Digest 7 min read Free

Monthly Learnings from the Daily Digest: May 2026

May marked a shift from fascination with foundation models toward the systems engineering that makes AI useful. As models commoditize, advantage is moving to harnesses, memory, failure handling, safe execution, and redesigned operating workflows.
Profile 9 min read Free

Lessons from Tom Freston

Lessons from Tom Freston Tom Freston co founded MTV, building a niche cable channel into a global cultural brand by championing offbeat creative talent...
Digest 7 min read Free

Daily Digest - 2026-05-30

1. My Agent Stack For Automating My Personal Life — Nicolas Bustamante Why read: A practical breakdown of using AI agents to automate personal workflows...
Research Explainers 6 min read Free

AI May Give Star Employees More Bargaining Power

This paper argues that generative AI may not flatten performance differences in knowledge work. It may widen them, especially when star employees have the judgment, autonomy, and reputation to turn AI into portable bargaining power.
Research Explainers 7 min read Free

Compute Is Not a Commodity

This paper argues that AI compute is not a simple commodity input. Chip architecture, energy use, software, training workloads, inference workloads, and policy all change what one more unit of compute really means.
Research Explainers 5 min read Free

AI Costs Need a Control Plane

An enterprise AI cost paper proposes a dedicated operating model because generative AI spend is driven by usage, ownership, governance, and workflow design. It connects unit economics to accountability for where, why, and by whom inference is consumed.
Research Explainers 8 min read Free

The CEO Sets the AI Operating Model

A Strategy and Leadership paper argues that CEOs lead AI transformation through generalist, expert, or disruptive operating models, each with different risks. The framework helps leaders choose where expertise, authority, and organizational disruption should sit.
Research Explainers 9 min read Free

Context Engineering Is the New Systems Layer

A broad survey argues that the hard part of useful AI systems is no longer prompt wording but deciding what information reaches the model, when, and under what constraints. That makes retrieval, memory, permissions, timing, and context assembly a systems discipline.

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