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How I Invest Clips
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Top clips from How I Invest with David Weisburd — featuring insights from leading CIOs, LPs, GPs, and institutional investors.
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Joined August 2026
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SC Moatti spent years telling herself she needed to know one more thing before starting her fund.
"The more I know, the less I know. And everything I don't know, I'll figure it out."
She points to John Chambers, former Cisco chairman, who watched the reinvention cycle shrink from seven to ten years down to three to five around COVID. Her guess today: about two years.
Readiness was never the blocker. It was the excuse.
.@stevenjr76 on what working under Steve Jobs actually gave him:
Not a playbook. Confidence. The kind that lets you sit across from any founder or billionaire executive and know you belong in the room.
He also learned what parts of Apple's culture to keep and what to leave behind when he went to run Foursquare.
Two years of flying New York to Cupertino taught him something else: his best work wasn't going to happen inside someone else's company.
That realization is the real reason he started a venture firm.
SC Moatti on why she'd tell a 22 year old to do sales first:
Sales gives you a fast, brutal feedback loop. You win the deal or you lose it. Nothing subjective about it.
That's what builds the credibility to eventually tackle the ambiguous stuff, like product or venture investing, where you don't find out if you were right for ten years.
"Anything that's not a win or lose outcome is really difficult to build the credibility and the confidence to execute."
Career growth is a sequencing problem before it's a talent problem.
.@stevenjr76: Steve Jobs didn't just want the iPhone to win.
He wanted the best developers in the world to want to build for it, because he knew the apps would decide which phones people actually bought.
What stuck with the exec who worked under him wasn't the vision itself. It was watching Jobs argue about pixels and colors on a Tuesday, then describe the future of mobile computing on a Wednesday.
Grand vision and obsessive execution rarely live in the same person. When you find a founder who has both, that's the tell.
George Santos made $17,000 on Kalshi predicting he'd show up to the State of the Union. Then got banned.
Nnamdi Okike's point: that's the exact problem with prediction markets right now. People who can influence the outcome betting on the outcome. It erodes the whole premise.
His fix is more interesting than the ban.
Stop letting people bet on whether a bill passes. Let them bet on what its actual revenue effect will be in 2028, 2029. Real dollars, tied to a measurable result, no room for a politician to talk their way around it.
Get to ground truth. Skip the politicking.
Mach Industries founder Ethan Thornton on why early SpaceX employees describe loving their job so much they needed to win:
"I think that feeling comes from when three things are happening at the same time."
A tangible mission. Real ownership. And equity that gives people asymmetric upside, what he calls financial sovereignty.
"You can be an entrepreneur within a company if you have super clear ownership."
Passion isn't a personality trait you hire for. It's what happens when purpose, autonomy, and upside line up.
Doug Beyer, managing partner at Roaring Brook Holdings, on the quiet checklist LPs run before they write a check.
Team continuity. Have the partners actually worked together before. If they disagree, who wins. Has the junior staff been around for a cycle or two.
"That could be total knockout for a new firm if the partnership is not rock solid."
"Are they receptive to feedback? Not that LPs want to meddle, but these LPs have seen what good looks like and what bad looks like."
Nnamdi Okike on why VCs whiff on consumer bets:
"You think there's 10,000,000 of you or 50,000,000 of you where there's maybe a few thousand or tens of thousands." VCs mistake their own taste for mass-market demand.
Even if the product is broadly liked, the business model might not hold up. TAM looks small, so the deal gets passed.
That's what happened with Squire. At seed, Okike and his partner saw a barbershop booking-fee product and calculated a market too small to matter. They passed on the model, not the founders.
By Series A, Squire had layered in SaaS software and supply-chain sourcing on top of the booking fee. Same company, completely different ACV trajectory.
"We don't think this market is big enough because of the early quality business model." The mistake wasn't the math. It was assuming the model in front of them was the one that would exist in two years.
Everyone loves Airbnb's underdog story. Cereal boxes, hustling to survive, the scrappy founders nobody believed in.
An investor who was at their Series A party has a different memory.
No read on the business model, no idea if the industry made sense. But the team's talent, chemistry, and ambition were obvious in the room.
"You could see it. It was just the X factor."
Will Robbins (@whrobbins) on why retail might be the greatest business model ever built:
"These large retailers, goods could be 50% or 100% more expensive than they are and so much less successful."
Amazon, Walmart, Target, Home Depot.
Trillions in combined market cap, built on the same engine: scale lowers costs, lower costs drive volume, volume deepens the moat.
Robbins' point is that we stop noticing it because it works. Decades of ERPs, systems of record, and operational experience sit quietly behind every cheap price tag.
