Why AI Agents Fail In Production And How To Fix It (ft Josh Purtell)

Unlock the reality of AI agents in production! While the AI agent gold rush is on, many businesses and developers struggle to move beyond expectation. This episode dives deep into the three fundamental challenges of AI agents: observability, reliability, and performance. Discover actionable strategies to overcome these hurdles and deploy your AI agent to production with confidence. Learn how to effectively communicate your needs to your AI, avoid common pitfalls like context window overload, and implement effective AI agent evals and debugging processes. We explore building high-value vs. low-value agents, structuring prompts for clarity, and the future of interacting with these powerful AI tools. If you're building or considering AI agents, this conversation is packed with insights on making them truly work.

Learn more about Synth: https://www.usesynth.ai/

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00:00:00 - intro

00:04:28 - Current & Upcoming Viable AI Agent Use Cases

00:08:11 - Common Pitfalls When Building AI Agents

00:13:32 - Strategies for Debugging Bad LLM Calls

00:21:46 - Enhancing AI Agent Observability

00:33:22 - AI Tooling: Build vs Buy Decision

00:38:51 - Choosing the Right LLM for Your Agent

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