Apple trims AI budgets as agents drive costs higher
- Apple lowered engineers’ daily AI spending cap from $300 to $200, with further cuts under consideration.
- Hosts say agents are pushing companies from flat-rate access toward bills based on usage and work done.
- The challenge is controlling fast-growing costs without stifling workplace AI use.
Apple has lowered its engineers’ daily AI spending cap from $300 to $200, and further cuts may be coming. The AI Daily Brief reported that the company is considering a $100 limit for engineers; non-engineers already have a $100 cap that could fall to $25. The limits sit uneasily alongside Apple’s push to promote AI features and encourage employees to use AI internally.
The cuts come as AI use is driving bills higher. The AI Daily Brief’s Nathaniel Whittemore cited a Menlo survey of about 400 U.S. enterprise decision-makers: average AI spending per company using AI rose 4.7 times in 2026, while the share of companies using AI grew from 55% to 65%. Whittemore pointed to agents, which can keep working on tasks after employees step away, as a reason spending is shifting from access for each worker to tokens and completed work.
That shift complicates the idea of a fixed daily allowance. Software engineer Peter Steinberger argued that individual spending caps may stop making sense when agents run ongoing loops and maintain entire codebases. On This Week in Startups, Jason said companies will likely move high-value AI tools away from flat-rate subscriptions and toward usage-based corporate pricing, with employers scrutinizing who uses them.
For companies, Apple’s cuts show the tension: AI can become more useful as agents take on longer-running work, but that work can also make costs harder to predict. The question is not only how much access to give employees, but how to pay for AI when usage increasingly reflects work done rather than seats filled.
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Nathaniel Whittemore
Companies Are Spending 5x More on AI Now • Nov 7
- Nathaniel Whittemore says business AI adoption is accelerating despite headlines about companies restricting employee use, including Apple limiting engineers’ daily AI spending. Agents are shifting enterprise spending from per-seat access toward tokens and work completed.
Also discussed on this episode: (19)
Enterprise (5)
- Menlo’s enterprise AI estimates put annual spending at $33 billion in 2025 and nearly $177 billion in 2026; its reported growth multiples were 5x from 2023 to 2024 and 3.9x from 2024 to 2025. The survey covered about 400 U.S. enterprise decision makers responsible for roughly $4 billion in AI spend.
- Menlo found enterprise AI use rose from 55% to 65% in a year, while average spending per AI-using enterprise grew 4.7x. Whittemore reads the gap as evidence that agents let companies scale spending with work and parallel activity, not employee headcount.
- Companies spent about 2.5 times what they budgeted for AI: planned spending growth was 1.9x, but actual average spending rose 4.7x. Whittemore says seat-based budgets failed to anticipate token-heavy agent use, leaving CFOs to treat AI as a new spending category.
- AI-native vendors dominated coding, finance and operations, and design spending, while incumbents retained most other enterprise categories. IT was the clearest incumbent stronghold: established vendors captured 91% of IT AI-app spending, compared with 9% for AI-native companies.
- Menlo found SaaS application growth slowed from 13% in 2025 to 11% in 2026, but most new AI spending came from new budgets rather than existing software budgets. Whittemore warns that agents using software without conventional interfaces could still pressure SaaS.
Models (3)
- Enterprise buyers shifted spending toward more capable, more expensive frontier models: their share rose from 35% to 63%, while mid-tier, small, and older models lost share. Menlo also reported labs cutting small-model prices by more than 80%, showing that cost competition and demand for capability coexist.
- Anthropic gained enterprise API share from 12% in 2023 to 55% this year, as OpenAI recovered to 31% and Google fell to 9%. Whittemore links Anthropic’s lead to Claude Opus models becoming a default for long-running agentic coding tasks.
- OpenAI’s Images 2.6 added short animated GIF generation, frame editing, speed controls, and reference-image input. OpenAI said users create 4 billion images per week, up from 3 billion a couple of months earlier, and the model is 50% faster, generating images in as little as six seconds.
Open Source (1)
- Open models accounted for 4% of enterprise AI spending but 19% of tokens, up from 11% of tokens the prior year. Kimi captured 61% of open-source spending; Whittemore argues token share may better indicate where adoption is heading than revenue share.
