This argument gets thrown at consumer / prosumer startups all the time. IMO, it’s almost always deeply flawed. Here’s why: - Products that feel magical might seem easy to use, but they are almost never easy to build. There is a lot of thought and craft that goes into them. You can reverse engineer the product but not the intuition behind it. This will keep the startup’s product ahead of the game - If a bigco could do it, they would have done it. I have seen many cases of a bigco attempting to replicate what seems like a “thin” product and failing to the degree that it never even ships. To the Siri example - we’ve been talking about a functional Siri for 15 years, and for three years now post-LLMs. Apple has 170k engineers and a $4.5T market cap…if it was easy to fix Siri, they would have fixed Siri - Turning a large boat is hard. Sometimes, fixing or improving a legacy product isn’t actually about the technical complexity of doing so. Large companies have infinitely more bureaucratic hurdles and political battles that prevent progress. They also have existing business lines that they need to be careful about cannibalizing, especially when they are accountable to quarterly earnings reports. Google has a whole army of VPs holding back innovation 😂 - Big companies are stuck in their existing product interfaces. When you have 100M users on your product, changing how something little works in that product - or even introducing something new - is a big deal (which, to the point above, could mess up those numbers you’re responsible for!) The risk of screwing up something that is technically “working” at major scale is often not worth it. They are also stuck in their existing operating systems - whereas a startup can ship a product or feature that is device / OS-agnostic. Apple is unlikely to build a Wispr Flow clone that works on Android - so if you have an Apple laptop and a Google phone, you’re out of luck - New products can achieve lock-in before incumbents catch up. This is especially true for product with network effects or compounding data advantages. Say Apple did perfectly replicate Granola tomorrow. I already have 2.5+ years of very valuable meeting data stored there, and it has context on me that is not transferable or ingestible by Apple. If you’re asking “what if X big co builds this….” the startup product usually has enough psychological, behavioral, or contextual loyalty that it is too late to just rip and replace it