in my experience, most ai projects die before the ai part people hate hiring data engineering (plumbing people feels like cost), and data eng like tools that w

in my experience, most ai projects die before the ai part people hate hiring data engineering (plumbing people feels like cost), and data eng like tools that work but most are.too niche/happypath-oriented, so even w trifacta etc, a lot of open territory. SW can solve a lot of that, in theory, so everyone wins. And I agree that until there is an oss winner, the proprietary stuff will keep getting churned through. So ultimately whatever your data platform does (aws, databrick, whatever) or oss you're bringing. A lot of room for vendors to carve out niches b/c of connectors x use cases, until platforms/oss eats them all. VC's will see some ARR and name brands and thus be happy to fund: a lot of gaps any startup can fill. (I am impressed by airbyte for a few non-technical reasons even without having used it, so not a knock on them, so just some clues for the continuing froth in their market.)