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ChatGPT agent mode: The “little helper” that transformed recruiting, crafted user personas, and solved parking nightmares | Michal Peled (Honeybook)
Michal Peled is a Technical Operations Engineer at HoneyBook who specializes in building internal tools and automations that eliminate friction for teams. In this episode, Michal demonstrates three practical AI use cases: using ChatGPT’s agent mode to automate LinkedIn recruiting, transforming customer research into interactive AI personas, and creating a custom calendar solution for a very San Francisco–specific problem—avoiding expensive parking during Giants games.
What you’ll learn:
- How to use ChatGPT agent mode to automate LinkedIn recruiting and find high-quality candidates that manual searches missed
- The step-by-step process for turning static customer research into interactive AI personas that product and marketing teams can actually use
- Why NotebookLM excels at creating prompts from source material with proper citations
- How to structure agent-mode prompts to create effective “little helpers” that follow your exact workflow
- A practical framework for improving your prompts when AI tools aren’t giving you the results you want
- How internal tools teams can drive massive impact by focusing on eliminating friction in everyday workflows
—
Brought to you by:
Brex—The intelligent finance platform built for founders
Google Gemini—Your everyday AI assistant
—
In this episode, we cover:
(00:00) Introduction to Michal and ChatGPT agent mode
(02:10) Using agent mode for LinkedIn recruiting automation
(05:14) Creating effective prompts for agent mode
(10:50) Demo of agent mode searching LinkedIn profiles
(16:29) Results and team reception of the recruiting automation
(19:53) The outcome of implementing on Michal’s team
(23:50) Creating custom GPT personas from customer research
(28:43) Using NotebookLM to transform research into persona prompts
(35:00) Adding guardrails to custom GPT personas
(37:20) Demo of interacting with custom-persona GPTs
(41:02) Creating a calendar automation for parking during baseball games
(48:15) Lightning round and final thoughts
—
Tools referenced:
• ChatGPT: https://chat.openai.com/
• NotebookLM: https://notebooklm.google.com/
• Claude: https://claude.ai/
—
Other references:
• Google Calendar: https://calendar.google.com/
• HoneyBook: https://www.honeybook.com/
• LinkedIn: https://www.linkedin.com/
—
Where to find Michal Peled:
LinkedIn: https://www.linkedin.com/in/michalpeled/
—
Where to find Claire Vo:
ChatPRD: https://www.chatprd.ai/
Website: https://clairevo.com/
LinkedIn: https://www.linkedin.com/in/clairevo/
X: https://x.com/clairevo
—
Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].
View all episodes
By Claire Vo
4.8
143143 ratings
Michal Peled is a Technical Operations Engineer at HoneyBook who specializes in building internal tools and automations that eliminate friction for teams. In this episode, Michal demonstrates three practical AI use cases: using ChatGPT’s agent mode to automate LinkedIn recruiting, transforming customer research into interactive AI personas, and creating a custom calendar solution for a very San Francisco–specific problem—avoiding expensive parking during Giants games.
What you’ll learn:
- How to use ChatGPT agent mode to automate LinkedIn recruiting and find high-quality candidates that manual searches missed
- The step-by-step process for turning static customer research into interactive AI personas that product and marketing teams can actually use
- Why NotebookLM excels at creating prompts from source material with proper citations
- How to structure agent-mode prompts to create effective “little helpers” that follow your exact workflow
- A practical framework for improving your prompts when AI tools aren’t giving you the results you want
- How internal tools teams can drive massive impact by focusing on eliminating friction in everyday workflows
—
Brought to you by:
Brex—The intelligent finance platform built for founders
Google Gemini—Your everyday AI assistant
—
In this episode, we cover:
(00:00) Introduction to Michal and ChatGPT agent mode
(02:10) Using agent mode for LinkedIn recruiting automation
(05:14) Creating effective prompts for agent mode
(10:50) Demo of agent mode searching LinkedIn profiles
(16:29) Results and team reception of the recruiting automation
(19:53) The outcome of implementing on Michal’s team
(23:50) Creating custom GPT personas from customer research
(28:43) Using NotebookLM to transform research into persona prompts
(35:00) Adding guardrails to custom GPT personas
(37:20) Demo of interacting with custom-persona GPTs
(41:02) Creating a calendar automation for parking during baseball games
(48:15) Lightning round and final thoughts
—
Tools referenced:
• ChatGPT: https://chat.openai.com/
• NotebookLM: https://notebooklm.google.com/
• Claude: https://claude.ai/
—
Other references:
• Google Calendar: https://calendar.google.com/
• HoneyBook: https://www.honeybook.com/
• LinkedIn: https://www.linkedin.com/
—
Where to find Michal Peled:
LinkedIn: https://www.linkedin.com/in/michalpeled/
—
Where to find Claire Vo:
ChatPRD: https://www.chatprd.ai/
Website: https://clairevo.com/
LinkedIn: https://www.linkedin.com/in/clairevo/
X: https://x.com/clairevo
—
Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].
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