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:
Which AI tool or model do you use for which part of the flow?
Which subscriptions are actually worth paying for?
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!
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