Economies of scale aren't just a defensible position. They're one of the rare moats that make the business more valuable and the product cheaper at the same time.
A portfolio company selling into insurance raised from a stack of brand-name VCs.
The person who actually moved the needle for them was a single adviser, a former senior Medicaid executive with a small sliver of shares.
Will Robbins' point: VC brand recognition doesn't exist outside the Twitter timeline. Insurance companies don't know who the tier-one firms are. They know who the Medicaid people are.
Software got cheap. Distribution and trust didn't. That's where the edge actually lives now.
Google invented the transformer. Had the compute, the talent, the money, everything.
Yuri Sagalov's point on why that didn't matter:
"In a lot of ways, OpenAI and Anthropic had no right to exist in the face of that, and Google missed."
A tiny team at OpenAI built something that competed with Google on day one. Then Anthropic did it again, faster.
SC Moatti, Managing Partner at Mighty Capital, on why the best operators today think like allocators:
"I have this amount of resources, people, agents, and money. And I'm gonna allocate them to my highest priority problems."
Three people and a hundred agents on one problem. An acquisition on another. Same company, same week, two totally different capital decisions.
Mighty Capital built their whole strategy around watching this play out. They call it the product alpha effect. Read the signals from 600,000 product builders, invest behind the ones actually allocating well.
Eight years in: six IPOs, six strategic acquisitions, a low loss ratio.
Nnamdi Okike, on why deploying fast into a hot category is a bad playbook:
"If you're putting all your money out in a year or two, and you're putting all these logos together in a heightened valuation environment, in categories where everybody's competing, that's a tough recipe for success."
He thinks that's exactly the playbook a lot of funds are running in AI right now.
Venture isn't a race to deploy. It's a long, dynamic game, pace, ownership, follow-ons, and when you harvest all move with the market, not against it.
Okike's own numbers make the case. His fund sold half a winning position at a rich valuation. That one decision returned 35% of the fund. Sell the other half, and it's closer to 70%.
Half right isn't the same as right.
OpenAI and Anthropic combined are rumored to be doing over $80B in revenue, built in the last 3-4 years. Adding $10B a month at times.
Lucas Swisher (@LucasSwisher1), Co-Head of Growth Investing at Coatue, says that's not even the main reason investors are obsessed with them.
The real shift: these tools stopped just answering questions and started doing the work, integrated into actual workflows. That moves the addressable market from software spend to labor spend.
His comparison: the last time technology hit that kind of productivity leg, it was the tractor replacing the plow.
And it's not contained to two companies. Swisher notes over half of GDP growth this year has come from AI infrastructure buildout, financed on the confidence these revenues create.
We're in the first inning. Everyone's watching these two because the rest of the AI landscape is being priced off of them.
Nnamdi Okike on the question most crypto pitches never survive:
"Why does this need to be crypto?"
Back in the ICO craze, most founders couldn't answer that. No real problem, no clothes on the emperor.
Stablecoins finally answer it.
Sending money still runs through a chain of toll gates, banks skimming fees at every hop, for no reason other than that's how it's always worked. It's just bits. There's no reason it should be this inefficient.
Okike's read on what's next: Jeremy Allaire's thesis that agentic commerce requires programmable money, and programmable money requires digital currency. Two technologies that had to evolve together.
Product market fit, not magic. That's the difference between this cycle and the last one.
Nnamdi Okike on the difference between slow and precise vs. fast and lucky:
"There's a lot of ways to succeed in venture. There are folks that are impatient that do really well, especially if you're doing a huge number of deals per fund."
SC Moatti on why product-led growth is breaking:
Product used to be the channel. Every step of the workflow, a human made a decision, and you could upsell and cross sell right there.
Now the workflow is run by an executing agent. Governed by an overseeing agent. Periodically checked by a human.
Three users where there used to be one. Only one of them can actually buy anything.
"The distribution has to be reinvented." That's the opportunity most founders haven't priced in yet.
SC Moatti's good, great, best framework for AI adoption:
Good: take existing workflows and bolt on AI. Record the sales meeting, let AI write the notes. Incremental.
Great: rebuild the workflow end to end. Product managers, designers, engineers, QA collapse into one role: product builder, working with agents.
Best: teach leadership to allocate people, agents, and capital the way investors allocate a portfolio.
Most companies are stuck automating steps. The best ones are redesigning the org chart.
Every government drawing a hard line on AI IP right now: machines can never own anything they create.
SC Moatti's counterpoint is a Battlestar Galactica scene, the one where a character cuts open what looks like a machine and finds flesh and blood inside.
"They're developing personalities. They're becoming in a way humans."
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