jh88

I don't know if there's a great general answer here. We used to make all these decisions pretty much manually. Now we automate some things directly in code. We're far from ML so will deal with it when we get there.

Manually doesn't scale, but also the people who are closest to the customers (operations) usually have most decision-making context anyway.

Tryna build this rn, and this was an incredible resource! Mind if I reach out with some questions?

As private late-stage rounds get larger (funding) and secondary pre-IPO markets emerge (employee liquidity), what incentives do companies have to go public?

Gotcha. Have you exhausted your first and second degree LinkedIn or ex-coworker network? Most of the user interviews I've done (different domain) have stemmed from reaching out to acquaintances, including those I hadn't spoken to in several years. People are usually willing to give you 20 mins of their time.

Based on your needs, might suggest you check out https://lu.ma/ (founder is a friend, so if you want additional support DM me)

Have you read The Mom Test? https://www.amazon.com/Mom-Test-customers-business-everyone/... Also, Rob Fitzpatrick did a youtube series focused on remote interviewing https://www.youtube.com/watch?v=bcWqxq2fJgY&t=1s

Just like with data science, don't we expect data engineering to get to a point where they codify best practices into a tool, so 1x data engineers can be closer to be as effective as 10x data engineers? The amount of data engineering work won't change, but the number of people needed to do it will reduce, reducing the open headcounts.