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Aakash GuptaAakash Gupta

I stole the AI product stack of the top 1% product managers for you (full tutorial)

Rachel Wolen is CPO at Webflow ($4B company). She runs her whole day out of Claude Code and Cursor. She reveals how to build an agentic Chief of Staff (calendar, email, analytics agents), scale AI adoption from 0% to 30% with Builder Days, and ship AI-native features with MVO before MVP and proper evals. Full Writeup: https://www.news.aakashg.com/p/rachel-wolan-podcast Transcript: https://www.aakashg.com/ai-product-leadership-rachel-wolan-claude-code-cursor/ ---- Timestamps: 0:00 - Intro 1:30 - What Is IC CPO? 3:25 - Building Agentic Chief of Staff 7:03 - Calendar Agent Demo 9:30 - Email Triage Agent 13:01 - Linear Ad Start 13:48 - Analytics Agent (Snowflake + MCP) 17:27 - Linear Ad Start 19:26 - Building Agent from Scratch 29:16 - Setting Up Your Org for AI 34:25 - Shipping AI-Native Features 36:12 - Evals Story 40:58 - Distribution First Mindset 44:00 - Outro ---- 🏆 Thanks to our sponsor: Linear: Plan and build products like the best - https://linear.app/partners/aakash ---- Key Takeaways: 1. IC CPO means self-serving answers - "As a leader, you are able to get your own answers to practically any question." No waiting on data scientists. No back-and-forth with analytics. You have tools to self-serve insights, make analysis, automate workflows. Model behavior for your team to inspire them. 2. Calendar agent analyzes time - Runs weekly with prompt: "Analyze my calendar for last two weeks. Where could I delegate?" Returns delegation opportunities, red flags (double bookings, context switching), what to cut next week. Rachel gives output to EA. Spot on when shown live. 3. Email agent watches behavior - Complete inbox access. Runs triage, archives junk (calendar notifications, marketing), pins important messages, creates draft replies. Twist: watches behavior. If email sits too long, it notices. Caught meeting missing link. Rachel's rule: agent recommends, she approves. No autonomous sending. 4. Analytics agent via MCP - Connected Claude Code to Snowflake via MCP servers (not officially supported repos, just fed them to Claude Code). Ask natural language questions, get SQL executed real-time. "How many sites does Shirts.com have?" Claude writes query, authenticates via SSO, returns answer. Data scientist in pocket. 5. Accept the adoption curve - Your org follows standard curve: early adopters, early majority, late adopters, laggards. Create pathways for everyone to ascend ladder at their pace. Don't force everyone to be you. Rachel to team: "I only want to see prototypes when you have meetings with me." Creates culture investing in prototype quality. 6. Builder Days strategy - Give everyone access: Claude Code licenses, MCP to Snowflake/Tableau, Figma Make, Cursor with design system. Run Builder Days where champions help others through technical hurdles. Everyone demos something outside comfort zone. Results: 0% to 30% of designers using Cursor weekly after first Design Builder Day. 7. Rewrite career ladder - Webflow rewriting career ladder to make AI-native work an expectation, not nice-to-have. Create right incentives. Make sure people supported. Avoid AI for AI's sake. Example: Two designers built similar prototypes. Director caught early: "Go harmonize your prototypes now." Easier now than late in product cycle. 8. MVO before MVP framework - Most teams: Feature → PRD → Design → Ship. Rachel flips it. MVO (Minimal Viable Output) before MVP. Get model's output right FIRST using RAG, prompt engineering, context engineering. Only then build feature. "If you don't have desired outputs, don't spend time productizing the AI feature." 9. Evals are now your job - Brutal story: Webflow's AI app generator 2 weeks from launch. Rachel tested it. Agent kept dying. Realized: changed underlying model, evals didn't have coverage. Evals = test cases for models. Want dream evals (should pass) and edge cases (should fail). Use BrainTrust. Teaching PMs to write evals is part of AI PM toolkit now. 10. Build on your strengths - Framework: See trend → Is it applicable to customers? → What's YOUR core competency? Webflow's strength: bringing visitors to front door via CMS. Built production-grade app generator (not prototype like Lovable). Uses your brand, CMS, hosting, security. "We're bringing a way to prompt an app to production." Don't copy trends, leverage unique strengths. ---- 👨‍💻 Where to find Rachel Wolen: LinkedIn: https://www.linkedin.com/in/rachelwolan/ Twitter/X: https://x.com/rachelwolan Website: https://www.rachelwolan.com/ 👨‍💻 Where to find Aakash: Twitter: https://www.x.com/aakashg0 LinkedIn: https://www.linkedin.com/in/aagupta/ Newsletter: https://www.news.aakashg.com #aipm #claudecode #productmanagement ---- 🧠 About Product Growth: The world's largest podcast focused solely on product + growth, with over 200K+ listeners. 🔔 Subscribe and turn on notifications to get more videos like this.

