Learning from examples: AI assistance can enhance rather than hinder skill development - “Decades before the advent of generative AI, the legendary UCLA baseball coach John Wooden declared that the four laws of learning are explanation, demonstration, imitation, and repetition (31). Few learners have access to the best human teachers, coaches, and mentors, but generative AI now makes it possible to learn from personalized, just-in-time demonstrations tailored to any domain. In doing so, AI has the potential not only to boost productivity but also to democratize opportunities to build human capital at scale.” // Also, some prompts used to evaluate writing quality. The one rating “easy responding” is interesting: how easy is it to (know how to) respond? Maybe good for CTAs.

OpenAI reaches 400M weekly active users, doubles enterprise customer base - SiliconANGLE - “The ChatGPT developer currently has 2 million paying enterprise users, twice as many as in September.” With “400 million active weekly users, a 33% increase from December.” And: “The New York Times reported in September that the company was expecting to end 2024 with a $5 billion loss on sales of $3.7 billion."

IBM co-location program described as worker attrition plan - From the RTO-as-not-so-stealthy-layoff files.

2025 is the breakthrough year for Generative Enterprise — and partnering with a capable services partner is critical - “[S]pending on GenAI is rising (HFS data suggests enterprise investment is rising by more than 25% on average into 2025), we start from a low base. We estimate enterprise spending on GenAI in 2024 accounted for less than 1% of global IT services spending. This is just one illustration of how far we still have to go.” // Plus, a whole bunch of commentary in enterprise AI.

A Simple Definition Of “Platform” - “a product that supports the creation and/or delivery of other products."

Inside Oracle’s New AI Agents - Moor Insights & Strategy - Getting the robot to do annual performance reviews: “Oracle is also leveraging AI to improve the performance review process itself. By aggregating and distilling information from check-ins, feedback and goal progress throughout the year, the AI agent can generate a first draft of a performance review. This should save managers time and effort while fostering a more comprehensive assessment of employee performance.” // Performance review are notoriously bullshit in the first place. What’d be interesting here is to have the robot go over the past five years and make a performance review and then compare it to what the human managers did. Which ones are (1) more correct, and, (2) better connect employee performance to organization goals (profit, growth, customer service, productivity/lower cost, etc.)

To avoid being replaced by LLMs, do what they can’t -

No Rules Are Implicit Rules - The European view on enlightened American management policy: “Greg, I hate to bring it to you, but working for ten fucking hours a day is not the normal hour. I don’t care if you live in America or not. The section continues with other “grand” examples of managers taking “up to” 14 days a year off to show their employees they should to so too. Let’s assume the best here: 14 workdays are almost three weeks. A year. The statutory minimum for full-time employees working a forty-hour week is 20 (thus 4 weeks) in Belgium. Oops."

On European Defence, Energy and Growth - Imagining big changes in European priorities: changing policy to get more energy, more emphasis on militaries.

AI Agents and the CEOs - “At the risk of saying the quiet part out loud, the way CEOs are talking about agents sure sounds like how they talk about employees–only cheaper!” // “Companies are dedicating significant spend to AI–approximately 5% of the revenue of large enterprises (revenues over $500 million) according to one survey by Boston Consulting Group, and yet only 25% claim they are seeing value from their AI investment."