04-18-2026Price:

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AI & TECH

ServiceNow CEO warns AI compute costs are unsustainable

Saturday, April 18, 2026 · from 2 podcasts
2 SOURCESNo PriorsAll-In
  • LLMs cost 10x more than SaaS platforms to run, making DIY AI a fiscal trap for enterprises.
  • AI labs must own power and land or face throttling by hyperscalers.
  • 2.2 billion digital agents will replace human roles, ending headcount-driven growth.

ServiceNow CEO Bill McDermott is sounding the alarm: enterprises are burning cash by rebuilding proven workflow platforms with raw LLMs. He calculates that running a simple application on a language model costs ten times more than using a deterministic system like ServiceNow. The 'SaaSpocalypse' narrative ignores that businesses demand reliability - they’ll forgive a human error, but not a software mistake.

McDermott argues that AI ‘thinks,’ but workflows ‘act.’ Trying to make the thinker do the acting leads to bloated GPU bills and fragile systems. One ServiceNow integration of security firm Armis took 20 days - a pace no model-only stack could match. Only 11% of Brazilian companies have moved beyond AI experimentation, showing how early we are in deployment.

"Rebuilding a workflow platform from scratch using a model requires massive GPU infrastructure and token costs that dwarf subscription fees."

- Bill McDermott, No Priors

The cost crisis isn’t just hitting customers - it’s threatening AI startups themselves. Chamath Palihapitiya warns that frontier labs like OpenAI and Anthropic are hitting a physical wall. Over 40% of contested data center builds are now being canceled. Maine has banned new data centers outright. Relying on Amazon or Google for compute is a strategic vulnerability; hyperscalers control 60% of all capacity and could throttle rivals at will.

Survival now means owning land, power, and cooling. Companies like Crusoe are bypassing the grid with modular nuclear and on-site gas. If AI labs can’t bring their own energy, their growth stalls - no matter how advanced their models. David Sacks notes Anthropic’s rapid release cadence has already made tools like Cursor obsolete within six months, but that pace is meaningless without infrastructure.

"Data centers have become the new temples of the wealthy, attracting fierce populist pushback."

- Chamath Palihapiti9ya, All-In with Chamath, Jason, Sacks & Friedberg

The winner won’t be the best model - it’ll be the platform that integrates them all. McDermott positions ServiceNow as the 'AI control tower,' using zero-copy data strategies to connect LLMs, hyperscalers, and legacy systems securely. With 90% of its own support cases now handled by agents, the future is clear: 2.2 billion digital workers are coming. Human hiring in support roles will collapse. The bar for human work rises - if an agent can do it better, automation wins.

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- Deep dive into what was said in the episodes

No Priors: Artificial Intelligence | Technology | Startups
No Priors: Artificial Intelligence | Technology | Startups

Scaling Global Organizations in the Age of AI with ServiceNow CEO Bill McDermott • Apr 17

  • Bill McDermott bought his first delicatessen business for $5,500, with the total cost rising to $7,000 with interest. He secured inventory on consignment by leveraging supplier relationships.
  • According to McDermott, for a simple application on ServiceNow's platform, it would cost 10 times more to try replicating it with a large language model. This factors in rebuilding costs, human capital, and GPU and token expenses.
  • McDermott argues enterprise buyers tolerate human error but will not forgive software for making mistakes, placing a premium on deterministic and context-aware workflow platforms over probabilistic LLMs.
  • ServiceNow processes more than 85 billion workflows and seven trillion transactions in-flight on its platform, representing major global brands.
  • McDermott states that cybercrime is the world's third-largest economy at $1 trillion per month, behind the US and China, prompting ServiceNow's expansion into security with Armis.
  • ServiceNow integrated its acquisition of security company Armis in 20 days, which McDermott cites as evidence of its engineering power to execute complex integrations quickly.
  • Within ServiceNow, AI agents now manage 90% of customer service cases, with only 10% requiring human intervention, shifting employee roles toward critical thinking and judgment.
  • McDermott says only about 11% of companies in Brazil have moved beyond the AI experimentation phase into mainstream deployment, illustrating the early-stage adoption curve globally.
  • Enterprise AI adoption varies by sector: public sector focuses on fraud prevention, healthcare on modernization, and financial services on headcount optimization and business model reinvention.
  • McDermott personally conducts 72 one-on-one conversations with quota-carrying sales representatives in a month to stay grounded in customer feedback and frontline insights.
Also from this episode: (1)

