Tech Brew keeps business leaders up-to-date on the latest innovations, automation advances, policy shifts, and more, so they can make informed decisions about tech.

Tech Brew

Future of Work

Patrick Kulp

emergingtechbrew.com

 are a natural use case for coding. But how do developers actually feel about the technology that’s shaking up their jobs?

Stack Overflow asked 49,000 of them in its annual survey, and found some mixed opinions. Adoption was indeed growing; around 84% used or planned to use AI in their development process, compared to 76% last year. But positive sentiments were in decline (70% → 60% favorability), while mistrust in its accuracy was on the rise (31% distrusted it in 2024, whereas 46% were skeptical this year.)

Only about 31% of developers said they used agents at least once a month, but around 38% said they had no plans to start doing so. A little over half of those who use them said agents have had a positive effect on their productivity.

“We know more developers are using AI tools, but they’re not having exactly a great experience using those tools,” Erin Yepis, senior analyst of market research and insights at Stack Overflow, told Tech Brew. “There’s more developers that have the ability to try it, and maybe their expectations aren’t exactly where the reality lies.”

 As far as what’s holding back agentic adoption, developers identified accuracy and security or privacy concerns as their biggest problems with these more autonomous systems.

“One of the top frustrations that developers have is when the AI code isn’t quite right, they have to spend more time sort of debugging the thing that’s supposed to help them save time and get work done faster,” Yepis said.

 about declining employment in the tech industry, most developers (64%) said AI is not a threat to their jobs, though that number decreased slightly from 68% last year. Yepis said the survey might be showing that developers are becoming a bit more hesitant about the way AI coding tools are changing their workflows.

“There are just a lot more tools out there now, and I think [they’re] becoming a little bit more wary, as far as, ‘Maybe part of my job is going to change—what part of the job? What is it going to look like in three to five years?” Yepis said.

Developers responding to the survey seemed to overwhelmingly reject the term “

” to describe what they do; 72% said the loosely defined practice is not part of their development work. The term became popular earlier this year to describe a certain improvisational approach to AI coding, but the trend has also 

. For the Stack Overflow survey, the vibe coding question offered open-ended responses and drew many strong opinions, Yepis said.

“Whether it’s just that the term itself is off-putting or not, I thought that was interesting,” Yepis said. “There’s passionate responses when it comes to developers and their jobs.”

A set of hands on a keyboard with AI code overlaid

Most developers aren’t using agents, but many who do find them useful

But a Stack Overflow survey also found that positive sentiment toward the tech has dipped.

No, it’s not a TikTok aesthetic that involves dressing like a spy: AgentCore is a new toolkit from Amazon’s cloud arm designed to help companies build and deploy 

 in AI, companies everywhere are itching to 

 to full-fledged production can be daunting.

Amazon Bedrock AgentCore is the latest in a 

 of new products from tech giants aimed at easing that process. The platform has tools for managing memory, observability, helping agents access other digital services and the web at large, running generated code, and coordinating between agents.

Amazon announced AgentCore, along with a new agent marketplace and a 

, at its AWS Summit in Manhattan last week.

“There are a bunch of missing pieces that make it really difficult [to] move from [proofs of concept] that are sitting in laptops to agents in real-world production use cases,” Swami Sivasubramanian, VP of AWS Agentic AI, said on stage at the event.

The hype around agents seems as strong as ever at the moment, and enterprises have plenty of choices when it comes to these kinds of tools. 

, and other tech companies have their own agentic builders for customers looking to delegate to so-called “

Preethi CN, tech executive and advisor for agentic AI at AWS, told Tech Brew that one of the key things that sets AgentCore apart from this crowded field is flexibility. All of the component services are independent, CN said, and customers can “pick and choose” between them as needed. Companies are also not tied to Amazon’s own Nova foundation models; they can choose any of the catalog of models that Bedrock offers.

That kind of flexibility might be useful for a customer like Intuit, which has already built many of these agentic tools on its own through an internal tool called GenOS, according to Intuit SVP and chief data officer Ashok Srivastava. He said his team will explore these new AgentCore tools and decide if and where they might make sense for the new agents the financial software giant 

“When we built the agents that we launched a few weeks ago, a lot of these technologies weren’t available, and so we built our own,” Srivastava told Tech Brew. “As [cloud providers] build these capabilities out—if it makes sense—we can adopt them into our platform.”

