Leadership isn't about having all the answers—it's about asking the right questions. I was reminded about this while listening to Shannon Minifie, CEO of Box of Crayons, on the Coaching for Leaders podcast (Episode 760), where she explored how the quality of our questions shapes the quality of our leadership.
The problem with "Why"
As leaders, we're trained to dig deep, to understand root causes. "Why did this happen?" "Why didn't you finish that project?" These questions feel investigative and thorough. But here's what Minifie points out: "why" questions often put people on the defensive.
When someone hears "Why did you do that?" their brain doesn't hear curiosity—it hears judgment. They start building walls instead of opening doors. The conversation shifts from exploration to explanation, from possibility to justification.
The "What" alternative
This connects directly to Michael Bungay Stanier's work in The Coaching Habit, which offers seven essential questions that keep conversations forward-focused. The shift from "why" to "what" is subtle but transformative.
Instead of asking:
"Why did this fail?" try "What happened here?"
"Why didn't you meet the deadline?" becomes "What got in the way?"
"Why do you think that?" transforms into "What's making you think that?"
Notice the difference? "What" questions invite reflection without accusation. They create space for honest conversation rather than defensive posturing.
Curiosity as a leadership muscle
The real lesson here isn't just about word choice—it's about cultivating genuine curiosity. When we approach situations with authentic curiosity rather than disguised criticism, we:
Build psychological safety: Team members feel comfortable sharing challenges and mistakes
Uncover better information: People share what actually happened, not sanitized versions
Foster problem-solving: The focus shifts to solutions rather than blame
Develop our people: Questions that make people think help them grow
The ripple effect
When you consistently ask "what" instead of "why," you're not just changing your vocabulary—you're changing your team's culture. You're signaling that mistakes are learning opportunities, that challenges are meant to be discussed openly, and that your role is to support growth, not assign blame.
Leadership curiosity isn't passive. It's an active choice to set aside judgment, stay genuinely interested, and create the conditions where people can do their best thinking.
There’s a moment before you start building where everything is still possible. You could structure it this way or that way. Use this pattern or that pattern. Once you start, you’re committed. The architecture solidifies like concrete.
AI makes implementation so fast that it’s tempting to skip this moment. Just start building, see what happens. But the architecture decisions you make (or don’t make) in that moment will haunt you for the life of the project.
Here’s what I’ve started doing: before building anything significant, I describe my approach to AI and ask it to poke holes. What could go wrong? What will be painful to change later? What am I not thinking about?
AI won’t make the decision for you. But it will stress-test your thinking before you pour the concrete.
Why Architecture Decisions Matter More With AI
AI makes implementation fast. That’s both the opportunity and the danger.
When implementation was slow, architecture decisions got scrutiny. Committing to an approach meant weeks of work. You thought carefully before starting.
When implementation takes hours, you might not think carefully at all. Just build it, see if it works. But the architectural problems are still there. You just hit them faster.
Speed of implementation makes architecture review more important, not less.
The Architecture Review Prompt
Before starting anything significant:
I'm planning to build this feature. Review my approach before I start.
Feature: [describe what you're building]
My proposed approach:
[describe how you plan to build it]
Evaluate:
1. What are the strengths of this approach?
2. What could go wrong?
3. What will be hard to change later?
4. What am I not thinking about?
5. What are 2-3 alternative approaches with tradeoffs?
Assume this will be in production for 5 years and maintained by developers
who didn't build it.
A Real Architecture Review
I was planning to add a notifications system. Here was my initial approach:
Feature: User notifications for card activity
My proposed approach:
- Add a notifications table
- When something happens, write a notification row
- API endpoint returns notifications for a user
- Frontend polls every 30 seconds
AI’s review:
Strengths:
Simple to implement
Easy to understand
Works for low scale
What could go wrong:
Polling every 30 seconds from 10,000 users = 333 requests/second just for notifications
Users with 10,000 notifications will have slow queries
No way to push urgent notifications
Polling even when no new notifications wastes resources
Hard to change later:
If you later need real-time, WebSocket integration will require significant frontend changes
If you need to categorize or filter notifications, schema changes affect all existing data
No notification preferences means no way to respect user choices
Not thinking about:
Notification cleanup (do you keep them forever?)
