How I AI
Claude Code for Product Managers: Research, Writing, Context Libraries, Custom To-Do System, and More | Teresa Torres
How I AI
•January 19, 2026•43 min
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How I AI•Jan 19, 2026
Why It Matters
The discussion shows how non‑technical product managers can harness AI tools like Claude Code to regain control over their task and research processes, boosting efficiency and insight generation. As AI becomes integral to daily work, learning to craft personalized, searchable workflows is crucial for staying productive and making data‑driven decisions.
Key Takeaways
- •Claude Code replaces Trello for personalized task management.
- •Slash commands automate daily to‑do generation in Obsidian.
- •AI tags and searches tasks, ideas, and research automatically.
- •Integrated research digest summarizes preprint papers for quick insights.
- •Pair‑programming mindset extends AI assistance beyond coding.
Pulse Analysis
Teresa Torres shows how Claude Code can become a bespoke task manager, eliminating the friction of Trello and other generic boards. By defining a simple "/today" slash command, Claude pulls due items from her Obsidian vault, creates markdown files, and even tags them, delivering a ready‑to‑act list each morning. This workflow blends a terminal‑based LLM with a local knowledge base, giving product leaders instant visibility into sales pipelines, bug reports, and idea backlogs without navigating multiple GUIs.
The research side of her system turns daily paper hunting into a low‑effort habit. A plugin queries the Archive preprint server, writes a markdown digest, and then Claude generates method‑focused summaries that highlight effect sizes and study quality. Saved PDFs are organized by topic, and the next day Claude produces concise briefs, enabling Teresa to critique findings on LinkedIn within minutes. The result is a continuous learning loop that feeds product discovery with up‑to‑date academic insights.
Beyond specific use cases, Torres treats Claude as a pair‑programming partner for every workflow. The AI handles tagging, context retrieval, and even suggests task permutations, freeing product managers to focus on strategy rather than administration. By storing everything as plain markdown, she builds a scalable context library that any LLM can query, turning a personal productivity stack into a reusable asset for teams. This approach demonstrates how AI‑driven automation can reshape product discovery, research synthesis, and daily execution for modern startups.
Episode Description
Teresa Torres is the author of Continuous Discovery Habits and an internationally acclaimed speaker and coach. In this episode, Teresa demonstrates how she’s built a personalized productivity system using Claude Code to manage her tasks, automate research collection, and improve her writing. She shows how non-developers can leverage AI tools to create personalized workflows that match their unique needs and thinking style.
What you’ll learn:
How Teresa built a personalized task management system in Claude Code that matches her exact workflow needs
Why she moved from Trello to a markdown-based system that gives her complete control and searchability
How she automated academic research collection with daily digests of relevant papers
Her strategy for organizing context files to make Claude more effective without overwhelming it
Why “pair programming” with Claude has become her approach to everything from writing to task management
How she uses Claude as a writing partner while maintaining her authentic voice
The power of slash commands and automation to reduce friction in daily workflows
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Brought to you by:
Brex—The intelligent finance platform built for founders
Graphite—The next generation of code review
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In this episode, we cover:
(00:00) Introduction to Teresa Torres
(02:10) Why Claude Code became Teresa’s productivity tool of choice
(03:00) The evolution from browser-based AI to terminal-based workflows
(04:14) Demo: Creating a personalized task management system
(07:52) How the task system works with markdown files and Obsidian
(12:56) Quick recap
(14:13) Taking notes within tasks for better searchability
(15:54) Demo: Automated research digest workflow
(19:32) How the research plugin searches and summarizes academic papers
(24:43) Filtering overwhelming information sources
(29:00) Using small, focused context files instead of one large document
(32:58) Claude as a writing partner: review, research, and refinement
(35:34) Recap of workflows and lightning round
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Tools referenced:
• Claude Code: https://claude.ai/
• Obsidian: https://Obsidian.md/
• VS Code: https://code.visualstudio.com/
• Descript: https://www.descript.com/
• ChatGPT: https://chat.openai.com/
• Trello: https://trello.com/
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Other references:
• Continuous Discovery Habits: https://www.producttalk.org/continuous-discovery-habits/
• Google Scholar: https://scholar.google.com/
• Claude Code: What It Is, How It’s Different, and Why Non-Technical People Should Use It: https://www.producttalk.org/claude-code-what-it-is-and-how-its-different
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Where to find Teresa Torres:
Blog: https://producttalk.org/
Podcast: https://justnowpossible.com/
Book: https://www.amazon.com/Continuous-Discovery-Habits-Discover-Products/dp/1736633309
LinkedIn: https://www.linkedin.com/in/teresatorres/
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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
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Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.
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