Episode

Nick and Zack from WorkOS @ AIE: building real-world AI tools & running conference workshops

Podcast: Scaling DevTools
Published: May 7, 2026
Duration seconds: 1708
Processing state: processed
Canonical source: https://podcast.scalingdevtools.com/episodes/nick-and-zack-from-workos-aie
Audio: https://media.transistor.fm/bad1cd1d/38b2434e.mp3
JSON: /v1/public/podcasts/scaling-devtools/episodes/nick-and-zack-from-workos-aie-building-real-world-ai-tools-running-conference-workshops
Markdown: /podcast/scaling-devtools/nick-and-zack-from-workos-aie-building-real-world-ai-tools-running-conference-workshops.md

Actions

POST https://stenobird.com/v1/public/podcasts/scaling-devtools/episodes/nick-and-zack-from-workos-aie-building-real-world-ai-tools-running-conference-workshops/transcription-requests
Idempotently request low-priority transcript generation for this episode.
GET https://stenobird.com/podcast/scaling-devtools/nick-and-zack-from-workos-aie-building-real-world-ai-tools-running-conference-workshops.md
Read the agent-friendly Markdown representation of this episode resource.

Summary

Developers explore how to build agentic loops that connect tools like Slack, Linear, and Notion to eliminate context switching. The discussion covers using LLMs to manage developer productivity and the potential for integrating biometric data into AI workflows.

Topics

AI Agents
Developer Productivity
Context Switching
MCP Servers
Automation Loops
Software Engineering
Tool Integration
Biometric Data

Highlights

Main idea: Agentic loops can automate the entire lifecycle from bug report in Slack to ticket creation in Linear and code verification
Practical takeaway: Use short-lived tokens and granular permissions to securely integrate third-party data into MCP servers
Failure mode: Endless stacking of automation loops can lead to developer burnout without defined inputs and outputs
Practical takeaway: Implementing a retrospective step in AI tools helps maintain memory and prune irrelevant context
Main idea: Integrating biometric data into LLMs can provide a personalized interface that monitors developer well-being and productivity

Chapters

1:00 Avoiding Developer Burnout: Discussing the importance of defined inputs and outputs for LLMs to prevent the exhaustion caused by infinite automation loops.
5:25 The Evolution of Coding: Reflecting on the shift from manual coding to managing high-level architectural tasks and workshops.
11:40 Secure Third-Party Integrations: Exploring how to manage permissions and authentication when connecting tools like Gmail to AI agents.
13:50 Eliminating Context Switching: How connecting Slack, Linear, and Notion allows developers to remain in 'focus mode' while automating ticket management.
18:00 Hands-on Workshop Design: The importance of interactive, keyboard-driven learning experiences in technical workshops.
26:15 AI-Driven Hardware Hacking: Using LLMs to rapidly prototype complex systems, such as software-defined radio interfaces.