If You're Not Building, You're Not Learning
Access to the newest AI tools is useful. Hands-on building is what turns access into skill.
Read the article →It Is Okay to Be Unrealistic
Ambitious goals are not commitments. They are a way to test the edge of what you are capable of, especially in the age of AI.
Read the article →Slow is smooth. Smooth is fast. Especially with AI.
Maximizing the speed of every step can make the whole system slower. Intentional friction is what turns AI speed into finished work.
Read the article →Flow state in the age of AI
The real AI superpower is learning to enter creative flow almost on demand, unlocking what humans and AI can achieve together.
Read the article →Five games. Five new worlds.
Dedicated websites are now live for five upcoming original games, each with its own identity, mechanics, and world.
Meet the games →More to come
The blog is open. Posts on AI development, product development, games, and studio news are on the way.
Read the post →WIP limits for humans and AI
Finishing more with better quality means limiting work in progress across the whole human-and-agent system.
Read the article →Can design.md be the design system?
A portable, versioned instruction layer can help AI coding agents produce interfaces that belong to the same product.
Read the article →The real gold rush in agentic AI
The most valuable discoveries are often tiny workflow nuggets found in real work, then written down so they compound.
Read the article →The rise of the AI-native Product Engineer
Strong engineering fundamentals, product sense, and AI-native workflows are converging into a powerful hybrid role.
Read the article →Judgment matters more than ever
Moving fast only matters when the product is moving in the right direction.
Read the article →Vibe coding: human-led, AI-accelerated
Professional software engineering can use AI for speed without surrendering human direction and responsibility.
Read the article →AI Ledger: Git-native governance for agentic AI
An append-only standard for declaring intent, keeping scope explicit, and recording what AI agents actually changed.
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