How Freshworks' CPO Actually Builds Products With AI (Live Demo)

Freshworks went public in 2021, serves 75,000 customers, and used to ship on a 6-month release cycle. Their CPO rebuilt the entire product development process around AI agents and now ships in 2 weeks. In this episode, he opens Cursor and shows you the whole system live, from PRD to prototype to a Slack agent answering employee tickets. Full Writeup: https://www.news.aakashg.com/p/srini-raghavan-podcast Transcript: https://tinyurl.com/346tvx7x Timestamps: 0:00 - Intro 2:31 - Why PM, designer, and engineer titles go away 4:03 - Data first vs AI first, the AI PDLC, and PRD Genie 10:56 - Ads 13:04 - Live demo, initializing the 12 step process in cursor 24:36 - How to trust an AI generated PRD 27:02 - From PRD to working prototype in Figma Make 30:23 - Ads 33:54 - Why Figma Make and where judgment still matters 37:14 - Inside agent studio, workflows, knowledge, and the Slack demo 49:41 - Fresh Service MCP connected to Claude 57:01 - The PM to engineer ratio and how Freshworks hires AI PMs 🏆 Thanks to our sponsors: 1. Customer.io (http://customer.io/productgrowth) - Send smarter messages using your product data 2. Ariso (https://ariso.ai/aakash) - The AI operating partner for every manager and team 3. Product Faculty (https://www.productfaculty.com/?code=AAKASH150) - Get $150 off their #1 AI Builder Fellowship with code AAKASH150 3. Land PM Job (https://www.landpmjob.com/) - Cohort 4 is open to help you master the PM job search 5. Amplitude (https://tinyurl.com/b7nret7v) - The market leader in product analytics Key Takeaways: 1. The product builder replaces a 3 role handoff - The linear flow from PM to designer to engineer existed because each role could only do one job. With AI in every step, one person can research the customer, write the spec, build the prototype, and open the pull request. The three titles collapse into one. 2. Data first beats AI first - Most teams start with the AI layer. Freshworks built the foundation underneath it first, a design system, a coding system, and a shared repository. The AI only goes fast because the references it needs already exist. 3. An AI agent sits in every phase of the lifecycle - Discovery, design, planning, development, QA, deployment, and release each have a dedicated agent. A knowledge hub holds product context and dependencies, a context hub passes feature context between phases, and a central skills repository holds the rules, commands, and agents. The whole thing runs inside a governed framework with evals. 4. PRD Genie drafts 80 percent of the PRD instantly - It pulls usage metrics from the data lake, runs competitive benchmarks, gathers customer feedback, and maps internal dependencies. Then a CPO review agent checks the draft for strategic alignment, clarity, and edge cases. The PM stops gathering evidence and starts making calls. 5. Grounding is what stops hallucination at enterprise scale - You cannot let AI invent details when 75,000 customers and 300 million end users are downstream. Every markdown file the system generates records which version it referenced and why. Initialization is where that grounding gets set. 6. Judgment is the new PM skill - The AI is a copilot, not autopilot. In the demo the design missed the internal component library on the first pass and broke on narrow monitors, and both fixes came from a human who knew to look. Value shifts from operational work to knowing which reference to give and what to check. 7. Prototype on the scaffolding your customers already see - Instead of a blank canvas, the PRD gets dropped into a preloaded Fresh Service starter kit built on the internal design system. The prototype comes out already sitting inside the screen half a million users log into. New builds skip this step because they have no precedent to protect. 8. MCP collapses a day of ticket work into a single prompt - One prompt pulled 12 Windows 11 tickets from the last 60 days, clustered them into two patch rollouts, produced a root cause analysis, and recommended actions nobody asked for. A second prompt drafted knowledge base backed replies and logged them to every ticket. Tickets that took one to two hours each were closed in five minutes. 9. Hiring now means show me what you built - Curiosity is the screen, because almost nobody has done this work before. Interviews ask candidates to open cursor and walk through what they made. You can teach skills, you cannot teach passion, so the git repository is the signal. 👨‍💻 Where to find Srini: LinkedIn: https://www.linkedin.com/in/srinivasan28/ 👨‍💻 Where to find Aakash: Twitter: https://x.com/aakashgupta LinkedIn: https://www.linkedin.com/in/aagupta/ Newsletter: https://www.news.aakashg.com/ #aiproductmanagement #productbuilder 🧠 About Product Growth: The world's largest podcast focused solely on product + growth, with over 200K+ listeners. 🔔 Subscribe and turn on notifications.