Meanwhile, Amazon has also assembled an agent R&D lab in San Francisco built around its quasi-acquisition of agent startup Adept last year. The Amazon AGI SF Lab’s goal is to “develop new foundational capabilities for enabling useful AI agents that can take actions in the digital and physical worlds.”

Kelsey Szot, former co-founder and president of Adept, who’s now a member of the technical staff at the AGI SF Lab, said the lab is dedicated to research questions that lead to end results for AWS customers. The lab recently yielded a model called Nova Act, which powers agents to complete tasks within web browsers.

Szot said reliability has been the biggest obstacle for companies taking agents from experimentation to production—but that’s finally changing.

“Unfortunately, in the field, the last few years have seen a ton of demos and not a lot of real results of actual production deployments that are having business impact in the agent space,” Szot told Tech Brew. “It’s only now that we’re seeing the level of reliability that we need to actually make this possible.”

Amazon jumps onto the enterprise agent hype train

AWS’s new toolkit aims to help companies move past proof of concept.

In the high-stakes war for AI talent, you never know which way the wind will blow next.

 been in talks to acquire AI coding platform Windsurf when Google 

 to hire away the startup’s top talent and secure nonexclusive licensing rights to some of Windsurf’s assets. Then Cognition, the AI startup behind coding agent Devin, 

The episode is the latest in a string of reverse-acquihire-style deals that have become fashionable in the AI space. A Big Tech company will peel off top employees from a startup and license rights to some tech assets, while stopping short of an outright acquisition. Some examples include 

 These types of deals notably sidestep the traditional merger review process, which might have been especially attractive under the Biden administration’s 

 pointed out that these deals have another advantage that could explain why they’ve lived on into 

: expediency. In a breakneck AI development race where every week counts, absorbing startups this way allows for much quicker integration than a traditional acquisition.

“We note this deal mirrors the increasing[ly] popular partnership structure between large technology companies and some fast-rising GenAI startups that upgrades talent and provides access to key new GenAI products, without facing the scrutiny of equity ownership or acquisition,” Colin Sebastian, senior research analyst at financial firm Baird, wrote in a research note.

While Cognition ended up purchasing the remains of Windsurf, there were a couple of days when it seemed that remaining employees might be left in the shell of a company without the usual trappings of a startup exit.

The situation raises the question: If there’s a chance that a startup’s founders and other top employees might jump ship en masse, does that change the incentive math for tech pros considering working at one?

Rudy Torrijos, PitchBook’s director of industry research, told Tech Brew this particular deal was the result of a one-of-a-kind situation that’s not likely to become commonplace. However, it could lead venture capitalists and startup leadership to carefully consider internal structures and ensure that incentives are aligned for companies.

“This will likely prove to be a rare occurrence and was likely due to very unique circumstances,” Torrijos said in an email. “However, this event is likely to spur VCs and startup boards to review founder [and] CEO compensation or employment agreements and make sure leadership interests are aligned with investors and employees more explicitly and transparently.”

Putting structures in place that discourage founders from abandoning teams is especially important in times of major transformation in the tech industry, Torrijos said.

“In times of significant platform changes, like during the rise of the PC and the dot-com era, leadership matters most, suggesting that VCs and startup boards will likely add provisions, incentives, or disincentives for abrupt CEO departures,” Torrijos said.

 The episode also shows just how heated the battle over top AI talent has become among leading AI companies. At a time when Meta has been offering OpenAI researchers 

, big-name AI researchers are currently among the most in-demand resources in the AI race.

“Larger companies are desperate to hire anyone with raw talent or extraordinary experience,” Torrijos said. “Advanced technical talent has always been hard to find.”

Image of people shaking hands on a multicolored surface.

Windsurf drama shows how poaching is a new norm for AI deals

Google snagged execs from the AI coding platform before another startup bought the rest of Windsurf’s assets.

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Join Tech Brew and Deloitte to explore how robotics and physical AI are evolving, from humanoids to drones, and uncover the trends, innovations, and opportunities shaping the future of business and technology.


Robots on the Rise: How Physical AI Could Shape our Future

ChatGPT and its ilk seem to be taking on ever more work in modern offices.

 from Gallup finds that AI use at work has been accelerating. Nearly one in five workers now say they use it a few times a week, and 8% of respondents report daily AI interactions. Both those numbers have essentially doubled from Gallup’s first measure in 2023.

