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Aakash GuptaAakash Gupta

How You Need to Think About Product Strategy in the Age of AI

AI has made shipping features cheap, which makes choosing the wrong ones more expensive than ever. Tim Herbig, product strategy coach and author of Real Progress, walks through how to build a product strategy that actually helps you say no. Full write-up: https://www.news.aakashg.com/p/how-the-best-pms-think-about-product-strategy Transcript: https://www.aakashg.com/product-strategy-in-the-age-of-ai-with-tim-herbig/ Timestamps 03:06 - Cheap features make wrong choices expensive 05:33 - The one test every strategy has to pass 07:19 - Ads 09:02 - The core questions every strategy answers 12:39 - Why AI is not a value proposition 18:41 - The Roger Martin test and the stupidity flip 25:11 - Ads 30:59 - Case study - Fair Mile, a used car marketplace 35:43 - Audience trees 42:16 - Differentiation with the 7 Powers 52:48 - How to know if your strategy worked 58:30 - Building the strategy and metrics loop 1:04:33 - What you inherit vs. what you create 🏆 Thanks to our sponsors 1. Fingerprint: Identify good and bad visitors with industry-leading accuracy - https://tinyurl.com/2s3p65p7 2. Ariso: Ship AI agents and features faster, with fewer regressions - https://ariso.ai/aakash 3. Customer.io: Send smarter messages using your product data - http://customer.io/productgrowth 4. Amplitude: The market leader in product analytics - https://tinyurl.com/b7nret7v 5. Product Faculty: Get $150 off their #1 AI PM Certification via code AAKASH150 - https://www.productfaculty.com/?code=AAKASH150 Key Takeaways 1. Cheap features make wrong bets expensive - AI made shipping fast, so picking the wrong feature now costs more, not less. You still have to get people to use everything you ship. The real question is whether any of that output moved customers and the business. 2. A strategy is only real if it helps you say no - Deck, one-pager, or framework, the test is the same. If it doesn't help teams say no to opportunities, it isn't a strategy. A healthy one has most of your team's energy going to work connected to it. 3. Every strategy answers the same core questions - A narrative for why act now, a playing field for who you serve and who else competes, and winning moves for how you deliver value and differentiate. Canvases and templates are just windows into that messy work. Start with the questions, not the template. 4. AI is a resource, not a value proposition - Everyone has access to the same frontier models, so you can't compete on the technology alone. Use AI to amplify the reason customers already choose you. Brand and data are the moats that remain. 5. Run the stupidity flip - Borrowed from Roger Martin. Flip a strategic choice and check whether the opposite is obviously stupid. If it is, you haven't made a real choice. Flip individual components like audience or value prop, not the whole statement. 6. Strategy doesn't have to cover everything - Focusing on paid users doesn't mean turning off the product for free users. The segment choice just has to fit the narrative behind it. Every component has to reinforce the others. 7. Build an audience tree - Land somewhere between too broad and comically narrow. Slice by region, buyer type, and car value until you can say no. Fair Mile lands on repeat buyers of cars worth more than 100K in Germany, and AI speeds up sizing whether that market is big enough. 8. Differentiate on what takes longest to build - Run your winning moves through Hamilton Helmer's 7 Powers. Brand and network effects hold up, while process power and AI features get copied. No one buys a car from you because your marketplace has AI search. 9. Measure behavior change, not tokens - First say in plain English what you will do differently next quarter, then how you'll know it worked. Tokens used is a value exchange for the model provider, not your customers. Ask whose behavior has to change, and by how much. 10. Tie metrics to your specific choices - Generic KPIs like revenue are too noisy and too slow to tell you if a strategy worked. Fair Mile tracks share of cars sold above 100K, margin per transaction, and recommendation score among those buyers. Then map every roadmap item back to those metrics. 👨‍💻 Where to find Tim Herbig LinkedIn: https://www.linkedin.com/in/herbigt/ Website: https://herbig.co/ 👨‍💻 Where to find Aakash Twitter: https://x.com/aakashgupta LinkedIn: https://www.linkedin.com/in/aagupta/ Newsletter: https://www.news.aakashg.com 🧠 About Product Growth The world's largest podcast focused solely on product + growth, with over 200K+ listeners. 🔔 Subscribe and turn on notifications.

