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Why tech companies jumped the gun on AI layoffs

Welcome back. Databricks is making the case that openness may be one of AI’s strongest business models, as it builds an open stack for agents, models, and cross-cloud interoperability. Snap’s new Specs point to the next phase of spatial computing, but this is still an early-adopter product, not a mainstream must-buy.  And while AI keeps rattling the job market, new PwC research suggests the bigger returns are coming from companies that train and amplify workers, not those rushing to automate them away. Jason Hiner

IN TODAY’S NEWSLETTER

1. Study: AI worker training pays off more than layoffs

2. Snap Specs are a breakthrough step, not a must-buy

3. How Databricks turned openness into an AI moat

WORKFORCE

Why tech companies jumped the gun on AI layoffs

AI is undoubtedly flipping the job market on its head, but not in the way that you might expect. 

Recent research from PwC found that companies using AI to enhance and augment their employees are being rewarded more than those simply replacing large chunks of their workforce with automation. 

The research finds that AI use in roles that are "professionalized," or used by experts to act as a force multiplier for skills, are seeing greater headcount growth than "democratized" roles, or those in which AI makes a skill easier for a non-expert to perform. 

  • Additionally, AI-exposed companies are seeing faster headcount growth than those that are less exposed, 52% compared to 36%, as well as higher wage growth, 24% compared to 17%. 

  • And demand for AI skills is skyrocketing, with jobs requiring AI-specific skills growing eight times faster than jobs that don't. 

  • Still, the landscape is growing thornier for young workers. PwC said AI-exposed entry-level jobs are now seven times more likely to require "human-intensive" skills traditionally associated with senior-level employees, including strong judgment and leadership skills. These "seniorized" roles grew 35% since 2019, while entry-level jobs dropped off 10%. 

"The companies seeing the greatest returns on AI are using it to amplify human expertise, accelerate innovation and create entirely new sources of value," Joe Atkinson, global chief AI officer of PwC, said in the release. "As a result, they are pulling further ahead on productivity and growth than companies that focus primarily on automation." 

The fear around AI's ability to automate jobs is growing more feverish by the day. It's not helped by the fact that new studies about the tech's impact on the job market continue to provide conflicting reports. The forecasts are creating panic among workers, too, who largely use the technology in their jobs despite resenting it and even lying about their proficiency with AI.

The growing cacophony of contradictory data around AI's impact on jobs isn't the only thing creating a sense of dread about the labor market. There's been a layoff bloodbath in 2026, as some of the biggest proponents of AI, including Meta, Amazon, Microsoft, Block, and others, have slashed their workforces while plunging more cash into their AI transitions. One estimate reported this week found that 40,000 people were laid off in tech last month, the highest single-month total in two years, with AI the most cited reason. Though it's possible that AI was simply a popular scapegoat for layoffs that needed to happen anyway, these cuts set a precedent that job automation is a silver bullet for delivering strong returns to investors. However, PwC's data may indicate that these companies were a bit too trigger-happy in automating their staff away, and companies looking to follow in their footsteps may be better off creating ways for their employees to thrive, experiment, and enhance or expand what they already do.

Nat Rubio-Licht

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CONSUMER

Snap Specs are a breakthrough step, not a must-buy

I have covered smart glasses for years, tried the new Snap Specs, and have spoken to the CEO, Evan Spiegel. Here are my thoughts on where they fit in the market.

Let's start with their look. Compared to smart glasses like the Meta Ray-Bans, the Even Reality G2s, or any everyday glasses, there is no denying they look significantly more chunky. However, none of the glasses we just mentioned are true AR glasses, in which virtual objects are anchored to your physical environment. That's reserved for full-on headsets. 

So now let's compare the look of Specs to the Apple Vision Pro, the Meta Quest, or the Samsung Galaxy XR. The Specs are much less restrictive and more comfortable than those, especially considering there is no tethered battery pack or puck. 

Even the Meta Ray-Ban Displays, which do have waveguide displays that project color directly into the lens and weigh half as much as Specs, only offer one-dimensional graphics, giving you visual aids but not the same AR experiences that Specs promises, such as a 115-inch cinema screen or a 24-inch monitor placed into your environment.

Now, in terms of weight, at 132 to 136 grams, they are not meant to be worn all day, unlike smart glasses. Rather, they are supposed to be session-based: you use them for work, to watch a movie, or on a plane, and then you take them off. For context, other headsets like the Apple Vision Pro weigh closer to 600 grams and have the same utility. 

That leads me to my next point: price. At $2,195, they are obviously not meant for everyone, as those other headsets are not either. When I spoke to Evan about the price point, he gave me the same response I got from Samsung when I asked about their headset release last fall. This is meant for "early adopters," meaning developers building apps for it, or people who love the idea so much that they're willing to pay a premium.

