How LinkedIn Feed Uses LLMs to Serve 1.3 Billion Users
Intriguing use of LLM embeddings to link member data and post together for super-fast retrieval in social feeds. And, of course, the use of LLM as semantic search layer is 🆒
Intriguing use of LLM embeddings to link member data and post together for super-fast retrieval in social feeds. And, of course, the use of LLM as semantic search layer is 🆒
Didn’t know GitHub was in such dire waters. But TBH I like Copilot.
Certainty in uncertain times goes a long way in approaching touch situations with calm and clarity.
What not to prematurely optimize is one of the most important engineering decisions in system design. Like how Dropbox avoided generating preview thumbnails for all uploaded video/images based on their data-backed insight that most such files will never be viewed in a search result. Saved them both storage and compute costs.
Tap compare, what a clever way to migrate from one tech stack to another in production. Sounds like a beginner interviewer shadowing an experienced one in real interviews.
Development has ground to a halt. The thing is plagued by security issues. As fondly as I remember MySQL from my formative years, the sad reality is it stopped being a viable option soon after its Oracle acquisition. Why Sun, why did you sell yourself?
A good case study in picking just part of an off-the-shelf platform solution and building out the rest based on your org’s unique architecture and constraints. ‘Most important is to stay grounded in real problems rather than chasing architectural trends.’
Add intentional ‘thinking time’ to your workdays. Use it for reflecting on hurdles encountered, measuring the impact of a completed task, and planning for future value creation. Otherwise, all you are doing is keeping the lights on rather than investing in your growth: good for your company, bad for your career.
TIL about Evals, the automated testing analogue to traditional unit/integration tests. Since running LLMs (for evaluation) in CI pipelines isn’t cheap, it’s good to prioritize test scenarios based on top buckets of real-world user issues.
Dr. Gandhi’s piece confirms my prophecy about the AI dust settling by late 2025 or start of 2026. 100% automation shouldn’t be the goal. Human knowledge is priceless (goal mine as per Dr. Gandhi). Rather than replace humans with AI, augment agents with humans for the best outcomes. Good for business, good for humanity.