Tim HerbigguestAakash Guptahost
Oct 14, 20261h 12mWatch on YouTube ↗

At a glance

WHAT IT’S REALLY ABOUT

AI makes features cheap; strategy choices and metrics matter more

  1. The conversation argues that as AI makes feature delivery dramatically cheaper, product strategy becomes more critical because wrong choices now scale faster and cost more in adoption, maintenance, and distraction.
  2. Tim Herbig defines effective strategy as a set of opinionated choices that help teams say “no” over a time horizon, rather than a deck, template, or a long list of priorities.
  3. The episode introduces a practical stress test for strategy—the Roger Martin ‘opposite is stupid’ check—plus a ‘stupidity flip’ exercise to turn vague statements into real trade-offs.
  4. Herbig emphasizes that AI alone is not a defensible value proposition because models are broadly available; enduring differentiation more often comes from brand, data, network effects, and other durable ‘powers.’
  5. Using a fictional used-car marketplace (‘Fair Mile’), the hosts show how to narrow audiences with Audience Trees, choose winning moves, and build a strategy→metrics loop with measures directly tied to strategic choices rather than generic KPIs or machine metrics.

IDEAS WORTH REMEMBERING

5 ideas

Cheap features make bad prioritization more expensive, not less.

When it becomes easy to ship “something,” the real cost shifts to adoption, maintenance, and opportunity cost—getting the wrong choices into customers’ hands is what becomes expensive. Strategy’s job is to constrain output toward what changes customer and business outcomes.

The primary test of strategy is whether it helps you say “no.”

A strategy is only useful if it creates constraints that let teams reject plausible opportunities for the next 6–18 months. If your “strategy” is compatible with almost any roadmap item, it’s not doing strategy work.

Pressure-test strategy with Roger Martin’s ‘opposite is stupid’ test (the ‘stupidity flip’).

If the opposite of your stated strategy is obviously stupid, you haven’t made a real choice (e.g., “make salespeople more efficient”). Use the “stupidity flip” on specific components—audience, value prop, channel, differentiation—until the alternatives are believable.

AI is a resource, not a value proposition or moat by itself.

Because frontier models are widely accessible, “we use AI” is rarely a differentiator; it’s an input you leverage to amplify an existing customer value exchange. Sustainable advantage tends to come from slower-to-build assets like brand, data, and network effects.

Use Audience Trees to pick a focused segment, then use AI to size and sanity-check it fast.

Audience Trees help teams move from too-broad targets (e.g., ‘all car buyers in Europe’) to focused, defendable segments without becoming ‘comically narrow.’ AI can accelerate the market research and sizing needed to validate whether a narrowed segment is viable.

WORDS WORTH SAVING

5 quotes

These days, as everyone probably know, like producing features got kind of cheap, especially for greenfield products, but even established companies can get stuff out the door much, much faster. But the problem, the downside of that is when features get cheap, not having chosen the right feature, funnily enough, gets more expensive because suddenly you're flooding your product with all this output, all this fluffy stuff, all these great vibe-coded lovable things, and everything you do to circumvent the complex engineering work or even accelerated your engineering department. But this can come as a cost because you still have to make people use the features you produced.

— Tim Herbig

Whatever you're thinking your strategy is, whatever shiny deck it is, whatever one-pager it is, whatever framework, think about does it help me say no to things? That's all that matters.

— Tim Herbig

AI by itself in your strategy is not a value proposition. Everyone has access to the same frontier models. You can't compete on that technology alone.

— Tim Herbig

Well, the question is, is the opposite of your choice, of your strategy choice, stupid on its face? If the opposite is stupid, it's-- you haven't made a real choice.

— Tim Herbig

The point is, that's no value exchange. Like tokens used is not a value exchange for your customers. It's a value exchange for Anthropic.

— Tim Herbig

Feature output vs. adoption and business impactStrategy as constraints: saying noRoger Martin ‘opposite is stupid’ test‘Stupidity flip’ exercise for real choicesAI as resource vs. value propositionAudience Trees and segmentation focusDifferentiation via Hamilton Helmer’s 7 Powers (brand, data, network effects)

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