But not all workers use AI equally. The surge is mostly among white-collar workers, for one; production and frontline staffers have actually seen a slight dip in usage over the past couple of years (from 11% to 9%). Sectors with the highest concentrations of workers frequently turning to AI included the tech industry (50%), professional services (34%), and finance (32%).

 have shown, AI usage among employees has also continued to race ahead of employer planning and leadership on the tech. That can create security headaches and lead to a lack of consistent guidelines for workplaces.

While the number of organizations that have communicated a clear plan for integrating AI improved from 15% to 22% in the past year, “it’s still quite low,” according to Jim Harter, Gallup’s chief scientist of workplace management and well-being.

“[Organizations] need to be intentional about the planning process, about the training process,” Harter told Tech Brew. “They’ve got to have a plan about how it can best benefit their company and the jobs that they have, and how it can be a companion for efficiency’s sake in those jobs.”

 about AI’s potential to reshape the job market, many of these workers are also notably not worried about being replaced by the technology. Only 15% of workers expect robots, automation, or AI to threaten their jobs in the next five years, a figure that remains unchanged from 2023.

Worries were slightly more pronounced in certain industries, however: 21% of tech workers and retail employees and 20% of finance workers think their jobs could be at risk in the same time frame.

“I think people are sort of embracing it as more of a companion, which probably is the right way to think about it right now,” Harter said. “We don’t know what direction it’s going and how quickly…and it probably will be quickly.”

Perhaps tech workers are right not to be overly worried at the moment. Another 

 of tech C-suite leaders from Deloitte this week found that seven in 10 said they’re increasing headcount in tech as a response to generative AI. Around 45% said that GenAI prowess is urgently needed, and there are talent shortages and skill gaps around the technology.

The survey, which queried more than 620 senior tech leaders in the US this spring, found that AI might best augment in-demand skills like cybersecurity (56%), cloud orchestration (47%), and data science/analytics (39%).

“Businesses are rapidly pivoting from AI as experimental to an engine for transformation and innovation. In organizations where the C-suite leads the shift, more value can be realized,” Ranjit Bawa, Deloitte’s US chief strategy and technology officer, said in the report.

Workers in an office space with surrounded AI patterns.

AI use at work has almost doubled in the past year, Gallup finds

White-collar workers are using it more than frontline and production roles.

AI agents were the talk of the town as Silicon Valley leaders descended on the Big Apple for New York Tech Week. But some discussions still began with an 

The decentralized conference consisted of more than 1,000 events, from pickleball matches and movie nights to panels and rooftop soirées, scattered throughout the city. This year’s iteration drew more than 60,000 RSVPs from attendees, according to one organizer.

A sizable chunk of those events focused on the rise of autonomous generative agents, billed as the 

 have gone all-in on this concept with lofty predictions about digital workforces at companies of the future.

But separating the hype from the current reality—or even nailing down a firm definition of what agents 

—can be a tall order sometimes. Dan Balaceanu, chief product officer of enterprise conversational AI platform Druid, said buzz around the term has swallowed up some of the more precise terminology in the AI world.

“Somehow this agent name absorbed all the related terms,” Balaceanu told Tech Brew before he appeared on a panel on enterprise agents. “We don’t talk about virtual assistants anymore—we call them AI agents. We don’t talk about bots, we call them agents, we don’t talk about intents and skills or conversation flows, we talk about agents. In my opinion, maybe it’s not 100% accurate, but if we understand we are speaking about AI completing and helping humans, it’s fine.”

The slipperiness around what an agent is doesn’t seem to extend as much to software developers, who are already using agents every day, according to Zach Lloyd, founder and CEO of AI command line terminal startup Warp.

“The development stuff is in production and real and I’ve used it, whereas a lot of the other stuff, it’s more in demo-land or pitch-land, or even deck-land,” Lloyd told Tech Brew. “Every enterprise company has an agent product, but we’re not using any of them.”

Merrill Lutsky, co-founder and CEO of code review startup Graphite, said engineering might offer more clear-cut use cases for agents, whereas AI in other fields might be stymied by more varied processes or regulatory concerns.

