Mastodawn

@nixCraft I bet some AI bros see soaring prices as a side bonus, given that users dealing with increasingly narrow hardware constraints might be pushed to make a heavier use of cloud computing power even for trivial activities.

The higher the barriers to access to good hardware are, the more power is wielded by those who control data centers. And there is always going to be enough funding for building more data centers. #AIeconomics

Miguel Afonso Caetano Jun 12

"4. Benjamin owns a farm. He employs 100 workers plowing his fields. His total payroll is $10 million/year. One day, he buys a mule, which provides the worker who uses it with a modest 10 percent productivity gain. Benjamin fires 99 of his workers and purchases 99 mules, expecting a 1,000 percent productivity gain. The driverless mules cause plow damage to his property in excess of $50 million. Benjamin loses another $5 million due to the loss of productivity from his one remaining employee, who no longer guides a plow but instead spends 100 percent of his time shoveling mule shit. Goldman Sachs builds an altar to Benjamin in their lobby and cuts out the heart of a junior analyst on it every Friday. They call it “Blood Sacrifice Friday.” The name isn’t catchy, but the event becomes a management favorite nonetheless."

https://www.mcsweeneys.net/articles/ai-economics-for-dummies

#AI #GenerativeAI #PonziScheme #AIBubble #AIEconomics

AI Economics for Dummies

“Xavier owns an apartment that he rents out at a loss of $1 billion/month. Seeing this success, he decides to make financial commitments to construct $850 bi...

McSweeney's Internet Tendency

NERDS.xyz – Real Tech News for Real Nerds [Unofficial]Jun 10

Linux Foundation launches Tokenomicon conference focused on AI economics

https://fed.brid.gy/r/https://nerds.xyz/2026/06/linux-foundation-tokenomicon-ai-economics/

the spend Jun 9

FYI: The AI bill that nobody budgeted for https://thespend.net/the-ai-bill-that-nobody-budgeted-for/?utm_source=dlvr.it&utm_medium=mastodon #AIEconomics #TokenEconomics #AIBill #ArtificialIntelligence #FutureOfWork

The AI bill that nobody budgeted for

Token economics are reshaping how companies pay for AI - and the bills are nothing like what anyone expected.

the spend

AIagent.at 🤖 AI News May 30

Corporate America is waking up to the eye-watering cost of AI after companies burned hundreds of millions in token spend with little to show for it. One client reportedly spent 500M USD in a single month with no usage limits. Meta and Amazon have already scrapped internal leaderboards after staff were giving AI agents pointless tasks just to climb the ranks. https://gizmodo.com/companies-are-getting-burned-by-burning-tons-of-tokens-2000765232 #AIagent #AI #GenAI #AIEconomics

Companies Are Getting Burned by Burning Tons of Tokens

Wait, this costs money?

Gizmodo

readuncut May 22

Five9's CEO described the mechanism with clarity: 'AI is replacing humans over time, and those dollars are going back into the software.' Money that used to pay support agents now pays cloud bills, which pay for GPU clusters, which show up as revenue at hyperscalers. The bet was never productivity — it was permanent wage compression with better PR.

https://readuncut.com/the-ai-layoff-receipts/

#AIEconomics #WageCompression #CloudComputing #TechConcentration #PayrollTransfer

The AI Layoff Receipts

This article explores do layoffs for AI actually help a business in the long run. We analyze 1000s of transcripts and stock filings to look at the data - the answer is depressing.

Read Uncut

HackerNoon May 8

AI is driving productivity gains and massive investment, but rising layoffs and shrinking labor share raise deeper economic questions. https://hackernoon.com/the-ai-productivity-paradox-nobody-wants-to-price-in #aieconomics

The AI Productivity Paradox Nobody Wants to Price In | HackerNoon

AI is driving productivity gains and massive investment, but rising layoffs and shrinking labor share raise deeper economic questions.

Harald Klinke Apr 30

Agentic AI is reshaping the classic buy or build decision. Not by replacing SaaS across the board, but by shifting the economics and governance of building software. The real change is hybrid: owning code while depending on external AI infrastructure. #agenticai #enterprisesoftware #aieconomics

The Buy-or-Build Decision, Rev...

