Input Reads, Output Builds
Why Gemini 4 Argon’s jump from 64K to 1 million output tokens matters more than input context, and why verification becomes the new bottleneck.
Essays on AI agents, models, enterprise adoption, education and AI geopolitics.
Why Gemini 4 Argon’s jump from 64K to 1 million output tokens matters more than input context, and why verification becomes the new bottleneck.

Anton Leicht’s case that countries without frontier AI risk a permanent periphery, why walls make it worse, and how sites and megawatts can buy access.

Why culture and data quality, not models, hold back enterprise AI, and why processes need redesign rather than automation: notes from a CIO summit.

A reply to Thompson’s warning that AI drafting will make people stop thinking: the effort moves to setting intent first and verifying output after.

A 2025 report finds AI raises software delivery throughput but also instability. The seven DORA capabilities that turn speed into organizational gains.

An electric hypercar’s 308.4 mph record and the hard problem of robot dexterity as signs that technology is returning to the physical world.

How three people at Google Labs built a source-grounded AI tool, and what it shows about focus, small teams and shipping before it is perfect.

Google Research’s Learn Your Way turns textbooks into personalized lessons. What that could mean for apprenticeships and workforce training in Europe.

How Google’s Agent Payments Protocol uses cryptographic mandates to let AI agents pay, why it matters for German firms, and the risks it brings.

Elon Musk’s answer during an intriguing interview on Artificial Intelligence (must-watch!) to what would he ask an an all-knowing-machine (AGI) : …“What’s outside the simulation?”