“There’s a pretty clear drop-and-replace or drop-and-augment workflow there for AI to come in, versus…a combination of the models not being quite as powerful relative to humans yet in other domains, and that workflow not being as well-defined. And then also, obviously, you know, some regulatory concerns.”

 George Mathew, managing director at venture capital firm Insight Partners, said on stage at an SAP panel on agents and copilots that AI has had the biggest impact thus far on three fields: coding, legal, and accounting.

“There’s a good, bad, and ugly to all this,” Mathew said. “The three most disruptive moments in AI right now—code, legal and audit, accounting—all three of those are being completely reimagined at the entry level.”

But Jared Coyle, chief AI officer for SAP, said on the same panel that even when enterprise technology is available to fields like sales, there’s a big challenge getting organizations to break from tried-and-true existing practices.

There are also plenty of technical hurdles when it comes to governing how agents interact. “As it turns out, there’s a lot of engineering aspects that you don’t think about,” Coyle said. “There’s orchestration considerations. There’s a lot of just validating who has access to what, and how do you define that from a governance perspective, and all of those have to be considered.”

When AI does make a big business impact, however, you may not see it in headline news, according to Coyle.

“The best AI is boring,” Coyle said on stage. “We’ve done a quantitative evaluation of the 34,000 or so organizations that are actually using our AI. And what’s interesting is you can make [that] one conclusion from it…It’s not the ones that you see on the keynote stage. It’s the ones that you sit back and you go, ‘Oh, that’s actually the most impact that we’re seeing and the most uptake.’”

Illustration of AI agents connected to a grid system.

Everybody was talking about agents at NY Tech Week

Business leaders reflected on the challenges and potential impact of autonomous AI systems at work.

Two and half years after the release of ChatGPT, the pace of AI development 

. A constant stream of new enterprise AI tools promises to remake work as we know it across every industry. But how much is generative AI actually moving the needle for companies that use it?

A handful of new reports aims to quantify how much businesses are adopting AI—as well as what they’re getting out of the technology.

 in generative AI, these surveys show many companies are rushing to test them out. But the data on how much all this AI spending has yielded in terms of results is mixed.

 A PwC survey of more than 300 executives in April found that 52% have either broadly or fully adopted AI agents; 27% reported limited usage. The rest of the companies either hadn’t yet adopted agents or had no plans to do so.

The top use cases were customer service, sales and marketing, and IT and cybersecurity. Most companies surveyed said their budgets were increasing because of agentic AI.

But the report authors wrote that while agents provide “a meaningful boost in productivity, [the technology] stops short of transformation.”

 Economists at the National Bureau of Economic Research studied the effects of chatbots on work in Denmark in late 2023 and 2024, and found their impact somewhat underwhelming. They found that despite substantial investments from the companies they studied, the technology yielded less than 3% in productivity gains for workers, on average. While the study noted that randomized control trials showed more than 15% in time savings in some professions, those impacts were negated by other jobs and don’t translate fully into the real world.

“Our main finding is that AI chatbots have had minimal impact on adopters’ economic outcomes,” the authors wrote. “Our findings challenge narratives of imminent labor market transformations due to generative AI. While adoption has been rapid, with firms now heavily invested in unlocking the technological potential, the economic impacts remain small.”

An IBM survey of CEOs in May found that only a quarter of their AI projects “have delivered expected ROI over the last few years, and only 16% have scaled enterprise-wide.” A little over half said they were seeing business impacts beyond cost savings.

“CEOs are balancing the pressures of short-term ROI and investing in long-term innovation when it comes to adopting AI,” Mohamad Ali, SVP and head of IBM Consulting, said in the report.

 Despite some of these mixed results, Box’s 2025 state of AI enterprise report pointed to a growing divergence between companies that have adopted AI and those that haven’t in terms of productivity gains.

Box found that 47% of more than 1,300 IT leaders described themselves as in the “early stage” of AI maturity, and 39% as in the “developing” phase. Those that are further along are seeing much bigger productivity gains, according to Box, with “leading edge” businesses clocking 37% ROI, on average. The most common measures of AI success were time savings, employee productivity metrics, and cost reduction, according to the survey.

“AI-first organizations—with clear business objectives, thoughtful implementation, and robust governance—are gaining significant advantages that appear likely to compound over time,” the authors wrote.