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The Rise of the AI Engineer

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  • Jun 30, 2023
  • #ArtificialIntelligence
swyx.ai
@swyx
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www.latent.space
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I take this seriously and literally. I think it is a full time job. I think software engineering will spawn a new subdiscipline, specializing in applications of AI and wielding the... Show More

I take this seriously and literally. I think it is a full time job. I think software engineering will spawn a new subdiscipline, specializing in applications of AI and wielding the emerging stack effectively, just as “site reliability engineer”, “devops engineer”, “data engineer” and “analytics engineer” emerged.

The emerging (and least cringe) version of this role seems to be: AI Engineer.

Every startup I know of has some kind of #discuss-ai Slack channel. Those channels will turn from informal groups into formal teams, as Amplitude, Replit and Notion have done. The thousands of Software Engineers working on productionizing AI APIs and OSS models, whether on company time or on nights and weekends, in corporate Slacks or indie Discords, will professionalize and converge on a title - the AI Engineer. This will likely be the highest-demand engineering job of the decade.

AI Engineers can be found everywhere from the largest companies like Microsoft and Google, to leading edge startups like Figma (via Diagram acquisition), Vercel (eg Hassan El Mghari’s viral RoomGPT) and Notion (eg Ivan Zhao and Simon Last with Notion AI) to independent hackers like Simon Willison, Pieter Levels (of Photo/InteriorAI) and Riley Goodside (now at Scale AI). They are making $300k/yr doing prompt engineering at Anthropic and $900k building software at OpenAI. They are spending free weekends hacking on ideas at AGI House and sharing tips on /r/LocalLLaMA2. What is common among them all is they are taking AI advancements and shaping them into real products used by millions, virtually overnight.

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Andrej Karpathy @karpathy · Jun 30, 2023
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I think this is mostly right. - LLMs created a whole new layer of abstraction and profession. - I've so far called this role "Prompt Engineer" but agree it is misleading. It's not just prompting alone, there's a lot of glue code/infra around it. Maybe "AI Engineer" is ~usable, though it takes something a bit too specific and makes it a bit too broad. - ML people train algorithms/networks, usually from scratch, usually at lower capability. - LLM training is becoming sufficently different from ML because of its systems-heavy workloads, and is also splitting off into a new kind of role, focused on very large scale training of transformers on supercomputers. - In numbers, there's probably going to be significantly more AI Engineers than there are ML engineers / LLM engineers. - One can be quite successful in this role without ever training anything. - I don't fully follow the Software 1.0/2.0 framing. Software 3.0 (imo ~prompting LLMs) is amusing because prompts are human-designed "code", but in English, and interpreted by an LLM (itself now a Software 2.0 artifact). AI Engineers simultaneously program in all 3 paradigms. It's a bit 😵‍💫
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