▲Takeaway20:30
Build a Portfolio to Stand Out as an AI PM Applicant
There's no college degree in AI product management, so Aman says you stand out by showing interest and building your own skill stack. A portfolio of products you've tried to build, even rough prototypes, answers the hiring manager's core questions before the interview: can this person do the job, are they excited, and do I like them.
- There's no degree in product management, let alone AI product management
- A portfolio of built products (even prototypes) shortcuts the hiring process
- Hiring answers three things: can they do the job, are they excited, do I like them
- Building things demonstrates how you think and what your interests are
“the way that you stand out is through showing interest in the space and and building your own skill set and skilled stack around what…”
“you can actually go and have a you know almost like a portfolio of products that you've tried to build and maybe they're just prototypes…”
#career#hiring#portfolio#ai-pm
▲Takeaway33:00
Describe the Problem, Not 'An AI Agent'
The AI agent hype is repeating the chatbot mistake. Aman warns that pitching 'we're building an AI agent' describes a solution, not a problem. Often it's better to let foundation model companies build the agentic layer, and make your job to weave that capability so seamlessly into your product that it doesn't even feel like AI.
- Saying 'we're building an AI agent' describes a solution, not a problem
- Ask whether it makes sense to build an agent or let foundation models build that layer
- The PM's edge is applying the technology, not inventing the cutting-edge technique
- Best AI integrations feel so seamless they don't feel like AI
“you're not really describing the problem you're describing the solution an AI agent to do something”
“make that experience so amazingly seamless in your existing product that it doesn't even feel like AI in the first place”
#ai-agents#product-strategy#takeaway#hype
▲Takeaway36:30
Every AI PM Needs a Metric: Count Your Shots
Aman notes that every PM is tasked with moving a business metric, but there isn't an obvious one for building AI prototypes since they don't immediately move revenue. His answer is to measure how many shots you're taking in the first place, tied to getting the whole organization hands-on through hackathons.
- AI prototyping doesn't cleanly map to a revenue or business metric
- The metric to track is how many shots (attempts) you're taking
- Hackathons get the whole org hands-on and remove the fear that AI is unapproachable
- Come to hackathons with problems to solve, not AI solutions to force-fit
“every PM within a business is tasked with moving some business metric but there actually isn't one for building prototypes with AI”
“how many shots are you taking in the first place”
#metrics#hackathons#ai-pm#takeaway
▲Takeaway43:00
Walk and Chew Gum: Deliver Value While Making Space to Fail
Borrowing a line from Kevin Yin, Aman says the AI PM job isn't to ship AI products, it's to solve customer problems. You're constantly pushed to move a business metric, but you must also carve out space to prototype, run hackathons, and tear down great AI products. None of those move a KPI directly, yet they're how you stay ahead.
- The job is to solve customer problems, not to ship AI for its own sake
- You must deliver customer value while creating space to iterate and fail
- Arize does weekly livestreamed teardowns of cutting-edge AI products
- Accept that the tech changes fast and some experiments will fail
“your job is is not to go and ship AI products it's to go solve customers problems”
“you have to continuously deliver a customer value while also creating space to iterate and fail”
#takeaway#ai-pm#prioritization#experimentation
▲Takeaway1:02:00
Amplify Signal Through the Noise With AI
A PM can't sit in a hundred customer meetings a week, so Aman scales himself with AI. He pulls call transcripts from Gong and feeds them into long-context LLMs to extract the most common problems and pain points, effectively being in many places at once. He treats this as a superpower for finding signal through the noise.
- Uses Gong to capture what prospects and engineers are actually saying
- Feeds transcripts into long-context LLMs to surface the most common problems
- Can turn the output into a NotebookLM episode to consume it
- Scaling yourself with AI lets you 'be in so many places at once'
“we fed them into some of these large language models that have super long context Windows now and what you can do is actually pull…”
#takeaway#customer-research#ai-tools#gong
▲Takeaway1:03:30
The Best Career Advice: Just Have Fun
Aman asked a serial-entrepreneur board member for advice and was surprised the answer was simply 'have fun.' He argues that staying curious, building for customers you care about, and having fun keeps you learning and iterating faster. Product feels heavy and serious, but reframing toward fun makes you go further.
- A board member's core advice for an early-stage PM was just 'have fun'
- Curiosity plus fun keeps you learning and iterating faster
- Lenny keeps a 'have fun' Post-it in front of him while recording
- Even scary, high-stakes work rarely is the end of the world, so reframe toward fun
“I was so surprised by the feedback he had which was just have fun”
“if you're constantly learning and having fun you're going to iterate so much faster too”
#takeaway#career#mindset#fun