Good Morning! Stocks suffered their biggest rout since April 2025 after investors unwound some of the year’s most popular AI trades. Top Democrats are calling for limits on the AI buildout after the midterms, including a national moratorium on data centers. And retail traders dumped the most stocks in a single day since the Covid selloff. 

Wall Street banks are set to lead a $3 billion debt deal to finance a CD&R acquisition. Goldman Sachs named 109 new partners, its biggest class since 2010. And Wendy’s rejected a $1.4 billion takeover proposal from Nelson Peltz’s Trian.

Plus: Blackstone lends $310 million for Starbucks’ Nashville hub, and the psychology behind bad investing decisions

Mosaic Intelligence is now live. Build complete financial models from natural-language prompts and supporting documents. See it in action.

If you work in corporate America, you know companies can get stingy about AI costs. So if you've ever needed three approvals to expense a $20 software subscription, you might be a little jealous of Cisco's latest AI experiment.

President and chief product officer Jeetu Patel gave a 27-year-old engineer "unlimited" AI tokens and told him to "go nuts." The goal is to see whether a two-person team can use AI to modernize Cisco's aging code within 24 months.

Padmanabhan "Paddy" Krishnamurthy may be young, but Cisco isn't exactly handing an intern a Claude Pro subscription. He co-founded the translation startup EzDubs, which Cisco bought in 2025, and he has computer science degrees from HKUST and Columbia. Even after running his own company, he ended up five levels below Patel, who described him as "buried away in the organization doing something unstrategic."

That changed when Patel visited Cisco's San Francisco office and the two got talking. Paddy pitched rewriting Cisco's legacy code with just two people, which is an aggressive target. With Patel's backing, he got four weeks to prove the concept. Fortune first reported the longer-term goal as refactoring 98% of the legacy code, but Cisco later clarified that the target is to rewrite or refactor 70% of its products by the end of 2027.

While the project might not be the most glamorous, it might be low-hanging fruit and a way for companies to show value. Keeping aging software running takes engineering time that could otherwise go toward building something new, so if a small team can use AI to handle more of that maintenance, Cisco could free up engineers without having to hire an entire department first. 

Patel has stressed that the project is an experiment and rewritten code must pass rigorous testing before deployment, so “go nuts” gets you permission to try, not permission to break a customer’s network.

Takeaway: Cisco hasn't proved that two people can modernize decades of software, but it has given them the resources and permission to find out. That's more concrete than another companywide email about embracing AI. If it works, Cisco's next big AI project might be checking who else is buried five levels down.

AI can build an LBO. But would you trust it in investment committee?

Everyone's talking about AI-generated financial models. But when millions of dollars are on the line, "mostly right" isn't good enough.

Meet Mosaic Intelligence. Build an entire financial model, test your assumptions, and explore different deal scenarios just by asking. No rebuilding spreadsheets. No LLM-generated calculations.

Here's how it works:

Upload a CIM, Excel file, or screenshot and ask: 

"Build an LBO with a 10x entry multiple, 5x leverage at S+550, and a more conservative base case."

Mosaic builds the operating forecast, debt schedule, and returns. In minutes, you're ready to move from building the model to challenging the deal.

Now ask the questions that actually matter:

Every question updates the actual underlying financial model, not just an answer in a chat window.

Here's the difference: AI drives the workflow. Mosaic's deterministic, Python-based financial modeling engine does the math. That means consistent calculations, traceable outputs, and no relying on an LLM to get the numbers right.

Less time building and fixing models. More time figuring out whether the deal actually works.

See Mosaic Intelligence in action →

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Description: The Scaling Curve examines the rise of Anthropic and its cofounder Dario Amodei, tracing his departure from OpenAI and the creation of a company built around developing powerful AI while prioritizing safety. The book explores AI scaling laws, the economics of artificial intelligence, competition among technology giants, and the challenges of building superintelligent systems responsibly. It offers a look at the intersection of technological innovation, corporate strategy, and existential risk.

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If you picture a startup founder, you probably picture someone in their twenties. Researchers used US Census data on 2.7 million founders of businesses launched from 2007 to 2014 to test that.

Among the fastest-growing 0.1% of new firms, the average founder was 45 in the company’s first year. A 50-year-old founder was 1.8 times more likely than a 30-year-old to build one of them.

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