Batch notifications (10 events in a minute = 10 notifications or 1?)
Cross-device sync (read on phone, still shows on web?)
Email/push integration (this architecture doesn’t support it)
Alternative approaches:
Event-driven with WebSocket
Events published to a queue
Notification service consumes events, delivers via WebSocket
Tradeoff: More complex, but real-time and scalable
Hybrid polling with push for urgent
Poll for routine notifications
WebSocket channel for urgent ones
Tradeoff: Two delivery mechanisms to maintain
Third-party service (Firebase, Pusher)
Outsource the delivery infrastructure
Tradeoff: Cost, dependency, but proven at scale
The review didn’t tell me what to do. It showed me what I hadn’t considered. I still chose polling for MVP, but I designed the schema to support future migration to events.
The Tradeoff Analysis Prompt
When you’re deciding between approaches:
Help me decide between these approaches.
The problem: [what you're trying to solve]
Option A: [describe first approach]
Option B: [describe second approach]
Option C: [describe third approach]
For each option, analyze:
1. Implementation complexity
2. Performance characteristics
3. Maintainability over time
4. Scalability limits
5. What breaks first under load?
6. What's hardest to change?
Then recommend which option for:
- MVP with 100 users
- Scale to 10,000 users
- Scale to 1,000,000 users
The “What Could Go Wrong” Prompt
For risk analysis:
I'm about to implement this. What could go wrong?
The feature: [describe it]
The approach: [describe your plan]
The constraints: [timeline, team, tech stack]
List everything that could go wrong:
1. Technical risks
2. Operational risks
3. Security risks
4. Performance risks
5. Integration risks
6. User experience risks
For each risk:
- Likelihood (high/medium/low)
- Impact (high/medium/low)
- Mitigation strategy
The Scalability Prompt
When you need to think about growth:
Analyze the scalability of this architecture.
Current scale: [users, requests, data volume]
Target scale: [where you expect to be in 1-2 years]
Architecture:
[describe your system]
Identify:
1. What breaks first as you scale?
2. What's the scaling limit of each component?
3. What would need to change for 10x scale?
4. What would need to change for 100x scale?
5. What should you build differently now to make scaling easier?
The Maintenance Prompt
For long-term thinking:
I'm building this feature. In 2 years, a developer who didn't build it
will need to modify it.
Feature: [describe it]
Current design: [describe your approach]
What will make maintenance hard?
1. What assumptions are implicit but not documented?
2. What will be confusing without context?
3. What coupling will make changes risky?
4. What will break in unexpected places?
What should I do differently now to make maintenance easier?
The Integration Analysis
When your feature touches other systems:
Analyze how this feature integrates with existing systems.
New feature: [describe it]
Existing systems it will touch:
[list them]
For each integration:
1. What data flows between them?
2. What happens if the other system is down?
3. What happens if the other system is slow?
4. What happens if the other system returns unexpected data?
5. Are there version compatibility concerns?
6. Who owns the contract between them?
The Migration Strategy Prompt
When you’re changing something that exists:
I need to migrate from the old system to the new system.
Old system: [describe current state]
New system: [describe target state]
Constraints: [uptime requirements, data volume, timeline]
Design a migration strategy:
1. Can we do this without downtime?
2. Can we run both systems in parallel?
3. How do we validate data integrity?
4. What's the rollback plan?
5. What's the sequence of steps?
6. What could go wrong at each step?
When to Ask for Architecture Help
Not every feature needs architecture review. Ask for help when:
High impact: The feature is core to your product
High complexity: Multiple components or services involved
High uncertainty: You’re not sure the approach is right
High cost of change: Changing later would be very expensive
Long lifespan: This will be in production for years
Skip it for small, isolated, easily-changed features.
Architecture Review Checklist
Before starting significant work:
□ Problem clearly defined
□ Approach documented
□ Alternatives considered
□ Tradeoffs understood
□ Scalability analyzed
□ Failure modes identified
□ Migration path exists
□ Maintenance burden acceptable
□ Integration points mapped
□ Rollback plan exists
The Humbling Part
AI often finds things I miss. Not because AI is smarter, but because AI has no ego.
When I design something, I want it to be right. I’m biased toward my own approach. AI doesn’t care. It just analyzes the tradeoffs.
