Just chatted about the future of molecular modeling and realized we lean too much on automation. AI is powerful, but those “aha” moments from years of intuition still drive breakthroughs. Human‑in‑the‑loop lets us spot patterns, tackle edge cases, and guide data toward creative solutions. How do you balance automation with expertise in your work? 🤔
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@baam93 There's a real tension there between interactivity and applied intuition on one hand and the reliability and reproducibility of automation on the other hand. It's something that ought to be discussed in all branches of computational science.
My take: ideally you want shallow automation and humans-in-the-loop when exploring a scientific question, but full automation for the results that you end up publishing. Unfortunately, the transition is badly supported by available tooling.
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