What AI PMs REALLY Need to KNOW in 2026 (Agents, Discovery, EVERYTHING)

Todd Olson spent 28 years in product management and built Pendo to $2.5B. He reveals why AI PM jobs doubled to 20% of all postings (and pay 30-40% more), the exact 5-layer technical pyramid to upskill from core PM to AI PM, and how to ship AI features at scale with proper evals, cost optimization, and the right product strategy. Full Writeup: https://www.news.aakashg.com/p/todd-olson-podcast Transcript: https://www.aakashg.com/the-complete-ai-pm-roadmap-how-to-upskill-from-core-pm-to-ai-pm-with-pendo-ceo-todd-olson/ ---- Timestamps: 0:00 - Intro 1:29 - Episode Begins 3:24 - Why AI PMs Get Paid 30-40% More 6:07 - How to Upskill into AI PM 11:50 - Ad 12:54 - The 5-Layer Technical Pyramid 16:30 - AI/ML Fundamentals 23:00 - Data Pipelines & RAG 33:02 - Trace Analysis & PM-Eng Tension 40:44 - Cost & Performance Optimization 48:56 - Evals Are Your Domain 56:03 - AI Product Roadmap 1:04:16 - Live Demo: Pendo's AI Features 1:13:07 - Ad 1:14:12 - Stakeholder & Board Management 1:22:03 - Outro ---- 🏆 Thanks to our sponsor: Reforge: Get 1 month free of Reforge Build with code BUILD - https://reforge.com/aakash ---- Key Takeaways: 1. AI PM market exploded - Last year 10% of PM jobs were AI PM jobs. This year it's 20%. They pay 30-40% more because of scarcity and skill level. But Todd warns: "You better damn well be good and know what you're talking about if you're gonna call yourself an AI PM because we are going to interrogate the hell out of it." 2. Real requirement is production at scale - Not "I built prototype at 1-person startup." Hiring managers want 20,000 paying B2B customers experiencing your AI feature successfully. To get there: upskill internally at current company by shipping AI features on your roadmap. 3. The 5-layer technical pyramid - Foundation: AI/ML fundamentals, data pipelines, prompt engineering. Middle: Observability (trace analysis), cost optimization, evals. Top: Product strategy, stakeholder management, leadership. You need to climb all 5 layers. Most PMs stop at layer 1. 4. RAG is table stakes - "RAG is the de facto way to build." You ingest data, create embeddings, feed into vector database, look up relevant context, pass to LLM. Todd: "If you put too much in context window, just like a human, you get confused. You want to give the right context." 5. PM-engineering tension is real - At startups, PMs do trace analysis. At large companies, engineering managers push back: "This is my world. I don't want some PM shadowing me." Similar to Data Dog—most PMs don't have login. Know the line. Be fluent but respect boundaries. 6. But evals are YOUR domain - Unlike trace analysis, evals are where PMs are the expert. "The PM is probably the best-suited human being to author and manage eval sets." You understand user and business needs. Engineers don't have that context. This is must-have competency now. 7. Cost optimization will matter - Some AI companies have sub-15% gross margins. Traditional software is 70-80%. Todd: "It's not a business at sub-15%." Eventually you'll rearchitect systems because infrastructure is too costly. Rule: when something's faster, it's cheaper (both buying compute). 8. Solve hard problems, not shiny objects - Todd's test: "Are we gonna do much better job than ChatGPT out of box? Why would we just wrap that and slap Pendo logo on it?" His discovery agent example: hard part isn't interviewing customers—it's finding which to interview, prioritizing, scheduling. Automate that workflow. 9. Kill bad features ruthlessly - Todd shipped features couple years ago that weren't great and turned them off. "Too often we hold on to something. Turn them off. Be unafraid. The more stuff in your product, the worse the experience is by default." 10. Control the narrative with boards - Don't show up with no story and get crushed with random requests. Todd: "Show them how you actually run your business. I want to see what you're looking at, not something just made for me." Think deeply about how each bet drives shareholder value. ---- 👨‍💻 Where to find Todd Olson: LinkedIn: https://www.linkedin.com/in/toddaolson/ Twitter/X: https://x.com/tolson Company: https://www.pendo.io 👨‍💻 Where to find Aakash: Twitter: https://www.x.com/aakashg0 LinkedIn: https://www.linkedin.com/in/aagupta/ Newsletter: https://www.news.aakashg.com #aipm #productmanagement #pendo ---- 🧠 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 GuptahostTodd Olsonguest

Dec 3, 20251h 21mWatch on YouTube ↗

EPISODE INFO

Released: December 3, 2025
Duration: 1h 21m
Channel: Aakash Gupta
Watch on YouTube: ▶ Open ↗