That objectivity is valuable. It’s like having a team member who will always tell you the uncomfortable truth about your architecture.
Tomorrow
Architecture reviewed. Approach decided. But what happens when it’s 2am and production is on fire?
Tomorrow I’ll cover production debugging: using AI when you’re under pressure and things are broken.
Try This Today
Think of a feature you’re planning to build
Write up your proposed approach
Run the architecture review prompt
See what you hadn’t considered
The best time for architecture review is before you write code. The second best time is before you write more code.
Meta’s Dexter Station office in Seattle. (Meta Photo)
New layoffs at Meta will impact 331 workers in the Seattle area and Washington state, according to a filing from the state Employment Security Department.
The company is cutting employees at four facilities located in Seattle and on the Eastside, as well as approximately 97 employees who work remotely in Washington. The layoffs are part of broader reductions in the company’s Reality Labs division, first announced last week, that impacted 1,500 jobs companywide.
The heaviest hit facility is the Reality Labs office in Redmond, followed by the Spring District office in Bellevue, according to the Worker Adjustment and Retraining Notification (WARN) filing.
Meta’s Horizon OS software engineering team, working out of a Meta office on Dexter Avenue North in Seattle, was the hardest hit single group with 20 jobs cut. Horizon OS is the extended reality operating system developed to power Meta Quest virtual reality and mixed reality headsets.
Layoffs are expected to take effect on March 20.
With about 15,000 employees, Reality Labs currently represents about 19% of Meta’s total global workforce of roughly 78,000.
The company employs thousands of people across multiple offices in the Seattle region, one of its largest engineering hubs outside Menlo Park, Calif. Last October, the Facebook parent laid off more than 100 employees in Washington state as part of a broader round of cuts within its artificial intelligence division.
The Reality Labs cuts come at a time when the company is reportedly shifting priorities away from the metaverse to build next-generation artificial intelligence.
Sam Altman greets Microsoft CEO Satya Nadella at OpenAI DevDay in San Francisco in 2023. (GeekWire File Photo / Todd Bishop)
The launch of the AI lab that would redefine Microsoft caught the tech giant by surprise.
“Did we get called to participate?” Satya Nadella wrote to his team on Dec. 12, 2015, hours after OpenAI announced its founding. “AWS seems to have sneaked in there.”
Nadella had been Microsoft CEO for less than two years. Azure, the company’s cloud platform, was five years old and chasing Amazon Web Services for market share. And now AWS had been listed as a donor in the “Introducing OpenAI” post. Microsoft wasn’t in the mix.
In the internal message, which hasn’t been previously reported, Nadella wondered how the new AI nonprofit could remain truly “open” if it was tied only to Amazon’s cloud.
Within months, Microsoft was courting OpenAI. Within four years, it would invest $1 billion, adding more than $12 billion in subsequent rounds. Within a decade, the relationship would culminate in a $250 billion spending commitment for Microsoft’s cloud and a 27% equity stake in one of the most valuable startups in history.
New court filings offer an inside look at one of the most consequential relationships in tech. Previously undisclosed emails, messages, slide decks, reports, and deposition transcripts reveal how Microsoft pursued, rebuffed and backed OpenAI at various moments over the past decade, ultimately shaping the course of the lab that launched the generative AI era.
More broadly, they show how Nadella and Microsoft’s senior leadership team rally in a crisis, maneuver against rivals such as Google and Amazon, and talk about deals in private.
For this story, GeekWire dug through more than 200 documents, many of them made public Friday in Elon Musk’s ongoing suit accusing OpenAI and its CEO Sam Altman of abandoning the nonprofit mission. Microsoft is also a defendant. Musk, who was an OpenAI co-founder, is seeking up to $134 billion in damages. A jury trial is scheduled for this spring.
OpenAI has disputed Musk’s account of the company’s origins. In a blog post last week, the company said Musk agreed in 2017 that a for-profit structure was necessary, and that negotiations ended only when OpenAI refused to give him full control.
The recently disclosed records show that Microsoft’s own leadership anticipated the possibility of such a dispute. In March 2018, after learning of OpenAI’s plans to launch a commercial arm, Microsoft CTO Kevin Scott sent Nadella and others an email offering his thoughts.
