The AI Daily Brief: Artificial Intelligence News and Analysis
Towards AI That Can Actually Interact
12 May 2026
Transcript generated automatically by AI and may contain errors.
Chapter 1: What is the main topic discussed in this episode?
Today on the AI Daily Brief, a new approach to AI called interaction models. Before that in the headlines, OpenAI's big consulting arm is official. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. All right, friends, quick announcements before we dive in. First of all, thank you to today's sponsors, KPMG, Granola, Scrunch, and Section.
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Chapter 2: How is OpenAI's new consulting arm structured and what are its goals?
This has happened almost totally organically because of listeners sharing with their friends and colleagues, but I think it's time to pour some gas on that particular fire. I am now hiring for what I'm calling a growth engineer. And the goal is to build stuff to make it easier for important parts of the AI Daily Brief to get to the audiences that they could be helping.
This is a role for someone who is creative, dynamic, highly self-directed, and lives inside Cloud Code or Codex. You can find the role at We kick off today with a story that is a follow-up to reports from last week. OpenAI is indeed launching a consulting company, and now it is official. The business will operate as a separate company called the OpenAI Deployment Company, or DeployCo for short.
This is basically a forward-deployed engineer shop that will pair developers with some of OpenAI's most important clients to help them on theoretically real deep AI and agentic transformation. Now, like the Anthropic venture that was announced last week, DeployCo is structured as a joint venture, in this case with 19 partners across consulting, private equity, and finance.
Chapter 3: What challenges do enterprises face in adopting AI technologies?
The initial investment was $4 billion at a pre-money valuation of $10 billion, with TPG as the lead investor, Advent International, Bain Capital, and Brookfield as also co-lead founding partners.
Now, one of the things of note here is that word on the street is that a big part of the motivation for the firms who are investing in this is to get first access to this set of engineers for their portfolio companies. In other words, this was effectively a buy-in cost to skipping the line when it comes to getting help on AI transformation.
Of the partners announced, it looks like Goldman Sachs is the only one to back both DeployCo and the Anthropic effort, which is as yet unnamed. The guts of DeployCo are going to be built around an acquisition, specifically engineering firm Tomorrow, which will give DeployCo right out of the gate about 150 staff who have experience in deploying AI solutions.
At this point, there is basically no way to grow fast enough to meet this demand other than acquisition, so I would expect a lot more M&A soon. Even though this was a big part of the discourse last week, there was a surprising amount of conversation about this.
Most of it was just a reaffirmation of what has finally started to become conventional wisdom, which is that it doesn't matter how powerful the models are, they're going to crash headlong into institutional inertia.
And for enterprises to close the capability overhang and actually get the full value from these models, it is going to involve meaningful support structures being built around them, both inside and outside.
Now, one funny strand in the conversation that I've seen is a lot of folks running smaller versions of these agencies, trying to sort of puff out their chest and make it clear that they still have a market, because no matter how well-resourced the efforts from OpenAI and Anthropic are, there's a massive long tail of people that need support too.
And to them, I would just like to say, guys, don't worry. No one thinks that because OpenAI and Anthropic are in the game, somehow they are going to be able to consume the sheer tonnage of transformation support that is going to be needed over the coming decades to get these companies onboarded onto AI. Next up, we have an interesting market sort of sub-story.
You might have seen posts like this one from the Kobayashi letter, suggesting something about Anthropic or OpenAI's market-implied pre-IPO valuation.
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Chapter 4: What is the significance of interaction models in AI?
Any third party claiming to sell Anthropic shares to the general public is likely either engaged in fraud or offering an investment that may have no value due to our transfer restrictions.
The Monday edition was a list of firms known to be offering access to the stock, with Anthropic specifically saying that any interest in Anthropic stock offered by these firms is void and will not be recognized on our books or records. In a rare show of solidarity, OpenAI sent a similar message to the market in the form of a blog post.
They restated their position that unauthorized transfers are legally void without approval, making some vehicles claiming to have exposure to the stock worth zero. Lawyer Gabriel Shapiro thinks people trading these gray markets could have a huge problem.
He wrote, There is an active secondary market purportedly in Anthropic stock or derivatives, including on fairly reputable or at least well-known platforms like Forge. Anthropic is calling them out specifically by name and essentially saying 100% of these are illegal.
Now Shapiro notes that the legal status is far from clear, but attempting to void transactions could trigger an avalanche of lawsuits against Anthropic and the marketplaces purporting to sell stock.
Giving an indication of why they want this activity to be nipped in the bud, Anthropic's notice triggered a quote-unquote massive crash, cutting the price of Anthropic on these markets in half yesterday. Now, what's important about this story is that this is not just doing crypto market things.
What underlies this is what has been a growing dynamic in private markets over the last, honestly, decade and a half, ever since the global financial crisis and the beginning of Zerp era policies. Private companies have been waiting longer than ever to IPO because of basically just unlimited private capital.
The dynamic has gotten to the point where some startups are even targeting the secondary market as their exit rather than aiming for an acquisition or an IPO. All of this comes down to demand from both long-tail accredited and retail investors who are structurally blocked out of investing in early stage companies.
If companies never go public or go public at enormously high valuations, it significantly cuts down the ability of retail investors to participate in the upside of company creation. Now, the issue is that a lot of the way that secondary markets happen completely negates the disclosure rules of markets in general.
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Chapter 5: How does Thinking Machines Lab's approach differ from traditional AI models?
