I build ML, RecSys, and LLM systems that serve customers at scale, and write about what I learn along the way. Join 7,500+ subscribers!
What We’ve Learned From A Year of Building with LLMs
|
Hey friends, Recently a couple of friends and I got together to write about some challenges and hard-won lessons from a year of building with LLMs. One thing led to another and this is now published on O'Reilly in three sections:
We have a dedicated site with all 42 lessons https://applied-llms.org/ and a job board with vetted jobs: https://applied-llms.org/jobs (get 20% off with discount code "2B212D9F"). While I'd typically paste the content here so you can read it from the convenience of your inbox, the current piece is long and probably best read in your browser. Nonetheless, here's the behind the scenes of how this started. I hope you find our writeup useful! |
Eugene Yan
I build ML, RecSys, and LLM systems that serve customers at scale, and write about what I learn along the way. Join 7,500+ subscribers!
Hey friends, How can we work effectively with AI? What’s the workflow and how does it scale? And ideally, it should compound. Every finished artifact—code, docs, analysis, decisions—becomes context for the next session. And each correction updates a config that reduces future errors. While I’m still learning, I’ve repeated my answers often enough that I’m writing it here so the next time I’m asked I can share a link instead. I appreciate you receiving this, but if you want to stop, simply...
Hey friends, After repeating myself for the nth time on how to build product evals, I figured I should write it down. There are three basic steps: (i) labeling a small dataset, (ii) aligning our LLM evaluators, and (iii) running the experiment + evaluation harness with each config change. I appreciate you receiving this, but if you want to stop, simply unsubscribe. • • • 👉 Read in browser for best experience (web version has extras & images) 👈 First, label some data It begins with sampling...
Hey friends, What makes an effective principal engineer or scientist? I’ve distilled what I’ve observed from role models and quoted some of their advice below. While my perspective is Amazon-centric, these ideas should also apply to most principal tech IC roles. As always, use your best judgment and assess if this advice applies to you and your situation. I appreciate you receiving this, but if you want to stop, simply unsubscribe. 👉 Read in browser for best experience (web version has extras...