Episode
How Listen is building a system of AI Agents & subagents for specialized tasks | Florian Juengermann, CTO
- Podcast
- Max Agency
- Published
- Apr 23, 2026
- Duration seconds
- 2857
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Summary
Florian Juengermann is the co-founder and CTO of Listen, an AI startup that turns qualitative research across hundreds of interviews, surveys, and focus groups into structured, traceable insights. Listen's agents analyze responses at scale, and Florian has rearchitected the system multiple times to get there. In this conversation, he walks through the virtual table architecture at the core of their Research Agent, how small models run map-reduce classification across thousands of open-ended responses, and the self-reviewing feedback subagent that catches errors during long async runs. We also discuss: The three agents inside Listen's platform How Listen rearchitected from a simple RAG bot to a multi-agent system multiple times Why the PowerPoint subagent was completely rebuilt using Claude's code SDK Contextual prompt engineering as an alternative to skills How Listen keeps report numbers live as new interview responses come in When to trigger the long-running agent vs. showing early results What Florian looks for when hiring agent engineers References: Anthropic ChatGPT Claude Claude Code SDK E2B Emotional Intelligence GPT Mini Haiku Listen OpenAI Pandas Postgres Python Research Agent Render Zoom Where to find Florian: LinkedIn Twitter/X Where to find Harrison: LinkedIn Twitter/X Where to find LangChain: Website Docs Send feedback or questions to [email protected] Timestamps (00:00) Introduction (01:25) The three agents inside Listen's platform (03:15) Live chat vs. long async runs, and how Listen tunes for each (05:33) Under the hood of the Research Agent (06:37) Listen's virtual table architecture (07:34) How small models classify thousands of open-ended responses (10:05) Running code in a sandbox: how E2B fits in (11:52) Why Listen rebuilt the PowerPoint suba…