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Aakash GuptaAakash Gupta

The Claude Code Analytics Workflow Top AI PMs Don’t Want You to Know

Frank Lee breaks down the complete AI PM workflow using Claude Code and MCP. Deep chart analysis, automated dashboards, customer feedback synthesis, PRD generation, and pushing directly to Linear or code all live demos. Full Writeup: https://www.news.aakashg.com/p/frank-lee-podcast Transcript: https://www.aakashg.com/mastering-analytics-and-claude-code-the-complete-aipm-workflow-with-frank-lee/ --- Timestamps: 0:00 - Intro 1:37 - Guest Introduction 1:47 - Most Powerful AIPM Workflow 3:45 - Setting Up Claude Code + MCP 6:28 - Context Management in Claude Code 9:41 - Ads 11:08 - Top 5 Use Cases for PMs 19:29 - Automating Dashboard Reporting 30:48 - Ads 33:01 - Customer Feedback Analysis 33:54 - Converting Insights into PRDs 39:24 - Pushing to Linear or Code 40:35 - Biggest Mistakes with MCP 45:19 - What Amplitude Is Shipping 50:28 - Outro --- 🏆 Thanks to our sponsors: 1. Amplitude: The market-leader in product analytics - https://amplitude.com/session-replay?utm_campaign=session-replay-launch-2025&utm_source=linkedin&utm_medium=organic-social&utm_content=productgrowthpodcast 2. Pendo: The #1 software experience management platform - http://www.pendo.io/aakash 3. Testkube: Leading test orchestration platform - http://testkube.io/ 4. Product Faculty: Get $550 off the AI PM Certification with code AAKASH550C7 - https://maven.com/product-faculty/ai-product-management-certification?promoCode=AAKASH550C7 5. Bolt: Ship AI-powered products 10x faster - https://bolt.new/solutions/product-manager?utm_source=Promoted&utm_medium=email&utm_campaign=aakash-product-growth --- Key Takeaways: 1. Claude Code + MCP is the most powerful AIPM workflow today - Connect your analytics tool via MCP, load your product context into a repo, and let the agent do analysis that used to take hours in minutes. 2. Deep chart analysis now takes 90 seconds instead of 3 hours - Drop a chart URL into Claude Code, trigger the analyse chart skill, and the agent navigates your data taxonomy, finds anomalies, and hypothesises why metrics changed. 3. Automate your entire weekly business review - Point Claude Code at your dashboards Monday morning. Get 3-5 top insights and the one urgent issue to tackle — no manual dashboard scanning ever again. 4. Customer feedback synthesis across all channels in one pass - Zendesk, Gong, Salesforce, Slack, app stores all unified. Claude Code navigates the MCP, clusters themes, and surfaces what customers love and hate that week. 5. PRDs write themselves from insights - Take the analysis output, point it at your PRD template in Cursor or Claude Code, and get a first draft spec in under 2 minutes. Iterate with command L or command K. 6. Skills are the most important Claude Code feature - A skill is just a named prompt with heuristics and tool instructions. It loads only when relevant, preventing context bloat and giving the agent a repeatable workflow. 7. The biggest MCP mistake is connecting too many servers - Every tool description burns context. Load only what's relevant to the workflow. Remove or hide tools that aren't being used for a given task. 8. MCP is not for complex orchestration - it's for data access - Set the right expectation. MCP connects AI to external systems easily. It's the first step, not the whole pipeline. 9. Granola has no MCP, so build a script instead - Frank used Claude Code to write a local script that dumps Granola meeting notes into his product repo. Now he can pull all meeting context with a single at-command. 10. The future of PMing is vibe PMing - Chart analysis, dashboard reporting, feedback synthesis, spec writing, and prototyping — all agent-driven. PMs who adopt this workflow now will have a massive advantage in 2-3 years. --- 👨‍💻 Where to find Frank Lee: Twitter: https://www.twitter.com/franklee LinkedIn: https://www.linkedin.com/in/franklee/ 👨‍💻 Where to find Aakash: Twitter: https://www.x.com/aakashg0 LinkedIn: https://www.linkedin.com/in/aagupta/ Newsletter: https://www.news.aakashg.com #claudecode #aipm --- 🧠 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.

Aakash GuptahostFrank Leeguest
Feb 24, 202653mWatch on YouTube ↗

At a glance

WHAT IT’S REALLY ABOUT

Claude Code + MCP turns analytics into end-to-end PM automation

  1. Frank Lee demonstrates a “vibe PMing” workflow where Claude Code/Cursor connected via MCP pulls product context and analytics data to answer questions and generate deliverables end-to-end.
  2. The setup centers on organizing durable product context (plans, specs, templates, meeting notes) in a GitHub-backed repo that Claude Code and Cursor can reference and update.
  3. Custom “Skills” (structured prompts + tool permissions) operationalize repeatable tasks like chart anomaly analysis, dashboard summaries, and feedback synthesis with consistent output formats.
  4. The workflow expands from quantitative analysis (charts/dashboards) to qualitative synthesis (Zendesk/Slack/surveys) and then into execution by drafting PRDs and pushing tickets or prototypes into Linear/code.
  5. They discuss common MCP pitfalls (too many irrelevant tools, wrong expectations) and rebut criticisms by highlighting tool optimization, improving auth/managed connectors, and dynamic tool calling to reduce context waste.

IDEAS WORTH REMEMBERING

5 ideas

Treat MCP as the data/action bridge, not the whole workflow.

MCP primarily lets models interact with external tools and data; the workflow power comes from layering Skills, good prompts, and curated toolsets on top of MCP connections.

Build a “product repo” as your persistent context layer.

Store roadmap notes, initiative folders, PRD templates, and terminology in markdown inside a GitHub repo so agents can reliably reference and generate consistent outputs across sessions and devices.

Codify recurring PM tasks as Skills with heuristics and output formats.

Lee’s chart/dashboard Skills specify what patterns to look for (spikes, seasonality, anomalies), how to query (e.g., charts three-at-a-time), and a standard narrative structure for business-ready summaries.

Automate weekly reporting by scheduling dashboard agents into where teams work.

Instead of building WBR slides manually, schedule agents to synthesize dashboards and push insights into Slack/email so meetings focus on decisions and solutions rather than reporting.

Connect quant changes to qual evidence in the same agent run.

After dashboard/chart analysis, the agent can pull related feedback, release notes/annotations, experiments, or session replay signals to form hypotheses about why metrics moved.

WORDS WORTH SAVING

5 quotes

“The most powerful thing is managing my product process in Claude Code and Cursor using a bunch of MCPs.”

— Frank Lee

“MCP… is the easiest way to connect your AI models with any external tools, action, and data.”

— Frank Lee

“At Amazon, I used to spend all of my Sundays… Now… Monday morning… [dashboards are] automatically synthesized.”

— Frank Lee

“They’re… correct. They’re too verbose. So I can go back to my prompt and say, ‘Hey, dramatically cut down the words.’”

— Frank Lee

“Sometimes people think that MCPs can do everything… [but] MCPs are easy ways for your AI to interact with external systems.”

— Frank Lee

Model Context Protocol (MCP) basics and valueClaude Code vs Cursor roles in PM workflowSkills as reusable prompt+tools “functions”Context management, compaction, and repo organizationAutomated anomaly detection and chart investigationsAutomated WBR/dashboard reporting to Slack/emailUnified customer feedback analysis and clusteringTurning insights into PRDs and routing to Linear/codeMCP pitfalls: tool bloat, ambiguity, latencyAmplitude’s upcoming agent suite and Slack agent

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