r/MachineLearning · · 1 min read

How do you split AI models across ideation, math, and coding?[D]

Mirrored from r/MachineLearning for archival readability. Support the source by reading on the original site.

Hi, I'm a freshly graduated (undergrad) guy currently working on 3–4 projects in parallel:

- An AI research project: working on a research problem statement, aiming towards a paper publication

- New corporate work at a product company

- My personal hobby projects

I wanted suggestions from you experienced people on how to accelerate my work and progress. Can you help me design my workflow with AI tools?

My workflow basically includes:

- Brainstorming, ideating, and formulating

- Experimenting, designing, and finding flaws and limitations

- Maths formulation and equations

- Architecture changes and experimenting by writing code

- Designing and maintaining the codebase, and exploring and building on top of it

As of now, a GPT subscription feels pretty much mandatory for me, since I use web ChatGPT, including the Pro model in chat (5x), for ideation, brainstorming, and formulation. I'm also looking at GPT 6 Astra, Claude Opus 5.5, and Claude Fable 5.1, and I'm open to any other recommendations.

For people with similar workflows:

  1. Which AI tool or model do you use for which part of the flow?

  2. Which subscriptions are actually worth paying for?

  3. If you were setting up a stack today for research + engineering + parallel projects, what would it look like?

I'm already very overwhelmed, and kind of anxious and strained, after seeing so many Reddit and X posts and suggestions. Everything feels jumbled up, so I'd really appreciate practical advice on what I should set up.

Thanks in advance!

submitted by /u/sky63_limitless
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