Daren Trousdell

AI-pilled investor and partner to the best management teams in Software, Critical Infrastructure and Tech-Enabled Services @ KOAT Capital 🇨🇦 + 🇺🇸

[andrew engler @aerockrose]

Brad Jacobs explains the acquisition filter that made him billions:

"I looked at that org chart and said: this is a messed up org chart."

"Great for making money if you can find something messed up and easy to unmess up."

"Boyah. There's your money. There's your opportunity."

The lesson: rigid plans miss the best deals. The money is often in a broken system that is obvious once someone draws the org chart.

[Daren Trousdell @dtrous]

Insanity for a useless cash-based card and expense manager that anyone can write with AI

[Simon Taylor @sytaylor]

Holy crap! @tryramp just raised $750M at a $44B valuation. 🤯

That's about 8.5x what Capital One paid to buy Brex two months ago.

Ramp says the new capital raise, led by ICONIC and GIC, to build the cost infrastructure for AI. The big picture the investors are buying is that there's a structural change to the economy coming.

We used to talk about

1. Capital - funding for businesses
2. Labor - people

The third, new one is intelligence. Intelligence comes with a token supply chain and that is paid for next to the existing vendors a business manages.

And there is a cost problem. Uber burned through their entire annual AI token budget in four months.

The Ramp product is rapidly shifting to address this with features such as token spend management, procurement agents, accounting agents, and a deeper Visa tie-up that lets AI agents make corporate payments on their own.

And on pure fundementals Ramp is crushing.

Purchase volume grew ~170% year on year in March, the fastest in three years, at roughly 20x the size they were 3 years ago. Woof.

And the contrast with Brex is noteworthy. Brex created this category. The original "Amex for startups." Capital One bought the whole company in April for $5.15B, a steep markdown from Brex's $12.3B peak.

Ramp, founded a full two years after Brex, just got priced at roughly 3.5x Brex's best-ever number. S

The difference is boring and brutal: Ramp went cash-flow positive and kept compounding. It was worth $13B in March last year and $44B now.

[Daren Trousdell @dtrous]

@JoshOnAir Can’t wait for that one!

[Daren Trousdell @dtrous]

My older girls enjoying the French Open 🎾 this week

[Daren Trousdell @dtrous]

@JoshOnAir They are. I’m a working stiff

[Shane Parrish @shaneparrish]

At 28 @markpinc was nearly broke, had been fired by John Malone and Bain, and as he says "my life sucked so badly."

He wanted a place to think and ended up in a synagogue. Sitting there something happened ... but it wasn't a religious experience.

He started writing what he calls the book of life. He documented every single thing that sucked in his life (and it was a long list.)

Then he wrote out a goal for the next year that taught he he was the master of his circumstances, not the other way around.

And he's done this every year of his life since.

The key question he's trying to answer each year is: "What would your future self thank you for doing this year?"

[Daren Trousdell @dtrous]

Genius marketing

[GURGAVIN @gurgavin]

BUSINESSES ARE NOW USING PREDICTION MARKETS TO HEDGE PROMOTIONS LOL

A BAR IN NYC HAD A PROMO IF THE KNICKS WIN, THEY COVER EVERYONE’S DRINKS FOR THE NIGHT

THE BAR PLACED A $5K HEDGE ON KALSHI THAT PAYS OUT IF THE KNICKS WIN

THE BAR WINS EITHER WAY

[StockMarket.News @_Investinq]

Nicolai Tangen, CEO of Norges Bank Investment Management pressed IBM CEO Arvind Krishna directly on whether AI is a bubble (Save this).

And Krishna responded with what has become known inside financial circles as the $8 trillion math problem.

A single gigawatt of AI data center capacity filled with accelerators, liquid cooling, and power infrastructure costs roughly $60 to $80 billion to build and populate.

The industry has committed to more than 100 gigawatts of buildout globally.

That is $6 to $8 trillion in capital expenditure and because AI grade hardware depreciates on a five-year cycle, that entire sum must be effectively replaced and refreshed every five years.

To service the interest on $8 trillion in capital at a conservative 10% borrowing rate, the AI ecosystem would need to generate approximately $800 billion in annual profit, a number that currently exceeds the combined net income of every large technology company in the world.

Goldman Sachs estimates $7.6 trillion in aggregate AI CapEx between 2026 and 2031 alone, and Reuters Breakingviews has flagged that even if the capital is available, physical bottlenecks power permits, land, cooling infrastructure, and electrical grid connections mean that half of the planned data center projects are being cancelled or delayed before they ever go live.

Krishna also raised a second, structurally distinct concern that markets have largely ignored.

He argued that the largest foundation models, GPT, Gemini, Claude, Llama are converging toward commodity status.

When a product is a commodity, switching costs collapse.

When switching costs collapse, pricing power evaporates and margins compress regardless of how much capital was spent building the capability.

Morningstar's equity research team conducted a review of 132 technology companies in 2026 and found that AI had caused moat rating downgrades across roughly 40 major stocks concentrated in enterprise software, IT services, and SaaS with Adobe, Salesforce, Workday, and ADP among the companies whose competitive moats have materially weakened.

The implication is that the companies spending the most on AI model development may be building an asset that is simultaneously the most expensive to produce and the most difficult to monetize with durable margins.

