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HR software provider Rippling this week unveiled AI Spend Console<\/a>, an anti-tokenmaxxing product that helps a company track and contain its AI spending. One of the most interesting features is that it maps how much individual employees, teams, and roles are spending and if they are genuinely more productive, or generally producing more AI slop.<\/p>\n The company promises the tool will show \u201cwhich engineers have high AI spend whose peers frequently ask them to redo work in code reviews,\u201d the company says in its blog post<\/a>.<\/p>\n The tool was born after Rippling went all in on tokenmaxxing at the start of the year \u2014 as so many did \u2014 only to discover employees were wildly burning cash. Chief Product Officer Matt MacInnis still recalls the executive team meeting in March when CFO Adam Swiecicki presented a number that shocked them.<\/p>\n Rippling was on track to burn 40% of its R&D headcount budget on AI tokens, meaning it was spending as much on tokens as 40% of all the compensation it paid employees in that unit. Millions of dollars. (The R&D org is home to engineering at most tech companies.)<\/p>\n Spending was growing by 80% month-over-month, and if that trend continued, the next year it would spend almost as much on AI tokens \u2014 90% \u2014 as it spent on its high-paid R&D unit employees.<\/p>\n \u201cWe were incredulous,\u201d MacInnis told TechCrunch. <\/p>\n Management immediately undertook an \u201curgent\u201d project to understand the spending and what they were getting for that money, he said. In fact, the launch ad<\/a> for this new product features Swiecicki sitting on a stool while employees are picking up wads of cash and dumping them into a paper shredder.<\/p>\n When Rippling conducted an analysis, it discovered facts like \u201croughly 10\u201315% of our employees were driving about 60% of total AI spend. One engineer was spending $50,000 a month,\u201d its blog post shared.<\/p>\n Rippling didn\u2019t want to stop AI usage, just rein it in \u2014 a lot. It started by negotiating a max spending cap with each of the tools its company used: Cursor, OpenAI, and Anthropic. It immediately found an obvious issue: Employees defaulted to using the most recent, and most expensive, frontier models for all tasks.<\/p>\n \u201cThe truth is that the inference providers, like Anthropic and OpenAI, have absolutely no incentives to help you control your spend. They have every incentive for it to be a runaway expense, and that\u2019s exactly what they do. They don\u2019t provide you with great usage insight, and they don\u2019t collaborate with one another,\u201d MacInnis said. <\/p>\n That was a common early-2026 problem. Now, eight months into the year, enterprises have figured out a couple of things. First, they know they need multiple models from multiple AI labs at various price points, including a frontier open weight option, perhaps of Chinese origin.<\/p>\n Rippling founder and CEO Parker Conrad noted<\/a> last month that when his company conducted its own benchmarks for its own internal uses, it discovered SpaceX\u2019s Grok was the all-around leader but that \u201cGLM 5.2 is 85% cheaper but [had] nearly identical performance\u201d to the frontier models. (SpaceX now owns Cursor, which offers access to Grok and dozens of other models.) Z.ai\u2019s GLM 5.2 has become a particular favorite Chinese model for coding tasks among tech companies these days. Databricks has also been championing it.<\/a><\/p>\n Second, enterprises now know they need an AI gateway that routes prompts to the best, most cost-effective model for the task. Rippling came to that conclusion too. So it built its own AI gateway that is also part of this product. MacInnis says it is possible for enterprises that already use another gateway to still use the AI Spend Console product, though if they want the features that govern spending, they would need to use Rippling\u2019s gateway. <\/p>\n AI Spend Console produces dashboards (once known as leaderboards in the tokenmaxxing days) that score attributes such as prompts per day combined with work output (lines of code\/pull requests) and spend.<\/p>\n With this tool in place, Rippling said it dropped its token spend from 40% of its headcount budget to about 15%. But it didn\u2019t curtail AI usage. The company spent a peak of 605 billion tokens the month the CFO issued his warning, MacInnis shared. In July, internal usage hit 600 billion tokens again, yet \u201cthe cost of July\u2019s token spend was 37% of the cost of April\u2019s token spend,\u201d he said.<\/p>\n \u201cThat\u2019s just because now we\u2019re routing to the more effective models,\u201d he said, joking that \u201cwe\u2019re not letting the sales team do grammar updates using Fable.\u201d<\/p>\n But technology solutions aren\u2019t enough, Rippling notes. The company found people using AI effectively and made them \u201cAI captains\u201d tasked with assisting the rest of the company. <\/p>\n Still, such efforts to use AI beyond engineering are a work in progress, MacInnis says, as software engineers have been the primary users so far. But Rippling is, for example, working on it for customer onboarding teams to automate some mailing data and data-reconciliation tasks. The dashboard will then measure productivity in terms of onboarding more customers.<\/p>\n \u201cWe have to be able to link token consumption in G&A functions and in customer-facing functions back to productivity. If we can\u2019t do that, all bets are off on any of this stuff being available to the broader employee base,\u201d MacInnis says.<\/p>\n So, if Rippling is an example, tokenmaxxing may have swung so far the other direction that employee AI access may no longer be like Slack or email. If the company can\u2019t measure productivity, then all employees might not have access.<\/p>\n As for the product, AI Spend Console is included for Rippling\u2019s HR subscribers, though there are additional AI usage-based costs. It can also be purchased as a stand-alone product and integrated with another HR system of record, MacInnis says.<\/p>\n<\/div>\n When you purchase through links in our articles, we may earn a small commission<\/a>. This doesn\u2019t affect our editorial independence.<\/em><\/p>\n