The GrowthStack

The question every founder is sitting with right now is some version of: what happens when Anthropic or OpenAI decides to do what we do? @apierriPMM 's answer was a fascinating one on our latest episode. Specialization is the only asymmetric lever a small company has. Not better technology. Not faster iteration. The kind of specialization that makes a vertical so narrow and so deeply served that it becomes genuinely uneconomical for a large model company to follow you into it. Lovable had a defensible position: build apps. It was specific, it was understood, and it was the thing that distinguished Lovable from general-purpose foundation models. Then the company announced it was adding AI agents and chat, moving toward direct competition with Anthropic and OpenAI on their own terrain. His read was immediate: "You guys had a great run. It's over." His logic is that a startup competing horizontally against a foundation model company is competing on the dimension where the foundation model company has the most resources, the most data, and the clearest scale advantage. A startup competing in a vertical narrow enough that the foundation model company would need a dedicated team to serve it properly is competing where the big company cannot easily follow. We covered so many more brilliant insights on Zapier, DocuSign, Apple, the idea of pricing, the viability of category creation, and more.

Episode 41: Focus is The Moat to Survive The AI Apocalyse Anthony Pierri (@apierriPMM) is one of the foremost voices in product marketing, having worked with 400 SaaS companies focusing on the one document that reveals whether a team has actually agreed on its strategy, the homepage. He also argues that most SaaS is priced too high because founders overpromised to investors and then increased spending, forcing customers to subsidize the whole arrangement. The RB2B case makes this concrete: Adam Robinson's bootstrapped, single-feature product is doing $7M ARR while its VC-backed competitors, who buried the same feature inside enterprise platforms to satisfy investor expectations, are doing less. In our conversation, we get into: ✅How Focus is the only defensible position against an LLM ✅The Lovable mistake and why competing horizontally with Anthropic or OpenAI is a death sentence ✅Why RB2B is doing $7M ARR while VC-backed competitors with bigger platforms generate less ✅Why DocuSign's rebrand became a punchline inside brand positioning circles ✅How investor expectations push founders into pricing that customers end up rejecting Listen Now 👉 youtube.com/watch?v=89JTvI…

Episode 41: Focus is The Moat to Survive The AI Apocalyse Anthony Pierri (@apierriPMM) is one of the foremost voices in product marketing, having worked with 400 SaaS companies focusing on the one document that reveals whether a team has actually agreed on its strategy, the homepage. He also argues that most SaaS is priced too high because founders overpromised to investors and then increased spending, forcing customers to subsidize the whole arrangement. The RB2B case makes this concrete: Adam Robinson's bootstrapped, single-feature product is doing $7M ARR while its VC-backed competitors, who buried the same feature inside enterprise platforms to satisfy investor expectations, are doing less. In our conversation, we get into: ✅How Focus is the only defensible position against an LLM ✅The Lovable mistake and why competing horizontally with Anthropic or OpenAI is a death sentence ✅Why RB2B is doing $7M ARR while VC-backed competitors with bigger platforms generate less ✅Why DocuSign's rebrand became a punchline inside brand positioning circles ✅How investor expectations push founders into pricing that customers end up rejecting Listen Now 👉 youtube.com/watch?v=89JTvI…

"If you use AI to write emotional copy, you are effectively telling your prospects to go away." Talia Wolf (@TaliaGw) is the author of Emotional Targeting, a conversion optimization framework used for over a decade to help B2B brands understand why their customers actually buy. She's worked with everyone from project management tools (like @mondaydotcom) to enterprise SaaS, digging into the psychology that feature comparisons and pricing grids will never capture. In our conversation, we get into: ✅Why AI-generated copy has made every B2B website functionally identical ✅The logo swap test is one that most founders fail ✅How the buying journey has moved almost entirely off your website into Reddit, Slack, and Discord ✅Why your website is now a confirmation tool, not a persuasion tool ✅The difference between social image and self-image in B2B purchasing ✅Why scraping one Reddit thread and asking ChatGPT to analyze it gives you useless insights ✅What zero-click marketing means for how you measure conversions right now Watch now👇

Episode 38: Why Being an "AI Marketer" is a Massive Red Flag I sat down with @ollyjjones, a marketing veteran from @myosin_xyz and an advocate for marketers transitioning from generic AI tool users to actual system builders. He broke down exactly why the standard AI marketing approach, which focuses purely on efficiency, keeps output generic and at the 70th percentile, and what growth teams must do to be the best by linking AI implementation to a sound marketing strategy. We dive deep into the mechanics of the "Forward Deployed Marketer" and why traditional marketing agencies must evolve beyond billable hours, focusing instead on robust data hygiene and upskilling teams to survive the next two years of rapid industry shifts. Chapters 00:00 - Forward Deployed Marketer concept 05:25 - Efficiency vs. Quality 12:00 - Building Trust 15:26 - 30-Day Learning Roadmap 20:32 - Overcoming AI Resistance 27:11 - Evolution of Agency Economics 36:10 - Implementing AI in Data 44:48 - Overcoming the Pain Points 51:12 - The Final Playbook for Marketers Full Episode 👇

Episode 37: Why Everyone's Wrong About AI Killing Product Roles I sat down with @ttorres (Author of Continuous Discovery Habits), the godmother of product discovery, who has helped 100's of teams across the globe build products to scale. She broke down how the playbooks she's developed for continuous discovery are evolving, but not fundamentally changing, even in the era of AI. We also dove into exactly why the standard tech-Twitter prediction of "zero-human" software is "baloney" and what product teams must do to measure non-deterministic AI outputs. We analysed the mechanics of cognitive bias in user feedback and why, when you're dealing with AI answer engines, the human in the loop is more critical than ever to ensure actual value creation. Chapters 00:00 - The AI Reality Check 00:36 - The invisible trap in customer interviews 04:04 - AI in sales and customer empathy 08:45 - The "Agentic Buyer" delusion 13:44 - The rise of the Product Builder 16:30 - Solving context rot with AI retrospectives 22:20 - AI evals and non-deterministic product paths 28:42 - Navigating shiny object syndrome in startups Full Episode 👇