That's what I hear! It'll be my first time seeing them so looking forward to it!

That is when it all begins again which is the true iterative product development cycle of data science in real life.

Once you deliver your solution to great success and everyone owes you one everyone now has confidence in you and learned from your example with the sureness that they can now implement your ways into theirs and be even faster next time.

That is the crucial moment to rise up to the occasion and deliver your value to build confidence with your stakeholders, which only is possible if you haven't been sitting on your hands while everyone was busy playing with shit on the wall.

Too often it seems more business savvy to throw piles and piles of shit at the wall over a quarter instead of the sound data approach and for people to finally come ask for your way when they truly have burned your runway leaving you little leeway for your mistakes.

When you can throw shit at the wall in a week, your estimates that suggest your solution will take about a month or quarter often makes people think that you're too academic and slow.

Next you deal with the velocity issues because often people confuse an iterative process with throwing shit at the wall. Yes throwing shit at the wall is very quick, much quicker than what you can offer.

And yes unlike a simple logic assumption that you hope works, a testable hypothesis can be validated.

In fact the reason they need your services is the code complex problem they're facing cannot be solved with some smart hack, but with a methodical and meaningful model that needs to be designed, developed, and validated.

They expect it should be just as quick as their failed attempt if not quicker through AI sorcery. So a lot of your valuable time is explaining to them you're not some omniscient superpower.