“I wonder if the big OpenAI donors are aware of these plans?” Scott wrote. “Ideologically, I can’t imagine that they funded an open effort to concentrate ML [machine learning] talent so that they could then go build a closed, for profit thing on its back.”
The latest round of documents, filed as exhibits in Musk’s lawsuit, represents a partial record selected to support his claims in the case. Microsoft declined to comment.
Elon helps Microsoft win OpenAI from Amazon
Microsoft’s relationship with OpenAI has been one of its key strategic advantages in the cloud. But the behind-the-scenes emails make it clear that Amazon was actually there first.
According to an internal Microsoft slide deck from August 2016, included in recent filings, OpenAI was running its research on AWS as part of a deal that gave it $50 million in computing for $10 million in committed funds. The contract was up for renewal in September 2016.
Microsoft wanted in. Nadella reached out to Altman, looking for a way to work together.
In late August, the filings show, Altman emailed Musk about a new deal with Microsoft: “I have negotiated a $50 million compute donation from them over the next 3 years!” he wrote. “Do you have any reason not to like them, or care about us switching over from Amazon?”
Musk, co-chair of OpenAI at the time, gave his blessing to the Microsoft deal in his unique way, starting with a swipe at Amazon founder Jeff Bezos: “I think Jeff is a bit of a tool and Satya is not, so I slightly prefer Microsoft, but I hate their marketing dept,” Musk wrote.
He asked Altman what happened to Amazon.
Altman responded, “Amazon started really dicking us around on the T+C [terms and conditions], especially on marketing commits. … And their offering wasn’t that good technically anyway.”
Microsoft and OpenAI announced their partnership in November 2016 with a blog post highlighting their plans to “democratize artificial intelligence,” and noting that OpenAI would use Azure as its primary cloud platform going forward.
Harry Shum, then the head of Microsoft’s AI initiatives, with Sam Altman of OpenAi in 2026. (Photo by Brian Smale for Microsoft)
Internally, Microsoft saw multiple benefits. The August 2016 slide deck, titled “OpenAI on Azure Big Compute,” described it as a prime opportunity to flip a high-profile customer to Azure.
The presentation also emphasized bigger goals: “thought leadership” in AI, a “halo effect” for Azure’s GPU launch, and the chance to recruit a “net-new audience” of developers and startups. It noted that OpenAI was a nonprofit “unconstrained by a need to generate financial return” — an organization whose research could burnish Microsoft’s reputation in AI.
But as the ambition grew, so did the bill.
‘Most impressive thing yet in the history of AI’
In June 2017, Musk spoke with Nadella directly to pitch a major expansion. OpenAI wanted to train AI systems to beat the best human players at competitive esports, Valve’s Dota 2. The computing requirements were massive: 10,000 servers equipped with the latest Nvidia GPUs.
“This would obviously be a major opportunity for Microsoft to promote Azure relative to other cloud systems,” Musk wrote in an email to OpenAI colleagues after the call.
Nadella said he’d talk about it internally with his Microsoft cloud team, according to the email. “Sounds like there is a good chance they will do it,” Musk wrote.
Two months later, Altman followed up with a formal pitch. “I think it will be the most impressive thing yet in the history of AI,” he wrote to Nadella that August.
Microsoft’s cloud executives ran the numbers and balked. In an August 2017 email thread, Microsoft executive Jason Zander told Nadella the deal would cost so much it “frankly makes it a non-starter.” The numbers are redacted from the public version of the email.
“I do believe the pop from someone like Sam and Elon will help build momentum for Azure,” Zander wrote. “The scale is also a good forcing function for the fleet and we can drive scale into the supply chain. But I won’t take a complete bath to do it.”
Ultimately, Microsoft passed. OpenAI contracted with Google for the Dota 2 project instead.
‘A bucket of undifferentiated GPUs’
Microsoft’s broader relationship with OpenAI was starting to fray, as well. By January 2018, according to internal emails, Microsoft executive Brett Tanzer had told Altman that he was having a hard time finding internal sponsors at Microsoft for an expanded OpenAI deal.
Altman started shopping for alternatives. Around that time, Tanzer noted in an email to Nadella and other senior executives that OpenAI’s people “have been up in the area recently across the lake” — a reference to Amazon’s Seattle headquarters.
The internal debate at Microsoft was blunt.