The Buy-or-Build Decision, Revisited: How Agentic AI Changes the Economics of Enterprise Software

Advances in generative artificial intelligence, particularly agentic coding systems capable of autonomous software development, are disrupting the economics of the make-or-buy decision for enterprise applications. The "SaaSocalypse" narrative predicts that AI will render large segments of the Software-as-a-Service market obsolete by enabling firms to build software in-house at a fraction of historical cost. This paper adopts a conceptual research approach, combining transaction cost economics and the resource-based view with an assessment of current AI capabilities, to systematically re-evaluate the factors underlying the make-or-buy decision. It makes three contributions. First, it provides a factor-level analysis of how AI reshapes seven canonical decision determinants: cost, strategic differentiation, asset specificity, vendor lock-in, time-to-market, quality and compliance, and organizational capability. Second, it develops a typology of enterprise applications by their sensitivity to AI-induced shifts in make-or-buy economics. Third, it demonstrates that AI fundamentally transforms the governance properties of the Make option, shifting it from Williamson's pure hierarchy to a hybrid governance form that combines code ownership with external AI infrastructure dependency, with qualitatively different economics, capability requirements, and governance structures than pre-AI in-house development. The analysis finds that the SaaSocalypse thesis is overstated for most enterprise application categories; Make is most compelling for commodity utilities and differentiating custom applications in the AI era, while regulated and mission-critical systems remain predominantly in the buy domain.

arXiv.org

Harald Klinke Apr 30

Agentic AI is reshaping the classic buy or build decision. Not by replacing SaaS across the board, but by shifting the economics and governance of building software. The real change is hybrid: owning code while depending on external AI infrastructure. Make becomes viable for commodity tools and differentiating layers, while regulated core systems remain in the buy domain.

https://arxiv.org/abs/2604.26482v1

#AgenticAI #EnterpriseSoftware #BuildVsBuy #AIeconomics

The Buy-or-Build Decision, Revisited: How Agentic AI Changes the Economics of Enterprise Software

Advances in generative artificial intelligence, particularly agentic coding systems capable of autonomous software development, are disrupting the economics of the make-or-buy decision for enterprise applications. The "SaaSocalypse" narrative predicts that AI will render large segments of the Software-as-a-Service market obsolete by enabling firms to build software in-house at a fraction of historical cost. This paper adopts a conceptual research approach, combining transaction cost economics and the resource-based view with an assessment of current AI capabilities, to systematically re-evaluate the factors underlying the make-or-buy decision. It makes three contributions. First, it provides a factor-level analysis of how AI reshapes seven canonical decision determinants: cost, strategic differentiation, asset specificity, vendor lock-in, time-to-market, quality and compliance, and organizational capability. Second, it develops a typology of enterprise applications by their sensitivity to AI-induced shifts in make-or-buy economics. Third, it demonstrates that AI fundamentally transforms the governance properties of the Make option, shifting it from Williamson's pure hierarchy to a hybrid governance form that combines code ownership with external AI infrastructure dependency, with qualitatively different economics, capability requirements, and governance structures than pre-AI in-house development. The analysis finds that the SaaSocalypse thesis is overstated for most enterprise application categories; Make is most compelling for commodity utilities and differentiating custom applications in the AI era, while regulated and mission-critical systems remain predominantly in the buy domain.

arXiv.org

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zeldman Apr 29

“When the bill arrives, the industry may discover that the storm was not intelligence. It was arithmetic.” 3/3 www.pootlepress.com/2026/04/ai-t... #aiEconomics

AI, Tokens, and the Gathering ...

AI, Tokens, and the Gathering Storm | Pootlepress

There is a possible future in which the AI boom does not end with a robot butler bringing us tea. It ends because somebody asks: “Wait. Why is this worth a trillion dollars?” OpenAI and Anthropic are now discussed less like companies and more like weather systems. Their valuations roll across the financial sky in […]