Coding (1)
- Revenue for Anthropic’s Claude Code and OpenAI’s Codex rose from $1 billion at the end of 2025 to $24 billion at the end of 2026. Other coding platforms, including Cursor, Cognition, Factory, and Lovable, also grew from $2.6 billion to $7.8 billion.
Agents (3)
- Agentic coding applications grew 7.7x, just behind financial-services AI applications at 8x, though coding spending was far larger. Menlo estimated $34 billion in coding-app spending against $800 million for financial services; customer success, sales, legal, and marketing also expanded.
- Claude’s personal-finance feature can connect to bank accounts through read-only Plaid access and analyze spending for budgeting, but it will not provide investment advice. Anthropic says users should rely on licensed professionals and regulated firms for major financial decisions.
- Meta’s Muse agent added voice and video conversations with animated avatars, selectable voices, and subtle expressions, using Meta’s live-voice models and real-time avatar technology. The feature lacks visual input for reading nonverbal cues and is available on mobile, web, and Mac.
Markets (3)
- AI stocks suffered their worst drawdown since 2020, with the Magnificent Seven losing a combined $1 trillion in market value. The S&P 500 fell 4.4% and the Nasdaq 6.4%, while semiconductor suppliers Micron and SanDisk dropped more sharply than major platform companies.
- Whittemore says the broad selloff looked like forced deleveraging after semiconductor losses, rather than a sudden change in company fundamentals. Reports said Walleye returned capital, Lone Pine had collapsed, and Millennium withdrew $1.5 billion in leveraged capital from two outside managers.
- Anthropic’s rumored pre-Thanksgiving IPO became less likely as markets fell: prediction-market odds dropped to 60%, and odds of a listing by year-end fell to 66%. The company’s reported $1.6 trillion secondary-market valuation drew investor skepticism, with one IPO investor arguing for roughly $1 trillion.
Safety (3)
- Anthropic’s first independent safety report from Meter said the pace of model improvement roughly doubled over the past year, largely because researchers use AI assistance. Meter reviewed three unreleased models trained since July; the latest was completed in September or October.
- Meter warned that AI-driven research could produce a sudden emergence of extreme capabilities if systems begin accelerating further AI development autonomously. Ryan Greenblatt called the report a major update toward ASI within one to two years; Nathan Lambert questioned whether existing benchmarks can measure that pathway.
- Whittemore says Meter’s report leaves gaps as an independent audit: Anthropic redacted evidence, and the report did not assess sandboxing or other cybersecurity safeguards. Critics also questioned Meter’s closeness to Anthropic and argued that an evaluation focused on AI research acceleration misses other safety concerns.
Why a Data Center Slowdown Benefits Big Tech • Nov 5
- Apple cut engineering employees’ daily AI spending caps from $300 to $200, with another reduction to $100 under consideration; non-engineers already face a $100 cap that could fall to $25. Apple’s policy conflicts with its push to use AI internally and sell AI features as a reason to upgrade.
- Apple’s previous $300 daily employee limit represented more than $6,000 a month, while Uber set a $1,500 monthly limit in June. Peter Steinberger argues that individual spending caps may stop making sense as workers use agents that run ongoing loops and maintain whole codebases.
Also discussed on this episode: (17)
Big Tech (2)
- OpenAI says ChatGPT now handles search requests at 20% of Google’s volume, although Adam Fry counts any query that triggers a web search. Sundar Pichai said AI Mode queries are slowing Google search revenue growth because they monetize less effectively.
- Adam Fry said ChatGPT ads have not hurt product usage, and that users’ limited backlash may encourage OpenAI to expand advertising. Nathaniel Whittemore argues that search growth could strengthen OpenAI’s advertising business.
Models (1)
- GPT 6.2 Astra and GPT 6.2 Sol appeared on Google Cloud’s backend, which Nathaniel Whittemore says usually signals an imminent release. The coming model comparison is whether GPT 6.2 can beat Opus 5.5.
Coding (2)
- Meta acquired Conductor, a startup that coordinates multiple coding agents running in parallel, to help build future coding products. Conductor founder Charlie Holtz teased a different approach to coding interfaces, while Meta’s MuseCode has drawn little attention.
- OpenAI agreed to acquire Pierre Computer Company, whose open-source tools help teams store codebases and track changes. Codex already uses Pierre’s tools, and the acquisition could support OpenAI’s ambition to add integrated services and compete with GitHub.