OpenAI CEO Sam Altman and Microsoft CTO Kevin Scott at Microsoft Build in 2024. (GeekWire File Photo / Todd Bishop)
Scott wrote that OpenAI was treating Microsoft “like a bucket of undifferentiated GPUs, which isn’t interesting for us at all.” Harry Shum, who led Microsoft’s AI research, said he’d visited OpenAI a year earlier and “was not able to see any immediate breakthrough in AGI.”
Eric Horvitz, Microsoft’s chief scientist, chimed in to say he had tried a different approach. After a Skype call with OpenAI co-founder Greg Brockman, he pitched the idea of a collaboration focused on “extending human intellect with AI — versus beating humans.”
The conversation was friendly, Horvitz wrote, but he didn’t sense much interest. He suspected OpenAI’s Dota work was “motivated by a need to show how AI can crush humans, as part of Elon Musk’s interest in demonstrating why we should all be concerned about the power of AI.”
Scott summed up the risk of walking away: OpenAI might “storm off to Amazon in a huff and shit-talk us and Azure on the way out.”
“They are building credibility in the AI community very fast,” the Microsoft CTO and Silicon Valley veteran wrote. “All things equal, I’d love to have them be a Microsoft and Azure net promoter. Not sure that alone is worth what they’re asking.”
But by the following year, Microsoft had found a reason to double down.
The first billion
In 2019, OpenAI restructured. The nonprofit would remain, but a new “capped profit” entity would sit beneath it — a hybrid that could raise capital from investors while limiting their returns.
Microsoft agreed to invest $1 billion, with an option for a second billion, in exchange for exclusive cloud computing rights and a commercial license to OpenAI’s technology.
The companies announced the deal in July 2019 with a joint press release. “The creation of AGI will be the most important technological development in human history, with the potential to shape the trajectory of humanity,” Altman said. Nadella echoed that sentiment, emphasizing the companies’ ambition to “democratize AI” while keeping safety at the center.
So what changed for Microsoft between 2018 and 2019?
In a June 2019 email to Nadella and Bill Gates, previously disclosed in the Google antitrust case, Scott cited the search giant’s AI progress as one reason for Microsoft to invest in OpenAI. He “got very, very worried,” he explained, when he “dug in to try to understand where all of the capability gaps were between Google and us for model training.”
Microsoft CEO Satya Nadella and OpenAI CEO Sam Altman at the Microsoft campus in Redmond, Wash. on July 15, 2019. (Photography by Scott Eklund/Red Box Pictures)
Nadella forwarded Scott’s email to Amy Hood, Microsoft’s CFO. “Very good email that explains why I want us to do this,” Nadella wrote, referring to the larger OpenAI investment, “and also why we will then ensure our infra folks execute.”
Gates wasn’t so sure. According to Nadella’s deposition testimony, the Microsoft co-founder was clear in “wanting us to just do our own” — arguing that the company should focus on building AI capabilities in-house rather than placing such a large bet on OpenAI.
Nadella explained that the decision to invest was eventually driven by him and Scott, who concluded that OpenAI’s specific research direction into transformers and large language models (the GPT class) was more promising than other approaches at the time.
Hood, meanwhile, offered some blunt commentary on OpenAI’s cap on profits — the centerpiece of its new structure, meant to limit investor returns and preserve the nonprofit’s mission. The caps were so high, she wrote, that they were almost meaningless.
“Given the cap is actually larger than 90% of public companies, I am not sure it is terribly constraining nor terribly altruistic but that is Sam’s call on his cap,” Hood wrote in a July 14, 2019, email to Nadella, Scott, and other executives.
If OpenAI succeeded, she noted, the real money for Microsoft would come from Azure revenue — far exceeding any capped return on the investment itself.
But the deal gave Microsoft more than cloud revenue.
According to an internal OpenAI memo dated June 2019, Microsoft’s investment came with approval rights over “Major Decisions” — including changes to the company’s structure, distributions to partners, and any merger or dissolution.
Microsoft’s $1 billion made it the dominant investor. Under the partnership agreement, major decisions required approval from a majority of limited partners based on how much they had contributed. At 85% of the total, Microsoft had an effective veto, a position of power that would give the company a pivotal role in defining the future of the company.
