When I first started as a fund manager, I was a skeptic. I could always see why things might go down. There was a deal that looked too rich, a balance sheet that didn’t hold up, a market that had run too far. And in the 50/50 world of listed equities, where a share can go up or down and you’re paid to have a view either way, that wasn’t necessarily the wrong mindset. Seeing the downside is a real skill. It keeps you out of trouble.

However, it has a mental toll. If your job is to look at the world and find the reasons it might break, you carry those reasons home with you. You get good at being right about why something is fragile, and being right about fragility is a quietly miserable way to spend a decade.

It took me a few years to work out that being negative was probably wrong.

The wealthy are optimists

The realisation was structural, not emotional. Most of the wealth in the world is owned by the top 10%. The wealthy drive the money flows. And the wealthy are, almost by definition, optimistic about the assets they own: they bought them, hold them, and want them to go up. If you are permanently bearish, you are betting against the people who move the most capital, and you are betting against them in a system they are inclined to push upward. You can be right occasionally. The crash comes, you feel vindicated for a quarter. But the long arc is owned by the optimists, and they are the ones setting the price.

I can pin the moment this stopped being abstract for me. In the early 1990s I was bearish on Sydney house prices. The 1990 property crash was still fresh, prices seemed eye-wateringly expensive, and every model I could build said wait. Then my now-wife convinced me to buy a house. And the moment I owned it, I became bullish on house prices.

I’d love to tell you this was a considered revision of my views in light of new evidence, but it wasn’t. I owned the asset, so I wanted it to go up, and my brain obligingly found the reasons. That’s the confessional bit, and it’s worth sitting with, because it’s the same mechanism that makes the wealthy optimistic about what they own. Conviction follows ownership far faster than it follows analysis.

The biggest momentum trade of my lifetime

At BT I sat on the asset allocation committee, and one of our central tasks was to work out whether the Australian market was going up or down. A heroic challenge, that one! The framework we leaned on tried to balance two things: valuation — what something is worth, the territory I’ve written about in valuing early-stage startups — and momentum, which is the tendency of things that are moving to keep moving.

Valuation tells you what to pay. Momentum tells you what’s happening. And it turns out the most powerful momentum trade I’ve ever seen had nothing to do with the asset allocation models.

I first became aware of technology as an investment theme when the US fund manager at BT asked me what I thought about the Windows 95 release and what it would mean for Microsoft. I didn’t have a good answer at the time. But the question lodged, and it was the genesis of what I now think of as the biggest momentum trade of my lifetime — one that is still running.

The trade is technology. And specifically, it’s Moore’s Law. (I have a soft spot for it, sharing the surname.)

Here’s what was a revelation to me. If you believed in Moore’s Law, you could predict, with some real confidence, where the technology would be in two to five years. Not which company would win or what the killer product would be, but the raw capability of the hardware. Transistor counts, compute per dollar, what a machine could plausibly do. You could see the floor rising on a schedule. And if you could see where the capability would be, you could think clearly about what that capability would make possible.

At the same time I came to understand something that gave the trade a logical foundation: humans are bad at exponential thinking. We are linear thinkers by default. Tell someone a number will double sixteen times and they nod, and then they badly underestimate where it lands. So a market full of linear thinkers will systematically under-price an exponential. This is a structural reason the technology momentum trade could keep working long after it “should” have stopped.

The curve I enjoy arguing with

There’s a second framework I keep coming back to, and I like it precisely because it pushes against the optimism rather than feeding it. The Gartner Hype Cycle, and the S-curve sitting underneath it.

The Hype Cycle is the emotional curve. A technology triggers, expectations rocket to a peak of inflated expectations, reality fails to keep pace, and everyone slides into the trough of disillusionment before the thing quietly climbs the slope of enlightenment to a plateau of productivity. The S-curve is the actual adoption, which starts slow, then steepens, then saturates. It’s the unglamorous reality underneath.

The reason this matters to me is the relationship between the two. The moment the S-curve finally steepens and real adoption happens tends to arrive when the hype curve is at its lowest. The crowd has given up just as the thing is starting to work. It’s the same human flaw as the exponential one, run in reverse. We overestimate what a technology does in two years and underestimate what it does in ten.

So I hold the two frameworks together. Moore’s Law tells me the capability will arrive on schedule. The Hype Cycle tells me the adoption won’t. It says the market mood will run ahead of reality and then collapse beneath it, and that the genuine inflection often comes when everyone has stopped paying attention. Optimism about the destination; discipline about the timing. That’s the framework I enjoy.

Why I’m 100% convinced

I’ll say it plainly: I am 100% convinced AI is going to change everything.

Here’s the specific reason, and it isn’t a bet on some future breakthrough. The models we already have today — never mind the ones coming — are good enough to underwrite five to ten years of productivity gains, breakthrough science, and entirely new business ideas. The capability is already in the building but most of the economy simply hasn’t absorbed it yet. That’s the S-curve point again: the tool works before the adoption catches up. It’s also the argument I made in After the Machines. The change doesn’t arrive as one dramatic event but as a hundred 1% effects compounding quietly across the economy. So even if every model lab stopped today, we’d have a decade of change still to run.

And of course they won’t stop. Moore’s Law may finally have broken, but we have a new version: the scaling laws for AI — more compute, more data, more parameters, predictably better models — which may extend the momentum trade for another decade on top of what we already have. And the trade doesn’t stop at the chips. It runs into the second, third, and fourth-order effects: what cheap intelligence makes possible, what that enables in turn, and what gets built on top of that.

For an angel, the ability to invest in the exponential is the opportunity. That’s the whole game.

The AI future I’m underwriting

Let me sketch the world I’m imagining, because the word that keeps recurring when I do is underwritten. Every part of this future rests on something specific holding up.

