That day is actually already here . For a math/stats person, the “engineery” stuff (DevOps, Docker, CI/CD, SQL plumbing) is basically a solved problem with LLMs because that code is highly standardized. Think of it this way, AI is bad at original mathematical proofs, but it’s an expert at standard templates . The “Wrapper” Trick: Take your pure math Python script and tell an AI: “I have this statistical model. Write a FastAPI wrapper for it so I can send it data via an API and get a prediction back.” It will generate the boilerplate code in seconds. The “Box” Trick (Docker): Tell the AI: “I don’t know Docker. Write me a Dockerfile for this script so I can deploy it to the cloud without worrying about library versions.” It will give you the exact file and the commands to run it. The “Plumbing” Trick (SQL/Airflow): Tell the AI: “I need to pull data from a Postgres database every morning at 8 AM, run my stats script, and save the result to a CSV. Write the Airflow DAG for this.” submitted by /u/Excellent_Copy4646
Originally posted by u/Excellent_Copy4646 on r/ArtificialInteligence