits and risks of using Small Language Models (SLMs) in agentic workflows, particularly when autonomy and tool access are involved.

What's Included

Participants receive a comprehensive blueprint outlining the conditions required for agent success—and the signals that indicate trouble. You'll gain a realistic understanding of the cost, complexity, and operational demands of agent-based systems, plus clear guidance for inco

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