1. Was one of the first members of the #ai slack channel inviting some people I had in person conversations about AI with.
2. I posted _a lot_ in there. Stuff about regulatory updates, people using co-pilot, cool github repos, little demo projects I was working on.
3. Now this was pure luck and probably the best thing to push me over the boundary, there was a hackathon. I thought "Hmm if I make a kick ass demo showcasing generative AI here, a lot of high up people will see it" - that 100% happened, CTO reached out to me saying demo was great and that people will be in touch.
4. I started really digging in to how I could provide value to our existing data team - be that code, deploying things, bringing some of my engineering know how to that team. This point the #ai channel really started to grow and the head of data and engineering started talking to me and directing people my way based on what they saw at the hackathon.
5. Did a demo of my hack in the company all hands which the CEO was MC'ing.
6. Started having fortnightly 1 to 1s with head of data at this point
7. Floated idea of team taking a little subset of good and motivated people from other teams for a short time to investigate and implement LLMs in some small way into our apps. That team has now grown to effectively investigate any and all use cases (internal and external) for generative AI.
8. I started reading more theory and also following a bit of a road map for things I should learn to have a better picture of how to actually bring LLMs in some form to production (fine-tuning, vector dbs, functions, guard rails).
9. Now I am just building some quick feature in the mobile app to show case the value of the team to exec as quick as I can, which should give us few months cover to work on the thing I am really interested in - multi-arm bandit LLM that uses our existing models.
This was pretty much it. Seems trivial, but in between each points was lots of reading, tinkering, working on weekends, but its totally possible. The ML + AI focused PhD's in your company likely need help from engineering but don't know it - bringing those two groups together quickly shows how you can be useful.
This post was helpful; https://blog.gregbrockman.com/how-i-became-a-machine-learnin...
