CashMonty
12K posts
CashMonty
@CashMontee
Mortgage Guy turned degen - follow me for opinions on things that don't matter and losing trades
Really enjoyed the deck @loganbartlett and team just shared on the state of Software, wanted to pull out a few things that caught my eye: 1. AI-native companies are growing faster AND more efficiently The growth rates are really staggering. And they’re doing it with very few people. The demand for AI is insatiable, like nothing we have ever seen, and is diverting budget away from traditional software. This is an existential moment for the incumbents. I’ve been saying Accelerate or Die for months. The accelerating is unprecedented, and the growth is coming at the expense of SaaS 2.0. Only death can pay for life 2. They’re doing it without going head-to-head with incumbents This is probably the most interesting slide to me. These AI-native businesses are growing so fast by using two approaches: A) Finding a wedge into the enterprise, scaling quickly, then trying to expand B) Building AI-native Systems of Record from below. @arampell calls this “Greenfield Bingo.” New businesses/SMB have zero/low switching costs, so AI-native CRM/HR/ERP companies can take share and march upmarket from below Both of these are particularly tricky for incumbents to defend against. They simply aren’t able to move quickly enough to build compelling AI point solutions, and they’re struggling to defend downmarket while also defending the enterprise (bimodal go-to-market and running multiple service models in one company is incredibly difficult) 3. Incumbents scale by throwing people at the problem This has been the dirty little secret of SaaS for 15 years. It’s basically impossible to grow revenue faster than headcount. Some companies like Shopify did it by layering on payments. Consumption-based companies have been doing it. The AI native companies have this figured out. The incumbent, seat-based, companies simply have never been able to decouple revenue from headcount. They will have to learn or die 4. Incumbents have the right to win but they are failing to capture the moment As I’ve said before, the CIO wants to stick with their current vendors. They WANT to buy AI solutions from the incumbents. The problem is their solutions suck. @jasonlk has been all over this. These incumbents have a shrinking window of time where they have the advantage, but that window is shrinking. Rapidly.
The Sharpe ratio and equity curve smoothness are the clearest signs this wouldn’t survive live trading or even out-of-sample testing. I’d start with looking into Look-ahead bias. This is when your backtest uses information that wouldn’t have been available at the moment the trade was supposed to be placed. E.g. if your code defines the range using the completed candle but enters the trade at the start of that candle, you’re “cheating” because you knew the high/low before it happened. That being said: Backtests are very tricky, mainly due to path dependence which means your results aren’t just about whether your strategy works. The same strategy, with the same win rate and same average trade, can produce wildly different outcomes depending on the order those trades occur in. Hope this helps!
Jeff Park (@dgt10011) lays out his Radical Portfolio Theory.