Also: Goldman’s 24x token forecast, Indian IT’s process-debt pitch, NatWest’s 35% AI-generated code, Gartner’s 84% productivity theater, vibesec.
Related to your interests
- ‘I’m delighted to be wrong’: Sam Altman says AI won’t lead to a ‘jobs apocalypse’ - but admits he was ‘pretty wrong’ on the social and economic implications it is having - “It really, in both positive and negative ways, updated me to thinking that the jobs picture is likely to be very different than we thought,” he said. CEO Said a Thing: “I don’t think we’re going to have the kind of jobs apocalypse that some of the companies in our space advocate or talk about.”
- The AI efficiency plateau - Yes: “Among developers who reached the highest time-savings band, roughly 7 in 10 (69.7%) got there in less than two quarters.” But: “Of those developers who reached peak time savings, two-thirds (66.1%) reported lower time savings in the quarters that followed.”
- AI Agents Forecast to Boost Tech Cash Flow as Usage Soars - Yes: “The important point is that the adoption rates are still relatively low today, especially in small to medium-sized businesses. In 2030, we forecast that 12% of knowledge workers will be using agentic AI yet by 2040 that figure will be 37%. You have this very long tail adoption.” But: “Agentic AI is expected to drive a 24-fold increase in token consumption by 2030 as consumers and enterprises adopt the technology, according to Goldman Sachs Research” // The vibe I get is that a lot of that token increase is consumer and end-user oriented: replacing search, organizing inboxes.
- U.S. companies have an AI problem. Indian IT wants to be the solution - ‘“The real question in enterprise AI is not who builds the most capable model. It is, ‘Who can make AI work inside messy, complex enterprise environments that have accumulated decades of process debt, data debt, technology debt, and cultural debt?'” he said. “That is precisely the terrain Indian IT firms know best."’
- AI at work is anti-labor by design - Their theory: enterprise AI ROI is laying off people.
- Gartner Says CFOs Risk Falling Behind Without a Scalable AI Strategy - Excerpts here.
- NatWest inks AI deal for trade finance - “Headline figures for 2025 saw the bank’s software engineers generate 35% of its code through AI software development tools, all 60,000 staff given access to AI productivity software, and thousands of human hours saved. Last year, the bank also embarked on a major collaboration with AI supplier OpenAI.”
- Trisha Gee: AI Amplifies What’s Already Broken
AI Summaries
I wanted to read these, but I didn’t make the time, so I asked the robot to summarize them.
- 🤖 DX Data Shows AI Coding Time-Savings Spike Fast, Then Fade for Two-Thirds of Developers
- 🤖 NVIDIA’s Erickson: Stop Asking AI to Do Everything - Build Platforms Where Deterministic Tools Ground Stochastic Agents
- 🤖 Anthropic’s Claude Code Lead: Coding Is “Solved” For My Work, 100x More “Builders” Coming, Software Engineer Title Dies This Year
- 🤖 Why AI Won’t Erase White-Collar Jobs: The Power of Bundles, Authority, and Human Trust
- 🤖 AI Boosts Software Output but Exposes Fragile Processes and Rising Cognitive Debt
- 🤖 Leo XIV’s First Encyclical: AI as the New Tower of Babel and Why Catholic Social Doctrine Needs a Reboot
- 🤖 Multi-Agent AI Faces a Delegation Crisis: Authority Lags Behind Connectivity
- 🤖 Epstein on Constraints: Monotask, Satisfice, Brainwrite, Share Obligations, and Build Commitment Devices
Wastebook
ICYMI
- A short video from me: When it comes to enterprise AI, here’s three things I’ve been hearing: (1) cost - we finally have to pay for this stuff - holy cow! (2) Cases - programming is great, but what else can we use this for aside from customer service and gussied up search? (3) Control - we can’t even track costs, how are we going to manage everything else?
- Elusive Enterprise AI ROI: No scaling, it’s not legible, lack of skills/need for training - there were several things saying AI for ROI is not doing as great as planned. Here, I round them up.
- Enterprise AI Slop
- The O-Ring and the Keystone: Two Readings of Where Humans Sit in an Automated Economy - In the AI replacing humans talk, you hear about O-Ring theory sometimes. It goes something like this: in a ten step process, if you mess up one of the steps, even if the other 9 are perfect, the whole process is tanked. The positive reading is something more like: you don’t automate aggressively unless you trust the O-ring. // Anyhow, here is AI writing it up for reference and connecting to AI and other jobs.
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