Tech
Are AI tokens the new signing bonus or just a cost of doing business?
This week, a topic that has been boomeranging around Silicon Valley bounced into the spotlight: AI tokens as compensation. The idea is straightforward enough — rather than giving engineers only salary, equity, and bonuses, companies would also hand them a budget of AI tokens, the computational units that power tools like Claude, ChatGPT, and Gemini. Spend them to run agents, automate tasks, crank through code. The pitch is that access to more compute makes engineers more productive, and that more productive engineers are worth more. It’s an investment in the person holding them, is the idea.
Jensen Huang, the leather-jacket-wearing CEO of Nvidia, seemed to capture everyone’s imagination when he floated the notion at the company’s annual GTC event earlier this week that engineers should receive roughly half their base salary again — in tokens. His top people, by his math, might burn through $250,000 a year in AI compute. He called it a recruiting tool and predicted it would become standard across Silicon Valley.
It isn’t entirely clear where the idea was first, well, ideated. Tomasz Tunguz, a renowned VC in the Bay Area who runs Theory Ventures and focuses on AI, data, and SaaS startups — and whose writing on all things data has garnered a loyal following over the years — was talking about this in mid-February, writing that tech startups were already adding inference costs as a “fourth component to engineering compensation.” Using data from the compensation tracking site Levels.fyi, he put a top-quartile software engineer salary at $375,000. Add $100,000 in tokens and you’re at $475,000 fully loaded — meaning roughly one dollar in five is now compute.
That’s no coincidence. Agentic AI has been taking off, and the release of OpenClaw in late January accelerated the conversation considerably. OpenClaw is an open-source AI assistant designed to run continuously — churning through tasks, spawning sub-agents, and working through a to-do list while its user sleeps. It’s part of a broader shift toward “agentic” AI, meaning systems that don’t just respond to prompts but take sequences of actions autonomously over time.
The practical consequence is that token consumption has exploded. Where someone writing an essay might use 10,000 tokens in an afternoon, an engineer running a swarm of agents can blow through millions in a day — automatically, in the background, without typing a word.
By this weekend, the New York Times had put together a smart look at the so-called tokenmaxxing trend, finding that engineers at companies including Meta and OpenAI are competing on internal leaderboards that track token consumption. Generous token budgets are quietly becoming a standard job perk, the paper reported, the way dental insurance or free lunch once was. One Ericsson engineer in Stockholm told the Times he probably spends more on Claude than he earns in salary, though his employer picks up the tab.
Maybe tokens really will become the fourth pillar of engineering compensation. But engineers might want to hold the line before embracing this as a straightforward win. More tokens may mean more power in the short term, but given how fast things are evolving, it doesn’t necessarily mean more job security. For one thing, a large token allotment comes with large expectations. If a company is effectively funding a second engineer’s worth of compute on your behalf, the implicit pressure is to produce at twice the rate (or more).
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And there’s a muddier problem underneath that: at the point where a company’s token spend per employee approaches or exceeds that employee’s salary, the financial logic of headcount starts to look different to its finance team. If the compute is doing the work, the question of how many humans need to be coordinating it becomes harder to avoid.
Jamaal Glenn, an East Coast-based Stanford MBA and former VC turned financial services CFO, similarly points out that what may seem like a perk can be a clever way for companies to inflate the apparent value of a compensation package without increasing cash or equity — the things that actually compound for an employee over time. Your token budget doesn’t vest. It doesn’t appreciate. It doesn’t show up in your next offer negotiation the way a base salary or equity grant does. If companies successfully normalize tokens as pay, they may find it easier to keep cash comp flat while pointing to a growing compute allowance as evidence of investment in their people.
That’s a good deal for the company. Whether it’s a good deal for the engineer depends on questions most engineers don’t yet have enough information to answer.
Tech
Glean’s top line crosses $300M as AI budget cutting becomes its major selling point
Glean, a company often described as the Google for enterprise, said it has reached $300 million in annual recurring revenue (ARR), a three-fold increase from the $100 million milestone it reached just 15 months ago.
While many AI startups are growing at a blistering pace, Glean’s progress is particularly remarkable. After years of essentially being the only player in the category, the seven-year-old startup is accelerating its growth as tech giants enter the enterprise AI search market with rival products.
“The first four or five years of our existence, we had no competition,” Glean CEO Arvind Jain told TechCrunch. “Given how important search is to make AI work in the enterprise, every single company in the world wants to be in this space.”
Tech heavyweights building Glean-like tools include Google, Microsoft, OpenAI, Anthropic, Salesforce, and Atlassian.