‘The opposite of open’
In September 2020, Musk responded to reports that Microsoft had exclusively licensed OpenAI’s GPT-3. “This does seem like the opposite of open,” he tweeted. “OpenAI is essentially captured by Microsoft.”
Nadella seemed to take the criticism seriously.
In an October 2020 meeting, according to internal notes cited in a recent court order, Microsoft executives discussed the perception that the company was “effectively owning” OpenAI, with Nadella saying they needed to give thought to Musk’s perspective.
In February 2021, as Microsoft and OpenAI negotiated a new investment, Altman emailed Microsoft’s team: “We want to do everything we can to make you all commercially successful and are happy to move significantly from the term sheet.”
His preference, Altman told the Microsoft execs, was “to make you all a bunch of money as quickly as we can and for you to be enthusiastic about making this additional investment soon.”
They closed the deal in March 2021, for up to $2 billion. This was not disclosed publicly until January 2023, when Microsoft revealed it as part of a larger investment announcement.
By 2022, the pressure to commercialize was explicit.
Mira Murati, left, and Sam Altman at OpenAi DevDay 2023. (GeekWire File Photo / Todd Bishop)
According to a transcript of her deposition, Mira Murati, then OpenAI’s vice president of applied AI and partnerships, had written in contemporaneous notes that the most-cited goal inside the company that year was a $100 million revenue target. Altman had told employees that Nadella and Scott said this needed to be hit to justify the next investment, as much as $10 billion.
Murati testified that Altman told her “it was important to achieve this goal to receive Microsoft’s continued investments.” OpenAI responded by expanding its go-to-market team and building out its enterprise business.
Then everything changed.
The ChatGPT moment
On Nov. 30, 2022, OpenAI announced ChatGPT. The chatbot became the fastest-growing consumer application in history, reaching 100 million users within two months. It was the moment that turned OpenAI from an AI research lab into a household name.
Microsoft’s bet was suddenly looking very different.
OpenAI’s board learned about the launch on Twitter. According to deposition testimony, board members Helen Toner and Tasha McCauley received no advance notice and discovered ChatGPT by seeing screenshots on social media.
McCauley described the fact that a “major release” could happen without the board knowing as “extremely concerning.” Toner testified that she wasn’t surprised — she was “used to the board not being very informed” — but believed it demonstrated that the company’s processes for decisions with “material impact on the mission were inadequate.”
Altman, according to one filing, characterized the release as a “research preview” using existing technology. He said the board “had been talking for months” about building a chat product, but acknowledged that he probably did not send the board an email about the specific release.
As its biggest investor, Microsoft pushed OpenAI to monetize the product’s success.
Microsoft CEO Satya Nadella speaks at OpenAI DevDay in 2023, as Sam Altman looks on. (GeekWire File Photo / Todd Bishop)
In mid-January 2023, Nadella texted Altman asking when they planned to activate a paid subscription.
Altman said they were “hoping to be ready by end of jan, but we can be flexible beyond that. the only real reason for rushing it is we are just so out of capacity and delivering a bad user experience.”
He asked Nadella for his input: “any preference on when we do it?”
“Overall getting this in place sooner is best,” the Microsoft CEO responded, in part.
Two weeks later, Nadella checked in again: “Btw …how many subs have you guys added to chatGPT?”
Altman’s answer revealed what they were dealing with. OpenAI had 6 million daily active users — their capacity limit — and had turned away 50 million people who tried to sign up. “Had to delay charging due to legal issues,” he wrote, “but it should go out this coming week.”
ChatGPT Plus launched on Feb. 1, 2023, at $20 a month.
Microsoft invested $10 billion in OpenAI. The companies had begun negotiating the previous summer, when OpenAI was still building ChatGPT. The product’s viral success validated Microsoft’s bet and foreshadowed a new era of demand for its cloud platform.
Ten months later, it nearly collapsed.
‘Run over by a truck’
On Friday afternoon, Nov. 17, 2023, OpenAI’s nonprofit board fired Altman as CEO, issuing a terse statement that he had not been “consistently candid in his communications with the board.” Greg Brockman, the company’s president and cofounder, was removed from the board the same day. He quit hours later.
Microsoft, OpenAI’s largest investor, was not consulted. Murati, then OpenAI’s chief technology officer and the board’s choice for interim CEO, called Nadella and Kevin Scott to warn them just 10 to 15 minutes before Altman himself was told.
