The Age of Steam Engines, Waiting for Carnot: The Mindset Science Needs Right Now
The gap between a machine that works and a principle we understand is one of the oldest scenes in the history of science. In an era that solves everything wi...
The gap between a machine that works and a principle we understand is one of the oldest scenes in the history of science. In an era that solves everything wi...
As engineering, product, design, and data blur into a single mass, Boris Cherny, the creator of Claude Code, proposes five role archetypes and a team-composi...
A comparison of the worldviews of Hassabis, Huang, and Amodei, who read the same AI wave through three different lenses of AGI, infrastructure, and labor, an...
When NVIDIA CEO Jensen Huang’s vision of ‘hundreds of agents per engineer’ becomes reality, how must organizational structures and ways of working change?
Starting from DeepMind CEO Hassabis’s statement that we are ‘nowhere near AGI,’ this post explores why AI organizations should make honest expectation-settin...
Starting from a market-coined label about Jensen Huang, and deepening the Moneyball legacy, how to root a data-beats-intuition decision culture inside your o...
When the marginal cost of code approaches zero, the value of an engineering team shifts from ‘what we build’ to ‘knowing what should be built.’
How to embrace and develop the new development culture brought by Vibe Coding and Agentic Coding? A guide to building collaborative culture with AI, breaking...
How to leverage Saberr algorithms to quantify team compatibility through 15-minute surveys and behavioral data, optimizing everything from hiring to onboarding
How to apply Moneyball strategy that discovers hidden value through data and achieves maximum performance relative to resources in development, product, and ...
In the AI era, developers don’t need to know everything. Explore a new paradigm that transforms ignorance into strength through hacking mindset and reverse e...