TWITTER_POST

Nabil Minhaz presents a sharply divided view of AI career progression, claiming…

2026-03-27 · 04:00 UTC ·NabilMinhaz ·1 min read

Brief

Nabil Minhaz presents a sharply divided view of AI career progression, claiming the durable upside is in building model infrastructure rather than merely consuming APIs. He promotes Stanford's free CS336: Language Modeling from Scratch as a path toward that deeper technical track, emphasizing both modeling topics and systems-level engineering such as kernels, parallelism, inference, alignment, and RL.

Source evidence

title: @NabilMinhaz: There are 2 career paths in AI right now: The API Caller: Knows how to use an AP...
author: NabilMinhaz
contenttype: twitterpost
published: 2026-03-27T04:00:03+00:00
source_url: https://x.com/NabilMinhaz/status/2037379096142094549

word_count: 143

Tweet by @NabilMinhaz

There are 2 career paths in AI right now: The API Caller: Knows how to use an API. (Low leverage, first to be automated, $150k salary). The Architect: Knows how to build the API. (High leverage, builds the tools, $500k+ salary). Bootcamps train you to be an API Caller. This free 17-video Stanford course trains you to be an Architect. It's CS336: Language Modeling from Scratch. The syllabus is pure signal, no noise: ➡️ Data Collection & Curation (Lec 13-14) ➡️ Building Transformers & MoE (Lec 3-4) ➡️ Making it fast (Lec 5-8: GPUs, Kernels, Parallelism) ➡️ Making it work (Lec 10: Inference) ➡️ Making it smart (Lec 15-17: Alignment & RL) Choose your path. (I will put the playlist in the comments.) ♻️ Repost to save someone $$$ and a lot of confusion. ✔️ You can follow @NabilMinhaz , for more insights.

Posted: 2026-03-27T04:00:03.000Z
Engagement: 1555 likes, 280 retweets, 39 replies