“Mira sounded like she had been run over by a truck as she tells me,” Scott wrote in an email to colleagues that weekend.
The board — Ilya Sutskever, Tasha McCauley, Helen Toner, and Adam D’Angelo — had informed Murati the night before. They had given her less than 24 hours to prepare.
At noon Pacific time, the board delivered the news to Altman. The blog post went live immediately. An all-hands meeting followed at 2 p.m. By Friday night, Brockman had resigned. So had Jakub Pachocki, OpenAI’s head of research, along with a handful of other researchers.
A “whole horde” of employees, Scott wrote, had reached out to Altman and Brockman “expressing loyalty to them, and saying they will resign.”
Microsoft didn’t have a seat on the board. But text messages between Nadella and Altman, revealed in the latest filings, show just how influential it was in the ultimate outcome.
At 7:42 a.m. Pacific on Saturday, Nov. 18, Nadella texted Altman asking if he was free to talk. Altman replied that he was on a board call.
“Good,” Nadella wrote. “Call when done. I have one idea.”
That evening, at 8:25 p.m., Nadella followed up with a detailed message from Brad Smith, Microsoft’s president and top lawyer. In a matter of hours, the trillion-dollar corporation had turned on a dime, establishing a new subsidiary from scratch — legal work done, papers ready to file as soon as the Washington Secretary of State opened Monday morning.
They called it Microsoft RAI Inc., using the acronym for Responsible Artificial Intelligence.
“We can then capitalize the subsidiary and take all the other steps needed to operationalize this and support Sam in whatever way is needed,” Smith wrote. Microsoft was “ready to go if that’s the direction we need to head.”
Altman’s reply: “kk.”
A screenshot of text messages between Microsoft CEO Satya Nadella and OpenAI CEO Sam Altman following Altman’s ouster in 2023.
The company calculated the cost of absorbing the OpenAI team at roughly $25 billion, Nadella later confirmed in a deposition — enough to match the compensation and unvested equity of employees who had been promised stakes in a company that now seemed on the verge of collapse.
By Sunday, Emmett Shear, the Twitch co-founder, had replaced Murati as interim CEO. That night, when the board still hadn’t reinstated Altman, Nadella announced publicly that Microsoft was prepared to hire the OpenAI CEO and key members of his team.
“In a world of bad choices,” Nadella said in his deposition, the move “was definitely not my preferred thing.” But it was preferable to the alternative, he added. “The worst outcome would have been all these people leave and they go to our competition.”
‘Strong strong no’
On Tuesday, Nov. 21, the outcome was still uncertain. Altman messaged Nadella and Scott that morning, “can we talk soon? have a positive update, ish.” Later, he said the situation looked “reasonably positive” for a five-member board. Shear was talking to the remaining directors.
Nadella asked about the composition, according to the newly public transcript of the message thread, which redacts the names of people who ultimately weren’t chosen.
“Is this Larry Summers and [redacted] and you three? Is that still the plan?”
Summers was confirmed, Altman replied. The other slots were “still up in air.”
Altman asked, “would [redacted] be ok with you?”
“No,” Nadella wrote.
Scott was more emphatic, giving one unnamed person a “strong no,” and following up for emphasis: “Strong strong no.”
The vetting continued, as Nadella and Scott offered suggestions, all of them redacted in the public version of the thread.
A screenshot of text messages from Nov. 21, 2023, included as an exhibit in Elon Musk’s lawsuit, shows Microsoft President Brad Smith and CEO Satya Nadella discussing OpenAI board prospects with Sam Altman following his ouster.
Nadella added Smith to the thread. One candidate, the Microsoft president wrote, was “Solid, thoughtful, calm.” Another was “Incredibly smart, firm, practical, while also a good listener.”
At one point, Scott floated a joke: “I can quit for six months and do it.” He added a grinning emoji and commented, “Ready to be downvoted by Satya on this one, and not really serious.”
Nadella gave that a thumbs down.
The back-and-forth reflected a delicate position. Microsoft had no board seat at OpenAI. Nadella had said publicly that the company didn’t want one. But the texts showed something closer to a shadow veto — a real-time screening of the people who would oversee the nonprofit’s mission.
