Product Management & Execution

Product managers are evolving from process coordinators to augmented architects: AI-powered builders who own strategy and commercial outcomes.

Internal platforms that slow teams down are taxes. Those that accelerate them are multipliers. The mandate trap hides which one you're building.

Why do customers churn despite green dashboards? Three layers determine retention: friction (anger), outcomes (indifference), resonance (loyalty).

Waiting isn't friction to eliminate. It's captive attention begging for engagement. The best products turn loading screens into learning moments.

AI accelerates shipping but not learning. Teams build faster without validating if they're solving the right customer problems.

Three major outages expose the gap between multi-cloud architecture and actual resilience when CDN infrastructure fails.

AI agents boost output but multiply review work while threatening entry-level jobs. Two patterns reshaping knowledge work simultaneously.

Google's whitepaper shows why stateful AI requires engineering context with Sessions and Memory, not just better prompts.

Enterprises repeat goals endlessly but skip strategy. In the AI era, that gap between knowing the destination and coordinating the route is existential.

Velocity isn't about shipping more features. It's about running faster learning loops that turn uncertainty into validated decisions.

Retention problems are created in week one, not month six. Product decisions about time-to-value determine long-term stickiness.

Prototyping tools like Claude Code now serve both discovery and production, narrowing the gap between build-to-learn and build-to-earn.

Two-thirds of organizations are stuck in AI pilot phase. The gap between adoption and enterprise value isn't technology—it's redesigning workflows.

Everyone's racing to add AI features. Few are building AI moats. The difference determines who's still competitive in 18 months.

Product sense isn't magic—it's systematic practice. Learn how to build intuition through decision-making, user empathy, and pattern recognition.

Webflow's AI search data reveals why aggregate traffic is misleading and what product teams should measure instead.

Daily publishing needs a scalable taxonomy. Claude Code built mine in 45 minutes: 63 tags → 40, three tiers, full automation.

Managers must add more value than they cost. Apply customer-thinking to direct reports: justify your existence through real services.

99 posts in 100 days: patterns that emerged, AI's surprising dominance, and 5 posts to start with if you're new here. Reflection on daily writing.

Exploring a B2B GTM survey through a PM lens: two data points that might change how you think about pricing and AI features.

Meta's Early Experience research explores agents learning from their own rollouts. Early results look promising—here's what changes if it scales.

A simple framework to evaluate product impact: map your work by customer value and business value to focus on what matters most.

How product teams can avoid paralysis in the AI era by acting before the window closes and minimizing the cost of delay.

A practical, no-hype guide for project managers moving into product roles — how to shift from delivery to discovery, unlearn old habits, and build learning loops that compound insight.

Claude Skills let users package reusable workflows that make Claude adaptable and modular: a practical leap in how AI assistants work.

AI-assisted prototyping is reshaping collaboration across product, design, and engineering—accelerating discovery and demanding the best from each discipline.

AI agents don’t replace jobs—they expand what teams can achieve. Learn how product leaders can turn automation gains into growth opportunities.

Spotify’s “bets board” shows how leaders can treat decisions as experiments. Here’s how to explore that mindset without copying the model.

Evals make AI products measurable. Traces, annotations, and layered tests turn evaluation into a practical loop for reliability.

Claude Sonnet 4.5 introduces usage tracking and thinking mode enhancements that streamline AI planning and session management.

How product managers can move beyond feature roadmaps to build strategy-driven outcomes, handle stakeholder pressure, and make sharper prioritization decisions.

AI makes building faster, but not smarter. The new PM advantage is clarity, knowing what to test, why it matters, and how to learn fast.

Notes on strategy, speed, and why modern product leadership is a leverage game.

How I built a scalable, AI-powered blog archive by learning GenAI coding constructs and focusing on product thinking, not syntax.

In the AI era, the strongest products don’t build walls — they build bridges. Here’s why connectivity, not isolation, defines modern defensibility.

AI feedback loops can lie. Learn why engagement metrics fail and how product managers can rebuild truth-centered measurement systems.

Platform products need empathy and accountability. Treat them like external products — measure impact, earn trust, and prove real value.

Exploring how agentic loops extend feedback loops by adding autonomy, iteration, and goal-directed action in systems and AI.

The core skills once seen as future-ready—adaptability, creativity, and tech fluency—are already defining how work gets done today.

Cloudflare’s VibeSDK acts like a factory robot for apps. It turns plain language into live software while teams stay focused on customer value.

How AI transforms product leadership from building to conducting. The rise of the Orchestrator mindset in product management.

Moving beyond the search for meaning to the practice of creating it. A product manager's reflection on making work matter, one sprint at a time.

Most 'AI products' aren't AI-native. Use the Home Screen Test to spot the billion-dollar opportunities hiding in plain sight.

AI is collapsing the line between platforms and products. The winners will master both, balancing ecosystems and user experiences.

Intuition is a compass, metrics are a map. Here’s how product managers can decide which to trust, depending on the product stage.

Metrics measure the present, but intuition imagines the future. Here’s why great product managers need both — and how to define intuition.

Apple’s iPhone 17 shows the sugar water trap risk as AI reshapes tech. A lesson for product managers on balancing incremental progress with bold bets.

How to make outcomes real, align cross-functional teams, and still give leaders confidence with a dual lens scorecard, DORA metrics, and probabilistic forecasts.

Learning how to learn is the real superpower for product managers. It’s not about speed, but reinvention, adaptability, and enjoying the process.

Product leaders must treat their job like a product and protect maker time, or risk getting stuck in execution and missing leadership growth.