You can’t predict a coin flip because it is random. However, we have an accurate understanding of the random process producing coin flips and therefore, we can make accurate predictions about large quantities of flips.
Weather may or may not be random. It could be entirely deterministic for all we know. However, we lack the ability to fully model all the factors that contribute to weather and therefore our predictions are inaccurate.
Now let’s consider long term climate predications. Do you think these predictions are more like coin flips, where we have an extremely accurate model of the process, or more like weather, where unknown unknowns have outsized impact on accuracy?
That’s not to say climate change isn’t real, but your analogy doesn’t make sense.
It’s fine to disagree with my analogy. But I find it a little ironic your dismissal of the analogy is a non sequitur. The invalidness of the analogy doesn’t directly follow, logically, from the fact that the written word and the spoken word are both mediums.
Isn’t a better question: why would they migrate off COBOL? Their business is working. What’s the impetus to change? It’s not like they need to use COBOL for every new project.
> Are you proposing that an LLM can extract some meaning from your initial prompt that a human being couldn't?
No, I’m asserting that an LLM can help formulate ideas in a coherent, understandable way. You can give it a brain dump with a rough outline for an argument and it fill in the details. If the argument isn’t to your liking, you can try again. But the end result is basically equivalent to the human-written equivalent.
I disagree. The purpose of writing is to convey ideas. If written language had just been invented, I’m sure you’d be saying “IMO any important stories you expect others to know should be communicated orally. It’s kind of disrespectful to convey stories as if they were hearing you speak.”
But a query optimizer only matters once you have an established business with large customers.
You seem to be implying Salesforce’s business is successful because they have their own query optimizer. But the causality is reversed. Salesforce has their own query optimizer because they’ve built a successful business.
Your friends don’t produce much content yet people had a need for frequent entertainment. Also, people realized that posting things to social media meant that it was there forever. This led to a bifurcation: friends / family updates are mostly relegated to temporary formats like stories while “feed” content is professional produced.
You should feel that C’s longevity is insane. How many languages have come and gone in the meantime? C is truly an impressive language that profoundly moved humanity forward. If that’s not insane (used colloquially) to you, then what is?
Many of the built-in types in Objective C all have names beginning with “NS” like “NSString”. The NS stands for NeXTSTEP. I always found it insane that so many years later, every iPhone on Earth was running software written in a language released in the 80s. It’s definitely a weird language, but really quite pleasant once you get used to it, especially compared to other languages from the same time period. It’s truly remarkable they made something with such staying power.
I think that’s different. You have a problem: invoice management. LLMs have made that cheaper and you should expect disruption. But you’re not building your own invoice scanner. You’re using another, cheaper product on the market.
However, the hypothesis in the SaaS market is that LLMs have made software have zero value and therefore the SaaS companies will be less profitable. That’s like if wood was suddenly free, expecting home builders to go out of business. If anything, home builders are going to do better, because they can apply their expertise while deploying capital elsewhere. We should expect software companies to be more profitable, not less.
Of course, there are exceptions. Sometimes AI replaces the product itself, e.g. image generation models vs. contractors on fiverr.
It’s worth asking: what do Wall Street traders know about building software companies? Almost nothing. Anyone who has attempted to start a startup knows that the software is always the easy part. Building the business is hard. The notion that we’re going to undo 100K+ years of specialization just so that companies can run mediocre, buggy versions of SaaS tools just to save a few bucks is crazy to me.
SaaS stocks are currently the buying opportunity of a lifetime.
You look at what Claude’s doing to make sure it doesn’t go off the rails? Personally, I either move on to another ask in parallel or just read my phone. Trying to catch things by manually looking at its output doesn’t seem like a recipe for success.