Aakash GuptahostSrini Raghavanguest

Aug 24, 20261h 5mWatch on YouTube ↗

EPISODE INFO

Released: August 24, 2026
Duration: 1h 5m
Channel: Aakash Gupta
Watch on YouTube: ▶ Open ↗

EPISODE DESCRIPTION

Freshworks went public in 2021, serves 75,000 customers, and used to ship on a 6-month release cycle. Their CPO rebuilt the entire product development process around AI agents and now ships in 2 weeks. In this episode, he opens Cursor and shows you the whole system live, from PRD to prototype to a Slack agent answering employee tickets. Full Writeup: https://www.news.aakashg.com/p/srini-raghavan-podcast Transcript: https://tinyurl.com/346tvx7x Timestamps: 0:00 - Intro 2:31 - Why PM, designer, and engineer titles go away 4:03 - Data first vs AI first, the AI PDLC, and PRD Genie 10:56 - Ads 13:04 - Live demo, initializing the 12 step process in cursor 24:36 - How to trust an AI generated PRD 27:02 - From PRD to working prototype in Figma Make 30:23 - Ads 33:54 - Why Figma Make and where judgment still matters 37:14 - Inside agent studio, workflows, knowledge, and the Slack demo 49:41 - Fresh Service MCP connected to Claude 57:01 - The PM to engineer ratio and how Freshworks hires AI PMs 🏆 Thanks to our sponsors:
Customer.io (http://customer.io/productgrowth) - Send smarter messages using your product data
Ariso (https://ariso.ai/aakash) - The AI operating partner for every manager and team
Product Faculty (https://www.productfaculty.com/?code=AAKASH150) - Get $150 off their #1 AI Builder Fellowship with code AAKASH150
Land PM Job (https://www.landpmjob.com/) - Cohort 4 is open to help you master the PM job search
Amplitude (https://tinyurl.com/b7nret7v) - The market leader in product analytics
Key Takeaways:
1. The product builder replaces a 3 role handoff - The linear flow from PM to designer to engineer existed because each role could only do one job. With AI in every step, one person can research the customer, write the spec, build the prototype, and open the pull request. The three titles collapse into one.
1. Data first beats AI first - Most teams start with the AI layer. Freshworks built the foundation underneath it first, a design system, a coding system, and a shared repository. The AI only goes fast because the references it needs already exist.
1. An AI agent sits in every phase of the lifecycle - Discovery, design, planning, development, QA, deployment, and release each have a dedicated agent. A knowledge hub holds product context and dependencies, a context hub passes feature context between phases, and a central skills repository holds the rules, commands, and agents. The whole thing runs inside a governed framework with evals.
1. PRD Genie drafts 80 percent of the PRD instantly - It pulls usage metrics from the data lake, runs competitive benchmarks, gathers customer feedback, and maps internal dependencies. Then a CPO review agent checks the draft for strategic alignment, clarity, and edge cases. The PM stops gathering evidence and starts making calls.
1. Grounding is what stops hallucination at enterprise scale - You cannot let AI invent details when 75,000 customers and 300 million end users are downstream. Every markdown file the system generates records which version it referenced and why. Initialization is where that grounding gets set.
1. Judgment is the new PM skill - The AI is a copilot, not autopilot. In the demo the design missed the internal component library on the first pass and broke on narrow monitors, and both fixes came from a human who knew to look. Value shifts from operational work to knowing which reference to give and what to check.
1. Prototype on the scaffolding your customers already see - Instead of a blank canvas, the PRD gets dropped into a preloaded Fresh Service starter kit built on the internal design system. The prototype comes out already sitting inside the screen half a million users log into. New builds skip this step because they have no precedent to protect.
1. MCP collapses a day of ticket work into a single prompt - One prompt pulled 12 Windows 11 tickets from the last 60 days, clustered them into two patch rollouts, produced a root cause analysis, and recommended actions nobody asked for. A second prompt drafted knowledge base backed replies and logged them to every ticket. Tickets that took one to two hours each were closed in five minutes.
1. Hiring now means show me what you built - Curiosity is the screen, because almost nobody has done this work before. Interviews ask candidates to open cursor and walk through what they made. You can teach skills, you cannot teach passion, so the git repository is the signal. 👨‍💻 Where to find Srini: LinkedIn: https://www.linkedin.com/in/srinivasan28/ 👨‍💻 Where to find Aakash: Twitter: https://x.com/aakashgupta LinkedIn: https://www.linkedin.com/in/aagupta/ Newsletter: https://www.news.aakashg.com/ #aiproductmanagement #productbuilder 🧠 About Product Growth: The world's largest podcast focused solely on product + growth, with over 200K+ listeners. 🔔 Subscribe and turn on notifications.

SPEAKERS

Aakash Gupta
host
Host of Product Growth with Aakash Gupta.
Srini Raghavan
guest
Chief Product Officer at Freshworks.

EPISODE SUMMARY

In this episode of Aakash Gupta, featuring Aakash Gupta and Srini Raghavan, How Freshworks' CPO Actually Builds Products With AI (Live Demo) explores freshworks’ CPO demos governed AI workflows from PRD to agents Freshworks’ CPO argues PM, design, and engineering roles will converge into a “product builder” because AI collapses traditional handoffs and enables one person to research, spec, prototype, and ship.

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