{"id":5746,"date":"2026-08-22T11:07:58","date_gmt":"2026-08-22T11:07:58","guid":{"rendered":"https:\/\/crosscountrymovingteams.com\/?p=5746"},"modified":"2026-08-22T11:07:58","modified_gmt":"2026-08-22T11:07:58","slug":"this-ceo-was-out-to-dinner-when-he-caught-his-ai-agent-wasting-1000-in-tokens-he-says-insecurity-is-a-bigger-problem","status":"publish","type":"post","link":"https:\/\/crosscountrymovingteams.com\/?p=5746","title":{"rendered":"This CEO was out to dinner when he caught his AI agent wasting $1,000 in tokens. He says \u2018insecurity\u2019 is a bigger problem"},"content":{"rendered":"
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Jenkins is the CEO of Maxio, a private-equity-backed software company headquartered in Atlanta that\u2019s on a path toward $100 million in annual revenue over the next couple of years. He\u2019s also, by his own admission, near the top of his company\u2019s internal AI spending leaderboard \u2014 an odd place for the chief executive to land. \u201cA thousand is not that much, I would say, but for one weekend, it\u2019s pretty annoying,\u201d he said in an interview with Fortune<\/em>. Describing his agent as \u201ccooking away,\u201d he described his response as \u201cWow, I just got here quickly.\u201d<\/p>\n

Read more Chief Justice John Roberts allows Trump\u2019s ballroom crews to keep working 20-hour days<\/a><\/p>\n

The episode has become something of a parable inside his company \u2014 and inside corporate America more broadly \u2014 for how quickly \u201cagentic\u201d AI tools can consume money without anyone quite noticing until the bill lands. But Jenkins said the surprise invoice isn\u2019t what\u2019s keeping him up at night. The deeper problem is something messier and more human: his own employees\u2019 \u201cinsecurity\u201d about being outpaced by the technology \u2014\u00a0and by him.<\/p>\n

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How a weekend turned into a $1,000 lesson<\/h2>\n

Jenkins, a self-described technical CEO who builds his own agents and automations, said he can write code from his phone using Claude even while away from his desk \u2014 which is how he ended up debugging and iterating on a project at dinner. The token wallet he\u2019d set up to fund those sessions was configured to auto-refill by $1,000 every time it ran dry, silently recharging his card without requiring a second thought \u2014 until he saw the total.<\/p>\n

\u201cI don\u2019t have governors where a lot of my staff hits limits, and they have to ask for approval,\u201d Jenkins said, describing his own unlimited internal budget as both a perk and a liability. \u201cSo I started leaning in and going, \u2018What does this look like?’\u201d<\/p>\n

What he found, he said, is that a lot of the waste comes down to model selection and runaway conversational drift \u2014 an AI system wandering a user down paths they never intended to go. \u201cA lot of times it\u2019s the agent\u2019s own mistakes that\u2019s burning your money,\u201d Jenkins said. \u201cYou kind of find yourself just chatting, and [things] getting away from you.\u201d Casting his mind back to his dialogues with his bots, he said, \u201cYou\u2019re like, \u2018Yeah, yeah, I like it, more of that, more of that.\u2019 All of a sudden you end up in who-knows-where, and you\u2019re like, \u2018No, I don\u2019t want that at all.\u2019 So some of that money is just wasted because it took you there.\u201d<\/p>\n

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His experience mirrors a pattern now well documented across the industry. Gartner has estimated that agentic AI models can require between 5x and 30x more tokens per task than a standard chatbot exchange, and a WitnessAI survey found that 68% of U.S. companies say at least some of their AI initiatives ran over budget in the past year, with a third saying overruns happen \u201cmostly or always.\u201d George Sivulka, CEO of Hebbia, put it memorably when he wrote that using agents means \u201cyou just hired a million bad employees.\u201d<\/p>\n

Uber reportedly burned through its entire 2026 AI coding budget within four months, and Amazon reportedly spent $500 million on AI in a single month after rolling out access without usage caps. That was the month \u201ctokenmaxxing\u201d died. Jenkins\u2019s $1,000 weekend is a rounding error by comparison \u2014 but the point is, that\u2019s real money. \u201cThere\u2019s no refund button. There\u2019s no dispute button in Claude,\u201d Jenkins said, adding that maybe there should be. <\/p>\n

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Tricks of the trade<\/h2>\n

After the dinner incident, Jenkins said he looked for ways to cut his own token burn \u2014 much of it, by his account, learned from AI-optimization tips circulating on TikTok rather than from his own engineering team. He started routing different tasks to different models based on complexity: lighter models like Claude\u2019s Haiku for basic math, mid-tier models for routine coding, and reserving the most expensive, highest-reasoning models for genuine strategic planning.<\/p>\n

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He also adopted what he called orchestration layers \u2014 third-party tools, often distributed as free GitHub repositories, designed to compress AI output and cut wasted tokens. One, which he called \u201cCaveman mode,\u201d forces an AI assistant to reply in short, blunt sentences instead of long, elaborated answers, which Jenkins estimated cuts token use by 70%. Another mode he described, \u201cgrunt mode,\u201d compresses replies to a word or two: \u201cIt\u2019s very trite.\u201d<\/p>\n

