Tech
Coders are refusing to work without AI — and that could come back to bite them
In 2026, you cannot pry AI coding tools out of developers’ vise grip, researchers have discovered.
But while AI is undoubtedly helping coders produce code faster, it may not be producing better code, other researchers warn. And that could cause problems down the road for them.
Specifically, in February 2026, respected AI research lab METR published a surprising revelation: Most developers won’t work, even on a limited number of tasks, without AI anymore.
METR had hoped to provide an update to some groundbreaking research published a few months earlier, in 2025, on AI coding productivity. In it, researchers measured how much time open source developers took to do tasks by hand versus with AI.
While developers in that study reported that AI was making them more productive, they were shocked to learn it actually slowed them down. Sure, it generated code faster, but then they spent extra time finding and fixing errors, steering the AI and waiting on it to complete tasks.
When METR set out to repeat the experiment to measure advances in AI and coder proficiency, they couldn’t.
Devs weren’t willing to participate “because they do not wish to work without AI” even just for the study, the researchers confessed.
Instead, METR published a survey in May that allowed technical employees to self-report their AI productivity gains. Not surprisingly, they perceived that AI made them twice as valuable to their organizations.
But recent headlines about the wild expense of so-called tokenmaxxing, coupled with a smattering of recent research, make such self-perceptions dubious.
Tokenmaxxing, or using the number of tokens a person uses as a proxy for productivity with AI, has been the trend of 2026 so far. And it may already be over.
Amazon shut down its internal token-tracking leaderboard called Kirorank after employees were gaming it by using AI agents excessively, and running up costs, the Financial Times reported this week. The employees proved that AI use does not automatically translate to increased productivity.
Uber blew through its 2026 AI budget within the first four months of the year, The Information reported. COO Andrew Macdonald recently said on a podcast that such spending hadn’t led to a measurable increase in projects or productivity.
AI-generated code also doesn’t necessarily reduce ongoing code maintenance needs and may even increase it, programmer and author James Shore elegantly argued in a blog post that went viral on Hacker News.
“You write code twice as quick now? Better hope you’ve halved your maintenance costs,” he wrote. “Otherwise, you’re screwed. You’re trading a temporary speed boost for permanent indenture.”
There’s other evidence that AI can increase code maintenance woes.
A viral tweet from Aiswarya Sankar, founder and CEO of reliability engineering agent startup Entelligence AI, proclaims that companies are spending 44% of their tokens on bug fixes that their AI generated. Meanwhile, code-reviewing tool company CodeRabbit says it analyzed open source pull requests and found that AI produced 1.7x more problems than human code.
Those are, admittedly, self-serving stats from those trying to sell AI code reviewing tools.
Yet independent researchers have also found such issues. Researchers from the respected Singapore Management University published a report in April warning that “AI-generated code can introduce long-term maintenance costs into real software projects.”
Given that programmers love their AI assistants, what’s the solution?
Well, those who want to sell you AI coding agents say devs can just use AI coding agents to do the bone-wearying tasks of fixing code as fast as AI spits it out. That’s what Cognition founder and CEO Scott Wu —the maker of AI coding agent Devin — suggests.
But even he admits that, while Devin can work independently, he’d currently rate its skill between a junior and mid-level programmer, depending on the task. This is not a hand-it-off and forget it solution.
The SMU researchers suggest a more human approach. Programmers should know what tasks AI does and doesn’t do well as deeply as they know their favorite coding languages. They need strong quality assurance systems designed for AI and they are stuck with carefully reviewing the AI’s work as if it were a junior dev.
Meanwhile, the researchers say (and Wu agrees), humans should still be doing the big-picture work like software architecture and security design.
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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:
- Direct access to investors, founders, and operators making moves now.
- Conversations that lead to partnerships, funding, and hires.
- Tactical insights from leaders scaling breakout companies.
- An inside look at emerging technologies before they hit the mainstream.
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.
Built for the people shaping what’s next
Disrupt is designed for founders raising capital, investors sourcing opportunities, operators scaling companies, and innovators looking for an edge. Whether you’re launching your next startup, growing your network, or tracking the future of technology, Disrupt puts you in the room with the people driving the industry forward.
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.
Speakers include:
Savings of up to $410 end tonight at 11:59 p.m. PT
Early Bird savings of up to $410 end tonight at 11:59 p.m. PT. After that, ticket prices increase.
Register now to secure your TechCrunch Disrupt 2026 pass at a low rate before the deadline expires. Bringing more than just you? Save 50% on a second ticket, or up to 30% on community passes.
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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.
How the application process works
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.
Lead the conversation at Disrupt 2026
If you have actionable insights, real-world experience, and a desire to contribute meaningfully to the tech ecosystem, we want to hear from you. Submit your application before today’s deadline.
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