Field notes

Insights on practical AI

Dario Amodei’s Policy on the AI Exponential — A Breakdown
AI Policy · 5 min read

Dario Amodei’s Policy on the AI Exponential — A Breakdown

A comprehensive analysis of Dario Amodei’s essay on AI regulation, macroeconomics, biomedical acceleration, civil liberties, and democratic leadership.

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When AI Helps Spot Lies — and Builds a Dangerous Confidence
ai-strategy · 3 min read

When AI Helps Spot Lies — and Builds a Dangerous Confidence

A study found AI chatbots help people catch fake news 21% better — but also create dangerous overconfidence. What enterprise AI leaders need to know about automation bias.

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AI Economic Indicators: A New Framework for Measuring Enterprise Impact
ai-adoption · 4 min read

AI Economic Indicators: A New Framework for Measuring Enterprise Impact

Stanford's new AI Economic Indicators platform gives enterprise leaders a data-driven way to track how AI adoption reshapes productivity, work, and market dynamics.

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Inside the Google-Apple $1 Billion AI Deal: What Enterprise Leaders Need to Know
ai-partnership · 5 min read

Inside the Google-Apple $1 Billion AI Deal: What Enterprise Leaders Need to Know

Google's $1B Gemini deal with Apple marks a new phase in enterprise AI partnerships. What CIOs and CTOs should learn about model ownership, data governance, and competitive strategy from this landmark agreement.

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How to Build an AI Adoption Strategy Deck That Actually Gets Used
ai-adoption · 4 min read

How to Build an AI Adoption Strategy Deck That Actually Gets Used

Stop adding AI tools randomly. This framework turns chaos into a structured rollout plan with use cases per department, risk mitigations, training workflows, and a 30-60-90 day roadmap that executives will actually approve.

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NVIDIA's Nemotron 3 Ultra: What Open-Source 550B MoE Models Mean for Enterprise AI Strategy
nemotron-3-ultra · 6 min read

NVIDIA's Nemotron 3 Ultra: What Open-Source 550B MoE Models Mean for Enterprise AI Strategy

NVIDIA released Nemotron 3 Ultra, a fully open-source 550B-parameter Mixture-of-Experts model with a 1M-token context window and hybrid Mamba-attention architecture. We examine the implications for enterprise AI procurement, inference costs, and deployment in regulated industries.

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Agentic AI's First Invoice: What Enterprises Must Know
agentic-ai · 5 min read

Agentic AI's First Invoice: What Enterprises Must Know

CEOs at Coinbase, Meta, Cloudflare, and Atlassian replaced engineers to prepare for agentic AI. Now those companies face their first real Anthropic invoices. Learn what this means for enterprise AI cost strategy and how to build an ROI framework before your next AI deployment.

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AI Agents Still Fail 70% of Real Office Tasks — What Enterprise Leaders Need to Know
ai agents · 3 min read

AI Agents Still Fail 70% of Real Office Tasks — What Enterprise Leaders Need to Know

Carnegie Mellon's agent study shows AI agents complete only 30% of real office tasks. New models did not close the gap. Here is what this means for enterprise AI strategy and governance.

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