EPISODE DESCRIPTION

Todd Olson spent 28 years in product management and built Pendo to $2.5B. He reveals why AI PM jobs doubled to 20% of all postings (and pay 30-40% more), the exact 5-layer technical pyramid to upskill from core PM to AI PM, and how to ship AI features at scale with proper evals, cost optimization, and the right product strategy. Full Writeup: https://www.news.aakashg.com/p/todd-olson-podcast Transcript: https://www.aakashg.com/the-complete-ai-pm-roadmap-how-to-upskill-from-core-pm-to-ai-pm-with-pendo-ceo-todd-olson/ ---- Timestamps: 0:00 - Intro 1:29 - Episode Begins 3:24 - Why AI PMs Get Paid 30-40% More 6:07 - How to Upskill into AI PM 11:50 - Ad 12:54 - The 5-Layer Technical Pyramid 16:30 - AI/ML Fundamentals 23:00 - Data Pipelines & RAG 33:02 - Trace Analysis & PM-Eng Tension 40:44 - Cost & Performance Optimization 48:56 - Evals Are Your Domain 56:03 - AI Product Roadmap 1:04:16 - Live Demo: Pendo's AI Features 1:13:07 - Ad 1:14:12 - Stakeholder & Board Management 1:22:03 - Outro ---- 🏆 Thanks to our sponsor: Reforge: Get 1 month free of Reforge Build with code BUILD - https://reforge.com/aakash ---- Key Takeaways:
1. AI PM market exploded - Last year 10% of PM jobs were AI PM jobs. This year it's 20%. They pay 30-40% more because of scarcity and skill level. But Todd warns: "You better damn well be good and know what you're talking about if you're gonna call yourself an AI PM because we are going to interrogate the hell out of it."
1. Real requirement is production at scale - Not "I built prototype at 1-person startup." Hiring managers want 20,000 paying B2B customers experiencing your AI feature successfully. To get there: upskill internally at current company by shipping AI features on your roadmap.
1. The 5-layer technical pyramid - Foundation: AI/ML fundamentals, data pipelines, prompt engineering. Middle: Observability (trace analysis), cost optimization, evals. Top: Product strategy, stakeholder management, leadership. You need to climb all 5 layers. Most PMs stop at layer 1.
1. RAG is table stakes - "RAG is the de facto way to build." You ingest data, create embeddings, feed into vector database, look up relevant context, pass to LLM. Todd: "If you put too much in context window, just like a human, you get confused. You want to give the right context."
1. PM-engineering tension is real - At startups, PMs do trace analysis. At large companies, engineering managers push back: "This is my world. I don't want some PM shadowing me." Similar to Data Dog—most PMs don't have login. Know the line. Be fluent but respect boundaries.
1. But evals are YOUR domain - Unlike trace analysis, evals are where PMs are the expert. "The PM is probably the best-suited human being to author and manage eval sets." You understand user and business needs. Engineers don't have that context. This is must-have competency now.
1. Cost optimization will matter - Some AI companies have sub-15% gross margins. Traditional software is 70-80%. Todd: "It's not a business at sub-15%." Eventually you'll rearchitect systems because infrastructure is too costly. Rule: when something's faster, it's cheaper (both buying compute).
1. Solve hard problems, not shiny objects - Todd's test: "Are we gonna do much better job than ChatGPT out of box? Why would we just wrap that and slap Pendo logo on it?" His discovery agent example: hard part isn't interviewing customers—it's finding which to interview, prioritizing, scheduling. Automate that workflow.
1. Kill bad features ruthlessly - Todd shipped features couple years ago that weren't great and turned them off. "Too often we hold on to something. Turn them off. Be unafraid. The more stuff in your product, the worse the experience is by default."
1. Control the narrative with boards - Don't show up with no story and get crushed with random requests. Todd: "Show them how you actually run your business. I want to see what you're looking at, not something just made for me." Think deeply about how each bet drives shareholder value. ---- 👨‍💻 Where to find Todd Olson: LinkedIn: https://www.linkedin.com/in/toddaolson/ Twitter/X: https://x.com/tolson Company: https://www.pendo.io 👨‍💻 Where to find Aakash: Twitter: https://www.x.com/aakashg0 LinkedIn: https://www.linkedin.com/in/aagupta/ Newsletter: https://www.news.aakashg.com #aipm #productmanagement #pendo ---- 🧠 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.

SPEAKERS

Aakash Gupta
host
Host of the Aakash Gupta channel who interviews product leaders about AI product management.
Todd Olson
guest
Product leader at Pendo discussing AI PM fundamentals, agents, evaluation, and workflow-focused product strategy.

EPISODE SUMMARY

In this episode of Aakash Gupta, featuring Aakash Gupta and Todd Olson, What AI PMs REALLY Need to KNOW in 2026 (Agents, Discovery, EVERYTHING) explores 2026 AI PM playbook: technical fluency, evals, roadmaps, governance, execution AI PM demand is rising fast, but “AI PM” labeling is a marketing and scarcity game that will be heavily scrutinized in hiring due to rampant AI-washing.

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