Education / Research & Learnings
Deep doctrine on AI-native growth.
These frameworks shape how I evaluate opportunities, build products, and advise teams in the AI era. Each represents hundreds of hours of research, synthesis, and field application. Select a domain to explore detailed frameworks, operating principles, and reusable models.
Frameworks
The AI Growth Imperative
Growth is no longer an advantage. It is a survival requirement in the AI era. AI accelerates building, destabilizes channels, compresses tactic lifecycles, and raises customer expectations. Growth first, then defensibility.
StrategyAI Growth Defensibility
Five misconceptions that kill AI companies. Speed is not a moat. Distribution is not a moat. Data alone is not a moat. Defensibility is a layered, time-sequenced process, not a destination.
AcquisitionAcquisition Strategy in AI
AI compresses product development but distribution, trust, adoption, and channel dynamics still obey growth fundamentals. Growth loops still rule. Bottlenecks move. They do not disappear.
MonetizationMonetization & Pricing in AI
AI breaks the SaaS pricing playbook. Usage-based pricing, outcome-based models, and value capture require rethinking the entire monetization stack for AI-era products.
RetentionRetention & Engagement in AI
Switching costs have collapsed. User loyalty is near zero. Most users arrive as AI tourists. Retention must be earned through disciplined activation, engagement, and resurrection design.
ProductAI Prototyping
Working software is now a decision artifact. The advantage is not building more demos. It is reducing learning latency from hypothesis to customer signal faster than competitors.
ProductAI-Native Product Teams
How AI-native teams think, work, and build differently. New team structures, decision velocity, and the shift from building features to orchestrating AI capabilities.
StrategyThe Expectation Reset
Seven ways AI is redefining customer expectations. Products are judged by AI-era standards: instant, contextual, proactive. Even if they were not built for it.
ProductPM in the AI Era
Same role, new possibilities. How AI changes product management: from backlog grooming to capability orchestration, from roadmap theater to learning velocity.
AcquisitionGrowth Loops & Acquisition
Funnels stay linear. Loops compound. How to design acquisition systems where each user brings the next, amplified by AI intelligence and relevance.
StrategyThe Four Fits Framework
A growth framework for the AI era. Product-market fit, product-channel fit, channel-model fit, and model-market fit : more fragile, faster-collapsing, and more critical than ever.
StrategyAI Evaluation & Decision-Making
An evaluation-first approach to AI opportunities. Structured frameworks for assessing AI vulnerability, opportunity sizing, and build-vs-buy decisions in the AI era.
AcquisitionLocal Business Lead Scoring Framework
A five-factor scoring system for qualifying local business leads using publicly available data. Weights website presence, review quality, image count, social media footprint, and Google Business Profile status to produce a composite score and a personalized outreach draft.
Start here
How to price AI consulting work: the freedom number method
Most AI consultants price by the hour and lose money on every engagement. The freedom number method starts from what you actually need to make and works backward, anchoring price to the value delivered instead of the time spent.
The one question that reveals where AI actually moves revenue
Most businesses automate what is easy to automate. The Income Lens framework asks a harder question that reveals where automation actually changes the P&L, not just saves hours.
The EBITDA math nobody runs before buying AI
How firm owners should price AI in profit terms. Revenue created, margin kept, the two-number test, and what to measure in the first 90 days.
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