So, should regular consumers pre-order them? Probably not, unless you are one of those people. In the future, I'm sure they will get lighter, look sleeker, and hopefully become cheaper, but what makes them impressive right now is that, in the current market for what they offer, they are leading the space, if they can deliver on their promises.

For instance, at the same event, Google launched the XREAL Aura glasses, which serve the exact same purpose as the Specs, but they also look a bit strange thanks to their birdbath display tech and bulky battery-and-processor attachment. Also, the price of these has not even been revealed.

Ultimately, it is really cool that Snap has crammed so much power into a footprint even close to that of normal glasses. Are we at a point for mass adoption? Absolutely not, but it's an important first step. For AI aficionados, this could also be a win for you, as there could be a future in which glasses provide AI assistance overlaid onto your actual environment with spatial awareness. That could be very powerful and useful. So for now, it's best to think of Snap Specs not as a more powerful pair of Meta Ray-Bans, but as an impressively smaller and less expensive version of Apple Vision Pro, and an interesting step toward the AR glasses of the future that could replace our smartphones.

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ENTERPRISE

How Databricks turned openness into an AI moat

If you're clinging to the idea that you can't build a great business on an open ecosystem in the AI era, then Databricks is rapidly making that line of thinking obsolete. 

The company started in 2013 as a platform built around the open-source engine for processing big data, Apache Spark, which the founders created at UC Berkeley. Today, it's a platform where companies organize their data and build AI on top of it. It's valued at $134 billion, and it's headed for a blockbuster IPO soon. Over 60% of Fortune 500 companies use the platform. 

What may be most impressive and surprising is that even as the company has grown its customer base and scaled its revenue to the moon, it has never shed its commitment to open systems. If anything, it's accelerating its commitment to openness. It used the Databricks Data + AI Summit this week to launch an open stack for agentic AI.

That included a flurry of developments:

  • OpenSharing: This is a platform that allows organizations to share AI components across clouds and platforms, including AI models, agents, AI skills, and AI applications. The goal is to help organizations avoid lock-in on proprietary platforms. OpenSharing is an OSS project hosted by Linux Foundation. 

  • Omnigent: This is a meta-harness, or a harness for harnesses. In other words, it's a powerful agent for managing, monitoring, and controlling your various agents. And Databricks announced that it's making Omnigent open-source. 

  • DBRX for open LLMs: DBRX is an open-source LLM from Databricks that it claims outperforms all existing open-source models at launch, a big claim. The goal is to raise the bar for what organizations can build without relying on proprietary AI. Because the full model is open, teams can fine-tune it or use it as a blueprint to build their own custom models.

Jonathan Frankle, chief AI scientist, told The Deep View, "[Databrick founders] Ali [Ghodsi], Matei [Zaharia], Reynold [Xi], and all of our leaders … have worked really hard over the past decade plus to just make sure things are open… It forces us to be on the ball every single day, and it makes our customers feel really comfortable being with us, because they know that they're not trapped here. I think it makes it easier to win business, and it forces us to work really hard to keep business."

In a question and answer session with the press at Databricks Data + AI Summit on Tuesday, Ghodsi said, "Our roots are open-source. Our roots are community. So we want to make sure that we can actually offer that we are independent, we are multi cloud, we work on top of all the clouds, we work on top of all the AI’s. We partner with all of those vendors and we work with open-source. So we think this is an important function in the market, and we hope to provide that."

The bigger question is whether Databricks' open ecosystem strategy is an outlier, or if the company is on to something. Could its approach have broader merit and point the way toward an emerging trend? With all of the big tech companies releasing their own agents and their own frameworks for managing agents, it's all getting very confusing and siloed. More interoperability and standard would allow organizations to take advantage of the best of breed in terms of models, harnesses, and other AI modules. That's especially valuable since new breakthroughs are happening at an incredible pace across the AI industry, and it's unlikely to slow down.

Jason Hiner, Editor-in-Chief

LINKS

  • Perplexity Brain: Now in Perplexity Computer, Brain is a continuously learning memory system that plugs every task into a context graph.

  • HappyOyster 1.0: An open-ended world model for real-time world creation and interaction.

  • Claude Code: The coding platform can now capture work progress as an artifact. 

  • Codex Record & Replay: Users can now teach Codex a recurring task, like filing an expense report or submitting a time-off request.

  • Meta: Research Scientist, Post-Training (Tech Leadership)

  • Google: Senior Research Scientist, Google Research

  • Palo Alto Networks: Principal Security Researcher (AI-Assisted Vulnerability Research)

  • Adobe: 2026 Intern - Research Scientist/Engineer

GAMES

Which image is real?

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POLL RESULTS

Should the public have a direct vote on major AI regulations?

Yes (62%)
No (20%)
I’m not sure (12%)
Other (6%)

The Deep View is written by Nat Rubio-Licht, Sabrina Ortiz, Jason Hiner, Faris Kojok and The Deep View crew. Please reply with any feedback.

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