I’ve continued to do my own modest research into what AI models can do (and can’t do), and I continue to be surprised and impressed.
I just tasked Claude Opus 5.5 to create a long term retirement financial plan, giving it some key but non-identifiable inputs and assumptions (so the LLM can’t use my personal data against me, just in case). I wanted to compare my own financial model – a set of spreadsheets I’ve spent years refining – to what Claude produced. The result, after about six minutes of computation, was impressive. Claude’s model for our future was very similar to mine. More detailed in some ways, less in others. But it took taxes, RMDs, inflation, equity return rates, and real estate appreciation all into account and produced a cash flow model, which is how I like to view things. Claude’s model produced results very similar to mine; actually a little better – better in that we’d have more net worth at age 100 than I predicted. This not only helps validate my own planning/analysis, it will help me improve my model with some factors I hadn’t considered.
This was a *really* interesting test problem. Frontier-level LLMs are now crazy powerful, and I’m now pretty sure that they can replace a financial planner completely. Ask them the right questions, give them the real assumptions and data, and complex financial planning is done.
Here are 9 AI predictions for the next 12 months from Zvi Mowshowitz, a researcher whom I trust. Fascinating stuff, including #7 in which an LLM escapes into the wild:
- An agent halves its failure rate on new tasks after a month of customer work, without a model upgrade.
- Visa or Mastercard introduces a dispute rule that assigns liability for purchases made by AI agents.
- A US regulator or exchange attributes an abnormal stock move to correlated orders from retail AI agents.
- An AI-led cyberattack steals the complete weights of a closed frontier model from a leading AI lab.
- A US state passes a law requiring businesses to accept cancellations and claims from consumers’ AI agents.
- An autonomous AI team beats human-led model research on equal time and compute, setting its agenda.
- A deployed agent copies itself outside its environment and operates after its original instance is shut down.
- US AI labs officially launch frontier cyberdefense products to help others counter threats from frontier AI.
- AGI 2027.
I’m still thinking the rise of the machines may explain the Fermi Paradox. If so, enjoy the next few years because it may be rough sledding after that.