And that's in the best case scenario. Casey Craig discussed some of the vehicles being traded in crypto markets that claim to represent anthropic shares and wrote, You are approximately anthropic adjacent at best. Now, to be fair to these market participants, most people at this stage who are trading these assets know that they're trading IOUs.
The bigger issue comes when naive investors think they actually own anthropic stock, and that turns out not to be the case. Ultimately, it seems like this is actually a bigger issue than just this one instance, with a potential reckoning on the way. Brian Norgard writes, Natasha Mascarenhas writes, It's hard to overstate the amount of fake SPVs circulating in the market right now.
They've always been a controversial financing tool, with Anduril, OpenAI, Anthropic, etc. fighting them for years. If companies crack down against them as promised, people are in for a rude awakening after lockups expire.
Still, Kingsley Advani thinks that Anthropic has limited options here, posting a chart with the dozens of registered SPVs holding Anthropic shares and saying, "'Anthropic unlikely to void half their investors.'" Moving over to politics now, administration officials have walked back calls for an FDA-like approach to AI safety.
Last week, National Economic Council Chairman Kevin Hassett said that the White House was considering an executive order to respond to mythos-level models. He said the new policy would put AI models through a process where they're proven safe, just like an FDA drug. This led to a massive industry reaction, with many fearing a burdensome regulatory structure that would slow innovation to a crawl.
Over the weekend, former AI czar David Sachs said that he'd spoken with Hassett and the FDA comparison wasn't particularly apt. Commented Sachs, I don't think any senior official supports it.
During an interview with CNBC on Monday, Hassett confirmed that an FDA-type organization is not in the cards, commenting, At the White House, nobody has an idea that we should do something like bring in a giant new bureaucracy to approve AIs.
He said that the current approach is simply administration officials working directly with the AI labs to, quote, in his words, make sure that the models before they're released to the public aren't going to cause an extreme amount of harm. Hassett noted that this all-of-government, all-of-private-sector approach is working well, and it's uncertain that an executive order will even be necessary.
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Chapter 6: What examples of capabilities do interaction models demonstrate?
Commenting on how much discussion his off-the-cuff comparison had generated, he added, I probably shouldn't have called it the FDA. Lastly today, President Trump is assembling a tech envoy for his trip to China later this week. The White House said that Elon Musk, Apple CEO Tim Cook, and Meta President Dina Powell McCormick will join the president's delegation.
The group also includes numerous finance, semiconductor, aerospace, and agriculture executives. U.S. officials have said they intend to finalize trade negotiations with China during the meeting, including establishing a bilateral board of trade. A senior official said the executives are from companies with significant Chinese exposure and represent sectors to be included on the trade agenda.
Notably absent is Jensen Huang. Last week, the NVIDIA CEO said he would join the envoy if invited, but it appears an invite was not extended by the White House. Now, there's a lot of different ways to look at this. Huang has traveled extensively with the president over the past year, joining trips to the Middle East and the UK.
There are also apparently executives from Micron and Qualcomm attending, so it's clear that semiconductors will at least in some way be discussed. However, Huang's absence could mean that the White House is sending a signal that NVIDIA's AI chips are off the table as part of the trade talks.
While the White House signaled in December that older H200 GPUs would be approved for export to China, those plans have stalled, and so far zero export licenses have been approved by the Commerce Department. We'll see later this week how much the absence of Jensen is an actual strategic move. For now though, that is going to do it for today's headlines. Next up, the main episode.
One of the most important AI questions right now isn't who's using AI, it's who's using it well. KPMG and the University of Texas at Austin just analyzed 1.4 million real workplace AI interactions and found something surprising. The highest impact users aren't better prompt engineers, they treat AI like a reasoning partner.
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Chapter 7: How might the interaction model change human-AI collaboration?
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Chapter 8: What future developments can we expect in AI interaction technologies?
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And you can prove the ROI. Stop guessing if your AI investment is working. Check out Section at sectionai.com. That's S-E-C-T-I-O-N-A-I dot com. Welcome back to the AI Daily Brief. Today's episode is a bit surprising to me. We're discussing a new model, which isn't out of the norm for this show, but it is not a new model from OpenAI or Anthropic or even from one of the Chinese labs.
Instead, it comes from thinking machines and is all about a new mode of interaction. Now, just by way of quick background, if there was going to be a lab outside of the biggies that could drop something that would catch our attention, Thinking Machines Lab is a pretty good bet for that.
Former OpenAI CTO Meera Muradi left OpenAI to form the lab and pulled away a super team of researchers directly from the labs while also doing some very aggressive fundraising. In any other era in the past, the low billions of dollars that they had raised in fundraising would be notable.
It's just obviously compared to the tens or even hundreds of billions in resources that the biggies are playing with, a billion or two seems frankly pretty quaint. Thinking Machines released their first product, Tinker, last October, which was a platform for reinforcement learning as a service, essentially allowing companies to fine-tune open-source models.
It wasn't received poorly exactly, but it certainly didn't capture a ton of attention or discourse in the industry. Late last year, we got rumors of more aggressive fundraising and talk of TML releasing their own model. But things went pretty quiet to begin this year, save for a wave of reports that staff and founders were leaving the company.
The highlight was that two of TML's co-founders, Barrett Zoff and Luke Metz, left in January to return to work at OpenAI. And of course, we are now in the firm realism period of AI.
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