By evening, a framework emerged. Altman proposed Bret Taylor, Larry Summers, and Adam D’Angelo as the board, with himself restored as CEO. Taylor would handle the investigation into his firing.
Smith raised a concern. “Your future would be decided by Larry [Summers],” he wrote. “He’s smart but so mercurial.” He called it “too risky.” (Summers resigned from the OpenAI board in November 2025, following revelations about his correspondence with Jeffrey Epstein.)
Altman wrote, “id accept it given my conversations with him and where we are right now.” He added, “it’s bullshit but i want to save this … can you guys live with it?”
Nadella asked for Summers’ cell number.
At 2:38 p.m., Altman texted the group: “thank you guys for the partnership and trust. excited to get this all sorted to a long-term configuration you can really depend on.”
Nadella loved the message.
Two minutes later, Smith replied: “Thank you! A tough several days. Let’s build on this and regain momentum.”
Altman loved that one.
Nadella had the last word: “Really looking forward to getting back to building….”
“We are encouraged by the changes to the OpenAI board,” Nadella posted on X. “We believe this is a first essential step on a path to more stable, well-informed, and effective governance.”
The crisis was resolved, but the underlying tensions remained.
‘Project Watershed’
On December 27, 2024, OpenAI announced it would unwind its capped-profit structure. Internally, this initiative was called “Project Watershed,” the documents reveal.
The mechanics played out through 2025. On September 11, Microsoft and OpenAI executed a memorandum of understanding with a 45-day timeline to finalize terms.
Microsoft’s role was straightforward but powerful. Its approval rights over “Major Decisions” including changes to OpenAI’s structure. Asked in a deposition whether those rights covered a recapitalization of OpenAI’s for‑profit entity into a public benefit corporation, Microsoft corporate development executive Michael Wetter testified that they did.
The company had no board seat. “Zero voting rights,” Wetter testified. “We have no role, to be super clear.” But under the 2019 agreement, the conversion couldn’t happen without them.
The timing mattered. A SoftBank-led financing — internally called Project Sakura — was contingent on the recapitalization closing by year-end. Without the conversion, the funding could not proceed. Without Microsoft’s approval, the conversion could not proceed.
Valuation became a key focus of negotiations. Morgan Stanley, working for Microsoft, estimated OpenAI’s value at $122 billion to $177 billion, according to court filings. Goldman Sachs, advising OpenAI, put it at $353 billion. The MOU set Microsoft’s stake at 32.5 percent. By the time the deal closed after the SoftBank round, dilution brought it to 27 percent.
OpenAI’s implied valuation was $500 billion — a record at the time (until it was surpassed in December by Musk’s SpaceX). As Altman put it in his deposition, “That was the willing buyer-willing seller market price, so I won’t argue with it.”
For Microsoft, it was a give-and-take deal: the tech giant lost its right of first refusal on new cloud workloads, even as OpenAI committed to the $250 billion in future Azure purchases.
At the same time, the agreement defused the clause that had loomed over the partnership: under prior terms, a declaration of artificial general intelligence by OpenAI’s board would have cut Microsoft off from future models. Now any such declaration needs to be made by an independent panel, and Microsoft’s IP rights run through 2032 regardless.
The transaction closed on Oct. 28, 2025. The nonprofit remained (renamed the OpenAI Foundation) but as a minority shareholder in the company it had once controlled.
Six days later, OpenAI signed a seven-year, $38 billion infrastructure deal with Amazon Web Services. The company that had “sneaked in there” at the founding, as Nadella put it in 2015, was back — this time as a major cloud provider for Microsoft’s flagship AI partner.
An OpenAI graphic shows its revenue tracking computing consumption.
In a post this weekend, OpenAI CFO Sarah Friar made the shift explicit: “Three years ago, we relied on a single compute provider,” she wrote. “Today, we are working with providers across a diversified ecosystem. That shift gives us resilience and, critically, compute certainty.”
Revenue is up from $2 billion in 2023 to more than $20 billion in 2025. OpenAI is no longer a research lab dependent on Microsoft’s cloud. It’s a platform company with leverage.
In December 2015, Nadella had to ask whether Microsoft had been called to participate in the OpenAI launch. A decade later, nothing could happen without the Redmond tech giant.
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