Akhil @ProdmohAI

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AI search is creating a new visibility layer. Google AI Overviews: 2B+ monthly users Adobe: AI referral traffic up 10x Bain: 30–45% use GenAI for product research arXiv: ~30% of AI-cited domains don’t appear on page 1 SEO still matters. It is being understood or cited.

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AI product management is not about becoming a prompt expert. That’s the shallow version. The real shift: AI can summarize feedback, cluster pain points, and draft PRDs faster. AI speeds up synthesis. PMs still own judgment. prodmoh.com/blog/ai-produc…

Branding in the ChatGPT era isn’t just about being memorable. It’s about being retrievable. When buyers ask AI tools for recommendations, your brand either shows up or disappears from the buying journey. The new brand metric: Are you cited when your customer asks the right prompt

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Recent Series A/B/C rounds show the real AI shift: Not more tools. Better decisions. Fifth Dimension, Viktor, Arkeus, Exaforce, Galaxea AI, SkildAI — different markets, same pattern: data → signal → decision → execution. Teams ship features. ProdMoh drives product decisions

New funnel: Question → AI Answer → Decision No SERPs. No scrolling. If you’re not inside the answer, you lose. Aparok shows: → Where your brand appears in AI → What prompts drive visibility → Which platforms send traffic Most brands aren’t even measuring this yet

AI made building software cheap. It did not make clarity cheap. If everyone can build, customers won’t adapt to your product. Your product must adapt to them. The winners won’t build more. They’ll decide what stays opinionated.

AI made output cheap. Decisions are still expensive. Roadmaps don’t fail from lack of PRDs—they fail from lack of enforceability: owners, dates, evidence. Strategy in AI isn’t “which model?” It’s Market → Wedge → Moat + trust maps + unit economics. amazon.com/dp/B0DCLBSYRT

Your analytics dashboard isn’t neutral. It nudges decisions. 20% adoption can mean: “this failed” or “this is promising” Same data. Different framing. Great teams don’t just track metrics. They design data to drive better decisions.

SEO tracks keywords. GEO tracks questions AI answers. Most brands don’t know: If ChatGPT mentions them Which prompts drive traffic Why competitors get cited Aparok fixes that. Welcome to the era of optimizing for answers, not rankings.

Have you checked this yet? Open ChatGPT and type: 👉 “best tools for [your category]” 👉 “alternatives to [your product]” Now ask: 👉 “Am I being recommended?” Most founders I tested: ❌ Not showing up ❌ Competitors showing instead Comment “check” or DM me your website.

Most teams are still optimizing for Google. But their buyers have already moved. They’re asking tools like ChatGPT: • “best tools for X” • “top agencies for Y” • “how to solve Z” And here’s the uncomfortable truth: 👉 AI doesn’t rank pages 👉 It selects answers

Most startups don’t fail because they can’t build. They fail because they build the wrong things. Your roadmap is probably: a backlog in disguise driven by opinions disconnected from outcomes Reality check: ~40% of R&D spend is wasted on features that don’t matter That’s runway. Gone. We don’t have an execution problem. We have a decision problem. New category: 👉 AI Product Decision System 👉 AI Chief of Staff for Product Teams ship features. ProdMoh drives product decisions. What it actually does: → Turns customer feedback into product signal → Generates decision-ready PRDs → Maps everything into a Product Canvas → Tells you what to ship / block / defer Instead of: “Let’s build this feature” You get: “Here’s the problem, evidence, impact, and why it matters” If your roadmap doesn’t answer: Why this? Why now? What outcome? You’re guessing. Series A/B founders: Your biggest risk isn’t speed. It’s building fast in the wrong direction. 👉 Plan. Decide. Ship with Confidence. That’s ProdMoh. If you're tired of roadmap chaos, Reply “DECIDE” I’ll show you how to turn product into a growth engine

🔹 1 Most startups don’t run out of money. They run out of good product decisions. AI made building cheap. It didn’t make bad bets cheap. 🔹 2 Funding doesn’t fix your roadmap. It hides its problems. More engineers = more output Not better decisions 🔹 3 AI has changed one thing: You can now build the wrong product faster than ever. That’s not leverage. That’s accelerated waste. 🔹 4 Every feature is a capital allocation decision. Time Attention Opportunity cost If your roadmap doesn’t reflect that, you’re not doing product. You’re doing activity. 🔹 5 After funding, most teams make this mistake: “We have more capacity → let’s do more” Instead of: “We have more capital → let’s choose better” 🔹 6 The best product teams treat their roadmap like a portfolio: High conviction bets Clear upside Defined kill criteria Everything else is noise. 🔹 7 Most teams don’t struggle to start things. They struggle to stop. That’s where decision quality actually shows up. 🔹 8 AI tools can help you: build faster prototype faster ship faster They cannot help you decide: What’s worth building What’s worth killing That’s still the game. 🔹 9 You don’t need more features. You need fewer, sharper bets. Focus is not a constraint. It’s a strategy. 🔹 10 (Thread starter) Unpopular truth: Well-funded startups often burn faster than constrained ones. Not because they hire more. Because they build more of the wrong things.

Most companies are still tracking Google rankings. Smart ones are asking a different question: 👉 “Which prompts mention my brand in ChatGPT, Gemini, or Perplexity?” Search is no longer just keywords. It’s conversations. If you don’t know: where you’re cited why you’re cited how often you’re cited You’re invisible in AI. Aparok shows you the exact prompts driving AI visibility + traffic. This is SEO’s next layer: GEO (Generative Engine Optimization)

Most product roadmaps aren’t wrong. They’re just… not decision-ready. And that’s where the real burn happens. → Features shipped ≠ outcomes delivered → Priorities listed ≠ priorities aligned → Roadmaps filled ≠ capital allocated In fact, up to 40% of R&D spend goes to features that never move KPIs As a Head of Product, ask yourself: Do I know how much of my roadmap is driving retention vs acquisition vs monetization? Can I explain why this feature exists, beyond stakeholder pressure? If I pause today, can I clearly say what to ship, block, or defer? If not — you don’t have a roadmap. You have a backlog with opinions. This is where Product Canvas changes the game Instead of managing features, you start managing product decisions at a portfolio level. Product Canvas gives you: → A bird’s-eye view of your roadmap across growth, retention, monetization → Conviction scoring — what’s backed by evidence vs guesswork → Portfolio imbalance detection (e.g. over-investing in acquisition, starving retention) → Execution clarity — owners, timelines, readiness → A live Decision Brief: What to ship What to block What to defer Because here’s the uncomfortable truth: Your biggest risk is not shipping slow. It’s shipping the wrong things with high confidence. Teams ship features. ProdMoh drives product decisions. If your roadmap isn’t helping you decide — it’s quietly draining your runway. Tagline: Plan. Decide. Ship with Confidence. If you're a Head of Product scaling from Series A → C, this is the shift you need to make: From roadmap management → roadmap capital allocation