Agents (2)
- Meta’s and OpenAI’s coding acquisitions point to competition shifting toward agent products and the overall developer experience, rather than model quality alone. Nathaniel Whittemore says leading labs appear to be preparing for a market where frontier models become less differentiated.
- JPMorgan and Bank of America said they would block agents from accessing customer accounts, citing the risk of mistakes. Lead Bank and Increase Bank are testing agent-specific accounts, spending controls, emergency lockouts, and APIs through fintech partnerships.
Biology (1)
- Google’s drug-discovery spinoff Isomorphic Labs is reportedly raising $5 billion at a $50 billion valuation to expand its operations. The company builds on DeepMind’s AlphaFold work, and Demis Hassabis shifted to chairman partly to focus on scaling it.
Elections (1)
- Democrats’ election sweep put the Senate, House, and most state governments under Democratic control for two years, including Texas, where data-center construction has been central to the boom. Public resistance is strong: 43 of 44 data-center moratorium votes passed, and incoming Governor Gina Hinojosa is expected to be less supportive than Greg Abbott.
AI Infrastructure (5)
- Citrini Research argues that data-center construction faces compounding power, grid-connection, labor, supply, and permitting constraints, alongside turbine delays and rising input costs. New state policies may add municipal concessions, clean-energy requirements, ratepayer protections, and slower approvals, raising project costs without stopping construction outright.
- Nathaniel Whittemore argues that local leaders could allow data centers to proceed in exchange for transparency, full payment for infrastructure and power costs, environmental safeguards, and community benefits. Incoming Texas Senator James Tallarico has called for companies to pay for energy, recycle water, and obtain residents’ consent.
- Google, Meta, Amazon, and Microsoft all spent below their third-quarter capital-expenditure targets after construction delays. Microsoft attributed a $5 billion shortfall to a rented facility that was not ready, while Oracle warned it might invoke force majeure over a New Mexico project’s power-connection problems.
- Nathaniel Whittemore and market analysts argue that a slower build-out could help hyperscalers lower capital spending, protect margins, and preserve free cash flow while easing pressure on power, labor, and supply chains. Matt Farley says constrained data-center capacity could raise compute rents and make infrastructure scarcity a competitive moat.
- The Hill reported that hyperscalers are discussing a shared data-center framework with environmental groups, potentially giving Democrats enforceable community and environmental commitments while offering companies cover to moderate spending plans. Jessica Lesson says the market’s split reaction across hyperscalers, chips, and neoclouds suggests AI weakness need not pull the entire market down.
Markets (1)
- Investors reacted differently across the AI trade: the S&P 500 and Nasdaq rose while chip and neocloud stocks fell, and the Magnificent Seven gained $1 trillion in market value. Seema Shah warned that volatility would continue amid possible Iran-war escalation, a December shutdown, and Federal Reserve rate hikes.
Regulation (2)
- Progressives including Abdul Saeed and Yasemin Ansari have backed an AI pause, while Bernie Sanders has proposed jailing people who develop AGI. Nathaniel Whittemore considers a federal pause unlikely under a pro-AI president and a veto threat, and says Democrats remain divided between moderates and the Democratic Socialists of America.
- Nathaniel Whittemore expects more room for agreement on AI policy than the pause-versus-acceleration debate suggests, including possible liability for labs, safety-incident disclosures, and third-party audits. He argues that wider public debate is appropriate as model capabilities keep advancing.
Did the Midterms Destroy All Hope for Data Centers? | E2360 • Nov 6
- Apple reportedly cut daily AI budgets for engineers and may impose lower limits on other teams. Jason says high-value AI tools will likely move from flat-rate subscriptions toward usage-based corporate pricing, with companies reviewing who actually uses the tools.
Also discussed on this episode: (20)
Elections (2)
- Democrats won both chambers in the midterms, while voters in more than a dozen Ohio towns and in Kansas, Florida, and California backed restrictions on new data centers. Texas Governor-elect Gina Inohosa campaigned for a construction pause pending new regulations.
- The hosts say affordability, government corruption, and opposition to war drove the Democratic wins more than culture-war messaging. Jason expects many new Democratic officeholders to govern from the center, while the co-host says party leaders largely waited for Trump’s policies to damage his standing.
