Thinking out loud.
PM strategy, UI decisions, and what we're learning building Rayform.
AI-Driven UI: What's Real and What's Hype in 2026
Every product now claims AI-powered personalization. Most of it is segment-based rendering with a language model bolted on. Here's how to tell the difference — and what the real infrastructure for adaptive UI actually looks like.
Read post →The Problem With Feature Flags as Your Personalization Strategy
Feature flags let you gate a pre-built variant to a named cohort. That's not personalization — it's conditional rendering. Here's why the difference matters, and what runtime adaptation actually requires.
Read post →The Death of the Universal Onboarding Flow
The universal onboarding flow — one linear path for all users — has hit a ceiling that copy optimization can't break through. Here's the behavioral data that shows why, and what adaptive onboarding actually requires mechanically.
Read post →What Rage Clicks Are Actually Telling You (And What To Do About It)
Rage clicks aren't random frustration noise. They encode three distinct failure types with different root causes and different fix owners. Here's the taxonomy — and how to close the loop without a three-week sprint cycle.
Read post →Event-Based Feature Flags Are the Closest Thing to a Self-Adapting Product — Here's Why They Still Fall Short
PostHog's event-based flag targeting fires on live behavioral events — a real step forward. Here's why flag trees still aren't a behavioral intelligence layer.
Read post →Conversational Analytics Is Here — But Insights Sitting in a Chat Window Still Do Not Fix the Product
Conversational analytics finds answers fast, but outcomes still lag unless behavioral signals drive runtime adaptation.
Read post →How to Read a Funnel Drop-off Before It Becomes a Churn Problem
Funnel drop-off shows you where users leave. It doesn't tell you why, or what to do next. Here's how to distinguish the three types of drop-off and act on each before the cohort churns.
Read post →A/B Testing Is Too Slow — Here Is What Fast Product Teams Do Instead
A/B testing assumes traffic volumes and stable surfaces most SaaS teams don't have. Here's the statistical and organizational math that explains why — and what a concrete alternative looks like.
Read post →AI Compresses Analytics Execution — But Judgment Is Now Your Only Moat
AI made SQL and dashboards 3-4x faster. That's table-stakes now. The real differentiator is knowing which behavioral signals matter and why.
Read post →Behavioral Telemetry 101: What Amplitude, Mixpanel, and PostHog Are Actually Capturing
Most teams treat their analytics stack as a reporting layer. It's actually a behavioral signal pipeline. Here's what these tools are capturing, what they're missing, and why the difference matters for runtime UI adaptation.
Read post →From Session Replay to Action: Closing the Gap Between Insight and Fix
Teams watch 50 session recordings and still ship the same broken flow. The insight-to-action gap is a workflow problem — here's how to close it.
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