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Subvolts take Learn to build flexible AI apps with advanced prompt engineering and tool call management. Oct 30, 2025
For you
Developers
Learn advanced techniques for building more dynamic and flexible AI applications using tool calls and context engineering.
Business
Understand how to empower both technical and non-technical users in AI development and deploy AI solutions effectively.
Hype note
3/5Notable

This episode provides a solid interview with an industry expert on advanced prompt engineering techniques.

Practical AI
Practical AI · Ep 334 Episode

While loops with tool calls

45 min Interview Hosts: Daniel Whitenack, Chris Benson
0:0044:45

Audio streams from Daniel Whitenack and Chris Benson. Your place is remembered on this device.

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From Subvolts

Summary and analysis by Subvolts editorial, AI-assisted.

Summary

This Practical AI episode features Jared Zoneraich discussing prompt engineering's evolution into context engineering and "while loops with tool calls." The conversation covers building flexible AI applications, managing tool calls, prompt testing and versioning, and enabling technical and non-technical users in AI development. They also explore coding agents and a phased approach to AI deployment.

Explained simply

This episode explains how to make AI programs more flexible by using "while loops" with tools. It's like teaching an AI to keep trying different actions until it gets the right result, making AI applications smarter and more useful for everyone.

Why listen

This episode offers practical insights for developers and product managers building AI applications. It demystifies advanced prompt engineering techniques like "while loops with tool calls" and context engineering, which are crucial for creating more dynamic and responsive AI systems. The discussion on testing, versioning, and empowering diverse teams is relevant as frontier labs like OpenAI, Google Gemini, and Anthropic push towards more sophisticated agentic capabilities and developer accessibility.

On the mic
  • HostDaniel Whitenack
  • HostChris Benson
  • GuestJared Zoneraichco-founder and CEO, PromptLayer
About
OpenAIGoogleAnthropicDeveloper ToolsCodingAgents
Key facts
  • Guest: Jared Zoneraich, co-founder and CEO of PromptLayer
  • Show: Practical AI
  • Length: 45 minutes
  • Key Concept: Prompt engineering evolved into context engineering and "while loops with tool calls"
  • Topics Covered: Building flexible AI apps, managing tool calls, testing/versioning prompts, empowering users, coding agents, AI deployment approach
Key moments and transcript

Chapters from the publisher ↗ · Transcript ↗ Key moments and transcript search come with a later piece.

Show notes from Daniel Whitenack and Chris Benson

Dan and Chris sit down (again) with Jared Zoneraich, co-founder and CEO of PromptLayer, to discuss how prompt engineering has evolved into context engineering (and while loops with tool calls). Jared shares insights on building flexible AI applications, managing tool calls, testing and versioning prompts, and empowering both technical and non-technical users in AI development. Along the way, they dive into coding agents and the “crawl-walk-run” approach to AI deployment.

Featuring: 

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Jargon decoded
context engineering
Jared Zoneraich
Making AI apps smarter by managing how they use information and tools.
while loops with tool calls
Jared Zoneraich
Teaching AI to repeatedly use tools until it achieves a goal.
coding agents
Daniel Whitenack, Chris Benson, Jared Zoneraich
AI programs designed to write or assist with writing computer code.
Published
Show
Practical AI · Daniel Whitenack and Chris Benson
Length
45 min
Companies
OpenAI, Google, Anthropic
Summary by
Subvolts, using an AI model (how we work). Spotted a mistake? Tell us.
#Developer Tools#Coding#Agents

Best of Practical AI

More on OpenAI this week

Questions people ask

What is context engineering?
Context engineering is an evolution of prompt engineering, focusing on building flexible AI applications by managing how AI uses information and tools.
What are "while loops with tool calls"?
This refers to a technique where an AI can repeatedly use tools or take actions until a specific condition is met, allowing for more dynamic problem-solving.

Page generated Oct 19, 2026. Summaries are Subvolts' own; the audio, artwork and notes belong to Daniel Whitenack and Chris Benson.