- Essays··10 min read
The Bill That Ended the Pilot
Uber burned its entire annual AI coding budget in four months — the full allocation gone by spring, no controlled overrun flagged in planning. Three-quarters of enterprises watched AI costs blow past budget last year, and the correction now arriving is triage, not enthusiasm. The governance failure and the cost failure are the same failure: if you cannot name who changed the production prompt, what it scored before it shipped, or what spending ceiling it is running under, the debt is already due.
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The Agents You Cannot Name
Most enterprises deploying AI agents cannot list what is running, who approved it, or what it costs: a governance gap that is today's operating environment, not a future risk. Agentic workflows trigger ten to twenty LLM calls per task, and token volumes have grown sixty-fold since 2023. The agents you cannot name are the ones that will fail an audit, breach a data policy, or exhaust months of budget because nobody set a spend limit.
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The Guardrail You Can Audit
The EU AI Act's Article 12 logging requirement is an architectural obligation, not a monitoring one. Guardrails embedded inside the application produce audit evidence the application controls; guardrails deployed as a gateway produce records the application cannot reach. That distinction decides compliance, and organisations retrofitting the wrong architecture will find the fix costs three to five times what building it correctly would have.
eu-ai-actai-guardrailsaudit-loggingcompliance-architectureRead - Essays··10 min read
The Specification You Can Download Is Not the System You Can Buy
A ratified specification is not a commissioned cluster. UALink 2.0 promises 1,024-accelerator pods at half the TCO of NVSwitch, but evaluation hardware is not expected until late 2026, and your purchase order is due in August. The more productive question for enterprise finance is whether InfiniBand or Ethernet closes your deployment faster than a roadmap that has not yet touched silicon.
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40% Escalated to the Board: The AI Invoice Surprise of 2026
Uber burned its entire 2026 AI coding budget by April, and it is not an outlier: unexpected AI costs changed a business decision at 62% of organisations this year. A charge only reaches directors once it has cleared the spending authority of whoever caused it. Budgets set in 2025, before agentic workloads ran at production scale, are now carrying orphaned agents that burn tokens with no owner and no attributed business outcome.
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The '19%' problem: what Gartner's productivity surveys actually measured this spring
Two Gartner surveys published in May 2026 reveal a measurement crisis enterprises have not yet named: time saved per AI seat is real, but organisations lack the controls to redeploy that capacity or quality-gate its output before it reaches the P&L. Between 60% and 89% of firms see zero detectable productivity impact despite widespread adoption. That is a governance problem that registers as a measurement problem and gets blamed on the models.
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BMW just put a number on humanoid ROI · the rest of manufacturing is watching
BMW's ten-month, 30,000-unit deployment of Figure AI's humanoid at Plant Spartanburg has shifted the industry's central question from 'can it work?' to 'at what cost, and where?' With unit costs projected below $17,000 by 2030 and current ROI timelines compressing toward 14 months, humanoid robots are becoming a capital-allocation decision. The binding constraint has moved from hardware to integration.
humanoid-robotsmanufacturing-aiindustrial-automationphysical-aiRead - Essays··8 min read
The $500 Million Bill Nobody Anticipated: When AI Slop Debt Becomes a Balance-Sheet Problem
An enterprise client burned $500 million on AI services in a single month, a consequence of deferred governance rather than reckless strategy. AI slop debt, the compounding cost of zombie agents, ungoverned prompts, and abandoned POCs that still bill, has crossed from engineering irritation to balance-sheet liability. When 73% of AI initiatives exceed budget, the board question is no longer which use cases to fund but who can turn off what is already running.
enterprise-aiai-governancefinopsai-agentsRead - Essays··8 min read
Harvey Signs at Raffles Place. The Bill Starts Now.