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He named other tools, including \u201cSuperpowers\u201d and \u201cPonytail,\u201d as part of the same underground ecosystem of cost-saving hacks.<\/p>\n

The catch, Jenkins said, is that none of it is accessible to a typical employee. \u201cThese are nerdy things,\u201d he said. \u201cDo we need sales leaders and service leaders and marketers finding this stuff?\u201d That gap\u2014between what power users like himself know and what the rest of the workforce can access \u2014is where he says the real organizational risk begins.<\/p>\n

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Why he warns insecurity, not cost, is the bigger threat<\/h2>\n

Asked to rank the problems he\u2019s encountered rolling out AI across his several hundred employees, Jenkins didn\u2019t lead with cost. He named three forces he says he has to actively manage: inefficiency, inequality, and \u2014 the one he returned to repeatedly \u2014 insecurity.<\/p>\n

Read more Retired racer Jimmie Johnson credits his multimillion-dollar success to shining his shoes and arriving 10 minutes early: \u2018Small things matter\u2019<\/a><\/p>\n

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Jenkins explained that he\u2019s proud that everyone\u2019s becoming a builder with vibe-coding permissions in his company, but it\u2019s disruptive in a very human sense. <\/p>\n

\u201c[Token overspend] is really not the problem, but it could easily be the excuse,\u201d Jenkins said. He described building tools and automations inside his own leadership team\u2019s departments, unprompted, simply because he\u2019d learned how \u2014 and watching the reaction turn uneasy. \u201cOne of them came to me and said, \u2018This put me on edge. I should be coming to you with these things. I\u2019ve got to catch up. I feel so behind.\u201d <\/p>\n

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Jenkins said the dynamic repeated itself down through multiple layers of management: \u201cAm I doing my job? Am I keeping up? Will this replace my job? Will this replace my team members?\u201d<\/p>\n

He also pointed to a version of the same anxiety playing out at the departmental level, rooted in unequal access to tools. His company initially rolled out ChatGPT company-wide, then began licensing the pricier Claude for a smaller group of roughly 50 employees concentrated in sales and marketing \u2014 prompting pushback from teams left out. \u201cPeople were like, wait a minute, why don\u2019t I have Claude? Why do they get that and we don\u2019t get that?\u201d he said. \u201cThat\u2019s an inequality.\u201d<\/p>\n

Jenkins argues that the anxiety is ultimately more corrosive to a company\u2019s culture than any single runaway invoice, because it shapes whether employees engage with the tools at all \u2014 or quietly resist them out of fear.<\/p>\n

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Building an org chart for humans and agents<\/h2>\n

Jenkins said his company\u2019s response has been structural. His entire executive leadership team went through a formal org-design exercise in which each executive mapped out their department not just in terms of the people who report to them, but the AI agents those people now manage directly. The result, he said, is a literal hybrid org chart \u2014 human names and agent functions layered together \u2014 that the company treats as a living management document.<\/p>\n

He\u2019s also expanded his DevOps organization specifically to govern the growing number of employee-built, informally coded internal tools \u2014 what he and others in the industry call \u201cvibe-coded\u201d software \u2014 that have become load-bearing parts of the business despite originating as side projects. \u201cIt can\u2019t just be with Tim that vibe-coded it on the weekend,\u201d Jenkins said, citing continuity risk if the employee who built a critical internal tool leaves or gets sick, along with unresolved questions about security and scalability.<\/p>\n

The bigger financial story, in his telling, isn\u2019t the occasional four-figure token overrun but a shift in his company\u2019s underlying labor math. Jenkins said his company\u2019s headcount has stopped scaling with revenue the way it once did, driving up its ratio of annual recurring revenue per employee \u2014 a metric he calls the clearest signal of what AI is actually doing to his cost structure, as opposed to the more visible but comparatively minor token bill.<\/p>\n

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\u201cI\u2019m not arguing that we want to reduce a whole bunch of headcount because of AI, but we should not be growing the headcount at the same rate that we were before,\u201d Jenkins said. \u201cThat\u2019s a big change in our business, and it\u2019s all attributed to AI.\u201d He also agreed that the occasional ping of $1,000 token burn at dinner is like a tax you pay \u2014\u00a0an AI agent colleague just got the wrong idea of what the job was.<\/p>\n

Jenkins said he doesn\u2019t see any of that as a reason to pull back. \u201cRight now there\u2019s so much good that outweighs a lot of this,\u201d he said, arguing that the efficiency gains from AI adoption are large enough that occasional waste, hallucination-driven detours, and even four-figure surprise bills are simply the cost of getting there. His head of engineering, when first told about Jenkins\u2019s token-saving tricks, waved them off, telling him the company was \u201cnot at the level of we\u2019re spending more on A.I. than [on] people, because there are examples of that out there. We\u2019re nowhere close to that.\u201d Jenkins said he didn\u2019t disagree \u2014 but he\u2019s convinced that day is coming. \u201cIt probably will be a thing.\u201d<\/p>\n

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For this story,\u00a0<\/em>Fortune\u00a0journalists used generative AI as a research tool. An editor verified the accuracy of the information before publishing.<\/em><\/p>\n

Read more YouTube offers creators millions to not work with Netflix<\/a><\/p>\n

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