AI Infrastructure (5)
- Jason says Texas, Georgia, and Ohio together represent more than 40% of planned U.S. data center capacity. Bloomberg reported Microsoft was souring on neocloud providers, while Nscale lost a deal tied to a U.K. data center.
- Jason gives Donald Trump high marks for backing AI infrastructure, energy expansion, and growth, but says Trump made data centers a partisan wedge issue. Jason argues split government provides useful checks and balances after Republicans lost both chambers.
- Jason argues data centers can win local support by paying taxes, creating jobs, funding community benefits, and protecting water and electricity prices. He warns that slowing construction could trigger a recession lasting two to four years, and says operators must control noise, pollution, odors, and energy impacts.
- Jason says the Republican split over AI centers on job losses, wealth concentration, and fears that technology firms will leave workers in a permanent underclass. He connects those concerns to opposition from Steve Bannon, Nick Fuentes, Tucker Carlson, and Megyn Kelly.
- OpenAI pledged to cover the full cost of powering its data centers, solicit local input, publish construction plans, and avoid nondisclosure agreements with public officials. Jason says repeated, direct communication about utility bills, water use, taxes, and community impact is essential to building trust.
Markets (1)
- Jason says markets corrected 5% to 6% after the election, but sees the selloff as overblown if tariffs ease and the Iran war ends. He calls the decline a buying opportunity in companies including Nvidia, Amazon, Uber, Tesla, and SpaceX.
Regulation (2)
- Jason criticized Trump family meme coins soon after Trump took office, arguing that leaders responsible for fixing crypto regulation should not launch speculative tokens while doing so. He says government officials should keep personal trading at arm’s length from their public duties.
- Jason says taxing loans backed by appreciated assets could address wealthy people borrowing against holdings instead of selling them. He described taxing margin loans above a threshold, while noting the gap between ordinary income and long-term capital-gains rates.
Trade (1)
- Jason says Trump’s tariff goals were defensible but the rollout was chaotic, with public threats replacing a planned negotiating strategy. He argues leaders should hear directly from affected businesses; a clothing-company CEO described how tariffs were affecting his operations.
Models (2)
- Anthropic signed its first content licensing deal with the Associated Press for election coverage, with Claude expected to provide attributed, up-to-date polling information. Jason distinguishes licensing from unsettled questions about training on purchased content and using copyrighted material in AI outputs.
- Jason argues AI companies should share revenue with publishers and other rights holders rather than leave licensing disputes unresolved. He floated giving media businesses a portion of AI revenue, potentially through platform-wide arrangements that let publishers opt out.
Big Tech (2)
- Jason thinks Apple could let customers choose between cloud models and local models, using its own devices as an AI platform. The hosts also discussed an expensive touch-screen Mac configuration, with Jason questioning the value of touching a laptop display when an iPad can handle that use.
- The hosts debated whether technology executives would return to progressive messaging after Democratic victories. Jason says Democrats should invite business leaders into policy discussions, while warning that executives who shifted toward Trump may face distrust if they reverse course.
Agents (1)
- A host described using a Plaud pin and agent to route voice notes across Gmail, Calendar, Slack, Notion, Claude, and Grokbot, then build a product demo. Jason requested keyword-triggered actions and offline recording that syncs after a ski run, ideally through cellular connectivity.
Psychology (1)
- Jason says only a small share of casino gamblers tip, and he prefers putting dealers into a hand so they can share the outcome. He described a home poker game that sometimes includes the server in a bomb pot, giving the worker a chance at a large payout.
Society (1)
- The hosts traded Austin food opinions: one criticized Whataburger, while Jason said he would reconsider his view of P. Terry’s and praised Velvet Taco’s brisket and tikka masala tacos. The conversation framed these local chains as familiar parts of Austin life.
Media (2)
- Jason recommended Godzilla Minus One, praising its emotional connection to the creature and its postwar Japanese setting. The hosts discussed the follow-up, Godzilla Minus Zero, which moves the story into the 1950s and was playing in theaters that week.
- The co-host recommended the Korean monster film Hope, describing its long runtime, violent action, shifting story, and major twists. The same co-host praised season two of Apple TV+’s Dark Matter for treating travel between realities as a psychological problem rather than a superhero spectacle.