Start with AI infrastructure: the data centres, the energy, the chips. It’s the most fascinating area to watch right now, and it’s where the investment dollars are flowing. This is the telecoms layer of the internet boom all over again: the “safe” picks-and-shovels trade, underwritten by the assumption that model capability keeps demanding more compute. But it’s exactly the layer I’m most wary of over-owning, because I’m watching for the multiplex moment. This is the supply-side shock that reprices the infrastructure overnight and shifts the dollars towards the models themselves and the applications on top. I’ve written about that pattern at length in The Multiplex Moment, and it’s the single most important thing I’m holding in mind as the capital pours into the pipes.

And Australia has a real seat at this table through its universities. We are home to some genuinely world-class research institutions, with the ecosystem around them: the research talent, the spinouts, the technology-transfer offices, the founders who come out of a PhD with something defensible. As that ecosystem puts these models to work, compressing research cycles, running experiments that were previously uneconomic, and turning lab capability into companies, I expect the innovation flow to be spectacular. That’s the part of the Australian story I’d back, and it’s where I expect a lot of my own dealflow to come from.

It’s a deliberate contrast with the old story. Australia’s prosperity has always been underwritten by natural resources, and as I argued in Don’t Be Idealistic, I don’t think we work out how to process those metals at home, let alone build a manufacturing industry on top of them. Our Asian neighbours are too hungry, too resourceful, too competitive for us to claw it back. The resource story is structurally stuck. The research-ecosystem story is wide open. I know which one I find more interesting to invest behind.

(And as a footnote on the things that don’t change: Sydney house prices are underwritten by their own momentum trade: high immigration, NIMBY planning rules choking supply, and a beautiful place to live underneath it all. The asset I was bearish on as a young skeptic turned out to be one of the most reliable momentum trades in the country, for reasons that have nothing to do with technology and everything to do with too many people wanting too few homes. Some trades just keep running.)

The live questions I’m chewing on

So what does the AI world look like up close? This is the kind of question I turn over on my walks, where, as I’ve written, most of my investment ideas come from. And it’s where it gets fun, because here I am not 100% convinced of anything. The destination is settled in my mind; the path is wide open, which is exactly what the Hype Cycle would predict. These are grey-scale questions, not binary ones, and my thinking is shaped mostly by listening to podcasts and arguing with myself.

I’ve felt the conviction before, for what it’s worth. In 2000 I was convinced the internet would change everything, and I ended up running an internet business. I was a small part of the change, but had a front-row seat to it. The conviction then attracted more pity than agreement. It feels identical now, and I trust it more for having been right the first time.

Take applications versus god models, whether value accrues to a handful of models that do everything, or to the applications built on top of them. I’m leaning towards applications, because people underestimate how much usability matters. The most capable model in the world is worth little if the thing wrapped around it is hard to use, and usability is unglamorous, hard-won work that the god-model thesis tends to wave away.

Or SaaS versus native AI — whether incumbents bolt AI onto existing software and win on distribution, or AI-native companies rebuild the category from scratch. I’m leaning towards SaaS, or SaaS-plus-AI, winning more often than the disruption narrative suggests. Corporate inertia is enormous and selling into the enterprise is hard, and an incumbent with the customers and the contracts can be slow and still win.

But I might change my mind on both. That’s not me hedging, but the actual state of play, and it’s the part I enjoy most. I’m certain about the destination and genuinely working out the route.

A better seat

Which is why, for all the uncertainty about the route, this is a genuinely fun place to invest from. In semi-retirement, I find myself optimistic, and that turns out to be a better seat than the alternatives.

The fixed-income investor is structurally pessimistic, paid to worry about default. The listed-equity investor lives in the 50/50 world, carrying the anxiety of a coin that might land tails. The angel seat is different. I am resigned to most of my bets losing — that’s the base rate and I’ve made my peace with it — but I can believe the momentum trade will carry some of them a long way. Optimism isn’t a mood I’ve talked myself into. It’s the correct stance for the job. You can’t be a good angel and a permanent bear; the two don’t fit in the same head.

When I look at an angel deal, the optimism shapes the questions I ask. I try to imagine how the company fits into the future. And I often conclude that what the founder is building will exist, and it will be a big opportunity. The thing is real. The space is real.

Which immediately moves my mind to the harder question: why will this founder be the winner? Because there will be competition. The best competitor might not even exist yet. It’ll probably be a fast follower, watching this founder prove the market and then arriving with more capital and fewer scars. So the question underneath the question is whether the founder can grab a piece of the market they can hold and trade from. Believing the thing will exist is the easy part. Believing this particular team captures and defends a slice of it is the work.

One deal at a time

And here’s the part that keeps it honest. I don’t experience this future as a thesis. I experience it as a sequence of deals, arriving one by one, each one a founder executing some small piece of it. A company that processes a metal a new way. A team putting a model to work in a corner of an industry I’d never thought about. The future stops being abstract when it walks through the door asking for a cheque. And the interactions run both ways. Every deal I see sharpens my view of where things are heading, and the sharper view tells me what to look for in the next one. The thinking and the dealflow feed each other.

So that’s the seat. Convinced about where the world is going, curious about how it gets there, optimistic by construction rather than by temperament. After a decade of being paid to find the reasons things break, it turns out being the one who believes is the better job.

If this is the kind of future that interests you and you’d rather spend your time imagining what gets built than cataloguing what might break, you can join MooCoo Ventures and co-invest alongside me. That’s the open invitation. The rest you work out one deal at a time.

Richard Moore — MooCoo Ventures

Richard Moore is co-founder of MooCoo Ventures, an angel syndicate that co-invests alongside Brisbane Angels, one of Australia’s most active angel groups. He has made over eighty personal angel investments since 2013.

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