24 deep guides on AI-powered product growth, retention, and monetization
The playbook that got you to 100K users won't get you to 10M. AI isn't just another channel—it's fundamentally reshaping how products grow, retain, and monetize. Here's what actually works in 2026.
Understanding the architecture that revolutionized NLP, from attention mechanisms to positional encodings.
Traditional segmentation is dead. Learn how to build individual-level personalization systems with embeddings, real-time inference, and behavioral prediction models that adapt to every user.
Choosing the right vector database for your AI application matters more than you think. I've run production workloads on all four—here's what actually performs, scales, and costs in 2026.
Stop reacting to churn. Learn how to predict it 7-30 days early with ML models, identify at-risk users, and build automated intervention systems that reduce churn by 15-25%.
Forget the 'act as an expert' templates. After shipping dozens of LLM features in production, here are the prompt engineering techniques that actually improve outputs, reduce costs, and scale reliably.
Static referral programs have a 2-5% conversion rate. AI-powered viral loops see 15-25% by personalizing incentives, timing, and messaging for each user. Here's how to build one.
Spending $10K+/month on OpenAI or Anthropic? Here are the exact tactics that reduced our LLM costs from $15K to $3K/month without sacrificing quality.
Traditional viral loops are predictable. LLM-powered loops adapt, generate, and scale automatically. Learn how to build growth loops that get smarter with every user.
Stop manually writing blog posts. Learn how to generate thousands of SEO-optimized pages with LLMs, rank for long-tail keywords, and drive organic traffic at scale.
Tested 12 embedding models on real production workloads. Here's what actually performs for RAG, semantic search, and clustering—with cost breakdowns and migration guides.
Stop leaving money on the table with static pricing. Learn how to build ML-powered pricing systems that optimize for willingness-to-pay and increase revenue by 20-40%.
Retrieval-Augmented Generation is powerful, but these common pitfalls can tank your accuracy. Here's what to watch for.
Build recommendation engines that understand semantic similarity, work with cold-start users, and deliver personalized experiences from day one using embeddings.
Generic experiences convert at 2-3%. Personalized experiences convert at 8-15%. Learn how to build recommendation systems and personalization engines that scale to millions of users.
Stop running one test at a time. Learn how to use multi-armed bandits, Bayesian optimization, and LLMs to run 100+ experiments simultaneously and find winners faster.
Ditch static tutorials. Build AI-powered onboarding that adapts to each user, answers questions in real-time, and guides them to their first win faster.
Sales-led growth is dead for most SaaS. Product-led growth powered by AI lets users self-serve, activate faster, and expand usage automatically. Here's the complete playbook.
Manual user research doesn't scale. AI can analyze thousands of support tickets, reviews, and sessions to find patterns, extract insights, and prioritize product decisions. Here's how.
Stop wasting time on low-intent leads. Build ML models that score leads by conversion probability, predict deal size, and route high-value prospects automatically.
Static conversion funnels convert at 2-3%. AI-optimized funnels that personalize every step see 10-15% conversion rates. Learn how to build adaptive funnels that improve themselves.
An honest look at when each approach makes sense, with real cost comparisons and performance data.
Context window size is more than just a number. Let's explore what it actually means for your applications.
A comprehensive comparison of embedding models for semantic search, RAG, and similarity tasks.