When WongPartnership signed with Harvey, it acquired a seat licence and a compounding stack with it: wrapper-maintenance costs running 30–60% above the sticker, prompt libraries with no clear owner, and a hallucination-liability perimeter across three jurisdictions that Vietnam's new AI statute just made more expensive. The Forrester 400% ROI ceiling belongs to firms with clean, documented processes. Most Southeast Asian mid-market partnerships are not those firms.
legal-aisingaporeai-governanceprofessional-liabilityRead - Essays··8 min read
Nadella's Half-Drawn Ledger
Satya Nadella's essay on the reverse information paradox names a real problem: enterprise buyers surrender proprietary knowledge to AI vendors with each query: prompts, corrections, evaluation harnesses. The framing is analytically sound. It is also written by the CEO most commercially exposed to a future in which that knowledge lives outside his cloud tenant. The enterprise buyer's job is to notice which parts of the argument survive when the messenger changes.
enterprise-aidata-sovereigntyinformation-paradoxmicrosoftRead - Essays··11 min read
Uber Burned Its Entire 2026 AI Budget in Four Months · The Bill Coming Due
Uber exhausted its entire 2026 AI coding budget by April, four months into the year. Beneath that headline sits a three-layer debt stack: technical debt, ungoverned prompt sprawl, and cost overhang accrued during a subsidised-inference era now ending. Organisations that treat AI spend as an architectural concern from day one will survive what follows; those that audit costs only after the invoice arrives will not.
ai-cost-governanceenterprise-aifinopstechnical-debtRead - Essays··9 min read
Mandates without mastery: the AI upskilling gap that vendor dashboards hide
Corporate AI mandates now outrun demonstrable capability. Google ties usage to performance reviews, Meta tracks AI-assisted output, Microsoft has declared it non-optional. 82% of organisations provide AI training; 59% still report a skills gap. Access is not the deficit. Completion certificates measure the wrong thing, and firms are applying one-time training models to a skill that demands continuous, deliberate practice on realistic tasks.
ai-upskillingenterprise-aiworkforce-developmentskills-gapRead - Essays··7 min read
The Slop Debt Bill Is Due, and Nobody on the Org Chart Owns It
Slop debt is the space between what you pay for AI and what you do not get. The bill is in the inbox; the question is whether the org chart catches up before the auditor does.
slop-debtfinopsagentic-aiai-governanceRead - Essays··8 min read
the kernel of truth and the trillion-dollar bet
A bubble is not the same thing as a lie. There is a real technology, it gets oversold, and the financing built on the overselling becomes the actual fragility. The question that matters: who's holding the debt when demand disappoints?
ai-bubblehyperscaler-capexcircular-financingproductivity-paradoxRead - Essays··7 min read
200 million to Study the Wave You're Making
A frontier lab has priced in the scenario where its product makes office work unnecessary, and is funding the academics who'll help governments respond. Adoption is wide; realisation is narrow. The gap is now numerical.
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the productivity number nobody can actually measure
When the number is real, the baseline comes with it. Everything else is a story about the future wearing a percentage sign.
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the 0.1% problem · when the productivity number depends on who's holding the ruler
BofA's 10x and the economy's 0.1% measure different things and call both 'productivity'. The number is only as honest as the ruler, and right now almost everyone is holding the ruler that pays them.
ai-productivitymeasurementmetrenterprise-aiRead - Essays··7 min read
The bill nobody booked
The most expensive line item in your AI budget for the next two years is the one your finance team has not yet named. It is sitting in your environment already, in half-built pilots, ghost fine-tunes and redundant copilots, capitalising itself into your monthly cloud invoice.
ai-slop-debtfinopsenterprise-aiai-governanceRead - Essays··7 min read
13%: the upskilling number that quietly breaks the agentic AI business case
Only 13% of employees can actually work with the agents their firms are deploying. The centaur the whole thesis assumes is mostly a novice holding the reins, and AI is demolishing the training ground that produced the experts.
agentic-aiworkforce-upskillingdeliberate-practiceapprenticeshipRead - Essays··11 min read
Sunday Essay · The Three Productivity Curves We Refuse to Reconcile
Three credible measurement traditions, applied to the same workforce in 2026, point in three different directions. The discourse treats them as one number. The gaps between them are the actual managerial signal.
ai-productivityenterprise-aimeasurementcentaur-vs-autopilotRead - Essays··8 min read
The owners are right. That's the part nobody wants to sit with.
The owners are directionally right that they can run with far fewer people. They are very often wrong about which people, how fast, and what it costs to get there. Those two things are the whole story.
ai-and-labourworkforce-displacemententerprise-aiautomation-economicsRead - Essays··7 min read
12% Faster, and Other Numbers I Don't Yet Believe
Four data sets, three methodologies, and no one who matters can yet give you a single defensible figure for AI's effect on knowledge-work productivity. The measurement culture is not up to the tooling, and the vendors will close that gap last.
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