AI & Tech (1)

  • McDermott expects 2.2 billion AI agents to enter the workforce in the next few years, fundamentally changing headcount strategies. He foresees net new hiring dramatically decreasing as agents handle more work.
EnterpriseAgentsMacroModels
All-In with Chamath, Jason, Sacks & Friedberg
All-In with Chamath, Jason, Sacks & Friedberg

OpenAI's Identity Crisis, Datacenter Wars, Market Up on Iran News, Mamdani's First Tax, Swalwell Out • Apr 17

  • OpenAI and Anthropic both had roughly $30 billion in annual recurring revenue at the start of Q2, but Anthropic's growth rate is approximately 10x per year versus OpenAI's 3-4x. David Sacks argues this disparity could become insurmountable if OpenAI doesn't focus on enterprise coding.
  • Travis Kalanick states that in winner-take-all markets like AI, growth and scale create network effects around compute, token volume, and customer base. He argues that if Anthropic sustains a significantly faster growth rate than OpenAI at a similar size, it will win.
  • David Friedberg observes an unprecedented pace of innovation at Anthropic, with a rapid release cadence that has supplanted tools like Cursor and made its models dominant in his organization within six months.
  • Chamath Palihapitiya argues frontier AI labs like OpenAI and Anthropic face a critical compute constraint. He cites a contested $6 billion data center project and a Maine bill banning all data centers as evidence of rising NIMBY opposition fueled by negative public sentiment toward AI.
  • David Sacks asserts that AI doomer groups have astroturfed opposition to data centers, shifting arguments from existential risk to local issues like water usage. He notes Anthropic allied with these groups, a strategy that may backfire as the company now needs to build its own compute infrastructure.
  • Chamath Palihapitiya claims hyperscalers control 60% of all compute, creating game theory where they could kneecap frontier AI labs by throttling access. He argues this forces labs to build their own infrastructure to avoid a 'Friendster effect' of being outcompeted due to poor performance.
  • Jason Calacanis argues AI-driven productivity gains are real but concentrated in startups and savvy teams, not yet translating to broad bottom-line results at large, complex enterprises where change management is a significant barrier.
  • Travis Kalanick states current AI agents are not AGI and lack taste or novel problem-solving ability, requiring heavy human-in-the-loop guidance. He confirms this from personal experience building investing agents that make basic logical errors.
Also from this episode: (7)

Regulation (1)

  • New York City mayor Eric Adams is proposing a pied-à-terre tax of 3.9% annually on secondary homes valued over $5 million. David Sacks and Travis Kalanick argue the tax will crash demand for high-end real estate and stifle development by removing price-insensitive buyers.

Business (2)

  • David Sacks claims Austin demonstrates supply-side solutions to housing affordability, with rents declining for three consecutive years despite the city's population roughly doubling over the past decade. He argues Democratic cities and NIMBY policies prevent similar construction.
  • Allbirds stock rose 450% in a week after pivoting from sneakers to AI, which the hosts cite as peak bubble behavior. The company sold its brand assets for $39 million after raising $350 million in its 2021 IPO.

Media (1)

  • David Friedberg warns that public doxxing of wealthy individuals' homes, like Mayor Adams did with Ken Griffin's property, creates dangerous dog whistles. He cites the recent firebombing and shooting at Sam Altman's house as an example of real-world violence.

Corruption (1)

  • David Friedberg recounts that multiple sources warned him of serious allegations against Congressman Eric Swalwell in December, which were then revealed in a coordinated manner months later. He finds it striking that this knowledge was held back for strategic political timing.

Markets (2)

  • David Sacks interprets the stock market's resilience during the Iran conflict as pricing in a near-term resolution, citing presidential statements that military objectives are almost achieved. The S&P 500 recovered all losses from the war's start by that Tuesday.
  • Chamath Palihapitiya notes market indicators like the Shiller PE and Buffett Index are at all-time highs, suggesting a risk-off posture. He sees dispersion where only a handful of stocks are driving gains and awaits major IPOs like SpaceX to deleverage.
EnterpriseAI InfrastructureModelsRegulation

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