Rachel WolenguestAakash Guptahost
Nov 29, 202545mWatch on YouTube ↗

At a glance

WHAT IT’S REALLY ABOUT

Webflow CPO’s AI agent stack for elite product leadership today

  1. The “IC CPO” mindset is framed as a leader’s ability to self-serve answers by investing in high-quality, accessible data and modern AI tooling across the team.
  2. Wolen demos an “agentic Chief of Staff” stack that analyzes calendar time, flags conflicts, recommends delegation, triages email with draft replies, and supports meeting/dinner research.
  3. She shows an analytics agent that uses MCP servers to query Snowflake/Tableau via natural language, enabled by documented dbt models to improve query accuracy and reliability.
  4. A live walkthrough illustrates creating a new agent (LinkedIn post generator) by generating a markdown agent spec, attaching reference files, and iterating through trial-and-adjust cycles.
  5. On shipping AI-native products, she highlights eval coverage as a critical failure point when swapping models, argues for building AI features aligned to company strengths, and urges a distribution-first approach focused on “answer engines” (AEO) as the next discovery wave.

IDEAS WORTH REMEMBERING

5 ideas

Define “IC CPO” as self-serve answers, then backsolve the infrastructure.

Wolen argues leaders should be able to answer most questions directly, which forces investment in clean data, self-serve access, and tools that let non-specialists retrieve insights without constant analyst dependency.

Start with high-leverage personal agents: calendar and inbox triage.

Her calendar agent reviews time allocation, flags overbooking/context switching, and suggests delegation; her email agent bulk-archives noise, pins important messages, and drafts replies—while keeping humans in control of sending.

Treat agents as iterative products, not one-shot automations.

She emphasizes running agents, observing errors, and tightening instructions; most agents take “three or four” iterations to dial in, especially for critical workflows like email drafting or analytics.

Analytics agents work best when your data models are documented.

Natural-language querying against Snowflake improved meaningfully once dbt models were well documented, enabling more accurate SQL generation and reducing back-and-forth to interpret schemas.

Use MCP servers to connect enterprise tools while preserving access controls.

She sets up MCP for Snowflake/Tableau using SSO credentials so the agent only queries data she already has permission to access, and she stresses privacy considerations in what context gets exposed to models.

WORDS WORTH SAVING

5 quotes

To me, IC CPO means that as a leader, you are able to get your own answers to practically any question.

— Rachel Wolen

It’s almost like having a data scientist in my pocket.

— Rachel Wolen

A lot of building an agent is trying it out and then going and adjusting what you want the agent to do.

— Rachel Wolen

We had changed the underlying model, and our evals didn’t have enough coverage to fail when we changed the model.

— Rachel Wolen

The next wave is really going to be around how do you get listed in answer engines?

— Rachel Wolen

IC CPO definition and implicationsAgentic Chief of Staff (calendar + email)MCP setup for Snowflake/TableauNatural language analytics with documented dbt modelsBuilding agents from scratch in Claude Code/CursorOrganizational adoption: training, builder days, career ladderEvals, model swaps, and distribution-first (AEO) strategy

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