This bear case is serious but it is also incomplete and that is what makes Krishna's framing so important to understand precisely.

When pressed further, Krishna explicitly said he does not believe there is an AI bubble in the technology itself only in a subset of the infrastructure capital that is being deployed against speculative assumptions rather than proven demand.

He draws the same analogy, the fiber optic overbuild of the late 1990s. Dozens of companies went bankrupt laying cable that nobody was using.

And yet that exact "wasted" infrastructure became the physical backbone of every cloud company, every streaming service, every mobile network, and every modern AI training cluster that followed.

The builders lost, the infrastructure won.

And the companies that were built on top of it, Amazon, Google, Netflix, Salesforce compounded for two decades.

The question, as Krishna framed it, is not whether AI is real.

It is which capital deployment earns a return versus which gets stranded and crucially, whether you own the stranded assets or the companies built on top of them.

On winners, Krishna was direct that distribution is the moat on the consumer side, and enterprise is wide open.

The data supports this, Meta with 3.3 billion daily active users across Facebook, Instagram, and WhatsApp is building AI into a distribution network that no startup can replicate at any cost.

Meanwhile, the productivity evidence arriving in real time is beginning to challenge the bear case's revenue projections.

Jensen Huang just showed on stage at Computex that GitHub commits, the universal measure of global software output nearly tripled in the first months of 2026, effectively converting $3 trillion in developer salaries into $9 trillion in productive output.

That is measurable, real time economic value already flowing through the system and it feeds directly back into token demand in a compounding loop that Krishna's static CapEx math does not fully capture.

[Daren Trousdell @dtrous]

🤣

[More Perfect Union @MorePerfectUS]

BREAKING: Bernie Sanders will introduce a bill to have the public take a 50% ownership stake in the country's biggest AI companies.

The American AI Sovereign Wealth Fund Act would have the government tax AI companies, take 50% of the stock, and put it under public control.

[st1ne @SolSt1ne]

Goldman Sachs MDs make $1-3M/year doing one thing: keeping CEOs of Fortune 500 firms on speed dial.

This 23-min UVA Law lecture by Goldman's Vice Chairman of Global Client Coverage teaches you the exact 18 rules he uses to do it.

worth more than any $5K business school elective on client management.

bookmark & watch today.

[Daren Trousdell @dtrous]

This is bonkers

[Vivek Sen @Vivek4real_]

BREAKING: AXIOS AI REPORTER JUST REVEALED A CO. SPENT $500 MILLION IN A MONTH AFTER NOT SETTING USAGE LIMITS ON CLAUDE FOR EMPLOYEES.​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​

THIS IS ABSOLUTELY WILD 🤯

[Daren Trousdell @dtrous]

@GaryMarcus @MadisonMills22 @axios Everyone going to move to https://t.co/uto9j40xXh

[Daren Trousdell @dtrous]

AI is no longer optional. For 99% of companies, it's still unaffordable.

Every board is mandating it. Every budget is bending to it. AI is now the fastest-growing line item in corporate IT — and with agents running 24/7, token bills are climbing vertically.

Yet most companies are stuck with two bad options:

→ Pay frontier APIs that are subsidized today and repricing tomorrow (GitHub Copilot moved to token billing this month; the rest are following).

→ Or build it yourself — a $5M+ ML team and 12+ months you don't have.

Neither works for the 99%. So we built a third option.

Today we're launching Good Enough AI.

Low-cost AI-as-a-service for the companies that need AI but can't afford the frontier.

→ 95% of the capability — running the best open-source models (Llama, Qwen, Mistral, DeepSeek) at parity with frontier APIs for real business work.

→ 70–90% less cost — smart routing sends every task to the cheapest model that can handle it.

→ 0% DevOps — managed hosting, eval, monitoring, security, and 50+ prebuilt workflows. You get an API and a dashboard. We do the work an ML team would.

One predictable bill. No surprise invoices. Production-ready from day one.

The subsidy era is ending. The bill is coming. We're here for everyone who can't pay it.

If your AI spend is outrunning your ROI, let's talk.

[Daren Trousdell @dtrous]

@WatchMyReview He’s not wrong. Maybe Toronto made him the bitch he was. Put a Mark Stone in the locker room and this guy plays his heart out.

[Daren Trousdell @dtrous]

@_DavidRumsey @FOS @FOS_News_ It’s guaranteed dogshit

[Daren Trousdell @dtrous]

Utter fucking trash

[Sawyer Merritt @SawyerMerritt]

Ferrari has just released a new video of the all-electric Ferrari Luce.

[Daren Trousdell @dtrous]

Apparently this is a golf hole 😳 - Tail of the Whale. Unplayable in the afternoon with high tide. Punta Mita Mexico is 👌

[Anatoli Kopadze @AnatoliKopadze]

KIMI FOUNDER JUST DROPPED A GUIDE ON BUILDING A $20B STARTUP FROM ZERO

I haven't seen anyone explain AI agent architecture this clearly before

40 minutes with Yang Zhilin on how Kimi works, what they built, and what's coming next

this is the kind of talk that used to stay behind closed doors

[Daren Trousdell @dtrous]

@JimChuong They barely invest in Canada too. Gross

[Codie Sanchez @Codie_Sanchez]

Life without HR at your company.