Been hearing this argument more lately. And from a technical capability set, probably true. However, I think this misses the role of Excel in the investing process...Excel is a simple, trusted, mostly bug free, deterministic tool for analyzing historical fundamentals and making forecasts about future fundamentals (where the alpha lives). You be surprised by how simplistic the models of many great investors look, and this reflects the reality that most investments hinge on 2-3 key variables. The model is also a core communication tool. "I'd love to build my models in Python, but my CIO still wants to see the spreadsheet" is a common response. An Excel file can be e-mailed, saved locally on a laptop for mgmt meetings / HQ visits, and very easily validated (your model may be 800 rows, but generally only ~5-10% of the inputs need rigorous triple checking as they could make/break the model output...i.e. 6 year ago Q3 D&A isn't going to make or break a thesis, but a clean properly adjusted year ago gross profit number that aligns with mgmt's soft guide of GM bps trajectory, could). I think some people are also glossing over the fact that IDE to MCP isn't accurate yet. It's better, but multi-document retrieval capabilities are not yet mature. A 70% accurate Excel model is highly frustrating, particularly when you have offloaded the experience of building it and don't have the personal context to debug. In our green/yellow/red light AI tools rubric, coding agent models have shifted from Red light to Yellow light, but won't move to Green light until 95%+ accuracy is achieved. So it's confidence & usability. Spreadsheets aren't perfect, but they don't hallucinate. Analysts aren't perfect, but they triple check and validate the ~5-10% key inputs (or they don't last long). "But analysts make mistakes...". Yes, they do, but great analysts know where model inaccuracy is acceptable / non-core and where an input is mission critical and obsess over checks/validations and a multi-approach modeling structure. Human accuracy in thesis contingent areas of the model, in my experience, is 99.99% (I can only think of one or two brutal thesis-contingent mistakes across 5 firms and both had real career implications for the analyst, and were a very bad look on the PM who should have caught it). And Excel spreadsheets are just intensely useful up, down and across the organization, as the analyst who runs the spreadsheet is rarely the end investment decision maker...the Excel sheet is a thinking tool and a communication tool, above all else. This could change, but requires CIO/PM/MD sponsorship, which I'm not sensing is happening (yet). So, with that context, I'll take the under on the end of spreadsheets (while joyfully experimenting with the new tools...)