Tool Use - AI Conversations Why AI Agents Fail In Production And How To Fix It (ft Josh Purtell)
May 13, 2025
In this engaging discussion, Josh Purtell, Founder and CEO of Synth, shares insights on the pressing challenges of deploying AI agents in real-world applications. He reveals strategies for overcoming issues like observability and reliability, ensuring AI agents can perform effectively. Listeners learn about the importance of structured prompts, avoiding pitfalls like context window overload, and evaluating agent performance. Purtell also highlights the balance between high-value and low-value agents, providing a roadmap for businesses aiming to leverage AI technology confidently.
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High-Value vs Low-Value Agents
- Josh Purtell describes high-value agents producing valuable artifacts through multi-step processes.
- He contrasts this with low-cost, low-value agents that monitor and triage simpler tasks like customer support.
Communicate AI Agent Goals Clearly
- Clearly communicate what you want to your AI agent; vague instructions lead to unpredictable results.
- In enterprise settings, explicitly state all preferences, requirements, and constraints for best outcomes.
Use LLMs for Debugging Agents
- Use LLMs as verifiers to automate detecting unnecessary context or missing instructions.
- Convert agent traces into text and review with another LLM to quickly discover major issues.