Jain maintains there’s value in being a first mover in the space, but that it’s also equally important to offer a better product.
What Glean does better than its competition, according to Jain, comes down to the deep understanding that its AI tools have of customers’ business needs. Glean’s AI achieves this knowledge — a concept captured by the new, popular term “context graph” — by connecting to and learning from enterprises’ internal software systems.
Jain claims that Glean’s context graph also helps enterprises cut AI computing costs.
“If you connect your AI to Glean, it gives you all the information that you need to do your work, and that results in AI consuming far fewer tokens compared to if you unleash AI onto your systems directly,” Jain said. That’s because with Glean, AI ends up performing fewer operations, he added.
At a time when many companies are blowing through their AI budgets, those token cost savings have become a major selling point for the company.
“One of the things you know our customers really like about Glean is the fact that we can reduce your AI bill significantly,” he said.
The company, which was last valued at $7.2 billion when it raised a $150 million Series F last June, offers various pricing structures to its customers, which include Databricks, Reddit, Pinterest, and Samsung.
According to Jain, Glean offers both a consumption-based model, where clients pay per use, and a hybrid model that combines a fixed monthly fee for active users with separate usage fees for model consumption.
Glean is definitely not the first company to do this, but it’s worth pointing out that the company’s $300 million milestone cannot be fully described as traditional ARR, because a consumption model by definition doesn’t have a strictly recurring component.
Pure consumption pricing models depend on fluctuating user activity rather than predictable subscription renewals, therefore a portion of Glean’s top line is more accurately described as an annualized revenue run rate.
Glean did not immediately respond to a request for comment; this post will be updated if the company replies.
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Tech
Final 24 hours to save up to $410 on your TechCrunch Disrupt 2026 ticket
This is it. The countdown is almost over. You now have until tonight at 11:59 p.m. PT to lock in Early Bird savings of up to $410 for TechCrunch Disrupt 2026 before prices increase.
If Disrupt has been on your must-attend list, this is your final chance to secure the lowest available rates before the next price jump hits. Once the deadline passes, so do the savings.
Register now and join 10,000+ founders, investors, operators, and innovators at Moscone West in San Francisco from October 13–15 for three days packed with networking, startup discovery, and conversations shaping the future of tech. Bring a plus-one at 50%, or bring a group to get an up to 30% discount.
What makes Disrupt worth attending year after year
TechCrunch Disrupt is where startup momentum accelerates. The event brings together the people actively building, funding, and scaling what’s next across AI, fintech, SaaS, climate, cybersecurity, consumer tech, and beyond.
Attendees come to Disrupt for:
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With 300+ exhibiting startups, Startup Battlefield 200, curated networking experiences, and multiple stages of programming, Disrupt is built to help attendees make meaningful connections and real business progress.
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Hear directly from tech leaders shaping the industry
Every year, Disrupt brings together hundreds of influential voices across startups and venture capital. Past speakers have included leaders from the companies and firms shaping the future of AI, enterprise software, fintech, consumer tech, and more.
This year will deliver the same high-caliber experience, with 200+ sessions across six industry-focused stages, plus roundtables and breakouts covering scaling, AI, fintech, infrastructure, robotics, and emerging technologies. Explore the growing agenda to see the latest sessions and speaker announcements.
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Savings of up to $410 end tonight at 11:59 p.m. PT
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Tech
Today is the last day to apply to speak at TechCrunch Disrupt 2026
TechCrunch Disrupt 2026 returns October 13–15 to Moscone West in San Francisco — and applications to speak are open for just a few more hours.
We’re inviting founders, investors, operators, and technology experts to apply for a chance to take the stage at one of the most influential tech events of the year.
More than 10,000 startup and VC leaders will gather at Disrupt 2026 to explore what’s next in AI, scaling, fintech, infrastructure, robotics, and the future of innovation.
Applications close tonight at 11:59 p.m. PT. Apply now to share your expertise and help shape the conversations defining the tech industry.
Pick your session format
We’re looking for high-impact speakers to lead one of two session types:
Breakout Sessions: A 30-minute talk (up to 4 speakers, including a moderator) with a 20-minute audience Q&A. Capacity: 100 attendees.
Roundtables: A 30-minute speaker-led group discussion, designed for up to 40 participants. No slides or AV — just insight and conversation.
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Each application will be carefully reviewed by our editorial team. Finalists will be selected for the Audience Choice vote — where TechCrunch readers choose which sessions make it to the Disrupt Stage. Learn more about speaking on Disrupt’s Call for Content page.
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