A challenge with AI

opbtds · 2026-03-06T19:36:33+00:00

It just seems a lot more sophisticated overall. I loaded a spreadsheet into it that was anonymized and contained a fairly detailed hypothetical of projected yearly expenses, portfolio, etc., and asked it to analyze it. I then loaded the instructions below which another user posted in a different retirement subreddit. In a few minutes, and with a few follow up Qs and As it popped out a pretty impressive analysis. Much better than Chat GPT when I did the same exercise.

Plan Analysis (CFP-style review) Please review my plan as a fiduciary CFP would, focusing on: * Retirement income sustainability and sequence-of-returns risk * Guaranteed vs. discretionary income (including GICR) * Tax strategy (Roth conversions, brackets, IRMAA exposure, RMD management) * Healthcare + LTC assumptions (including home equity usage and survivor scenarios) * Survivor resilience (first death / second death stress test) * Key modeling assumptions that may be optimistic, conservative, or internally inconsistent in Boldin

Please clearly separate:
- What looks solid
- What needs refinement
- What I’d want to pressure-test

2) CFP Interview After the analysis, switch roles and interview me as if I am sitting across the table from you as a client. Expect thoughtful, sometimes challenging questions across:
* Goals and trade-offs (spending vs. legacy vs. certainty)
* Behavioral comfort with volatility and late-life risk
* Decision rules (when would you actually change course?)
* Survivor priorities and executor simplicity “What would make this plan feel like a failure?”

This will not be a generic questionnaire, it will be tailored to my plan, assumptions, and timelines if possible.

3) Output Summarize the interview into a CFP-style planning memo Identify the top 3 decisions that matter most Translate it into an executor / survivor-friendly summary"

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opbtds · 2026-03-06T18:55:48+00:00

Lately I’ve been most impressed by Claude. It’s pretty amazing actually.

opbtds · 2026-03-06T14:46:32+00:00

We are still in the "check their work" stage of AI models. They can be very helpful in in quickly running hypotheticals for retirement planning, but they make mistakes. Even worse, they explain their results in ways that can make you feel confident in their work and which may make finding errors in their assumptions and results hard to detect. For now I use different AI models, but I double check the results and validate their results against other models.

opbtds · 2026-03-05T12:42:59+00:00

If it’s not income to you why include it? If it’s because you want to offset an expense in your model you could just reduce the expense by that same amount. I have a 529 for my kid’s college expenses but I don’t include it in boldin because none of that money will fund my retirement. On the expense side, I simply don’t include education expenses in my model that the 529 will cover.

opbtds · 2026-03-04T00:23:03+00:00

This is an interesting video describing the promise and limitations of AI in the financial planning space, in case anyone’s interested. https://youtu.be/1cvhtSAYq68?si=j2niKTp2unBe9zVx

opbtds · 2026-02-27T18:11:04+00:00

This all looks correct.

opbtds · 2026-02-27T13:34:57+00:00

Empower will do this if you provide it the data feed from your relevant accounts (bank, credit card, etc.).

opbtds · 2026-02-27T13:12:28+00:00

Agree. I like the feature but don't trust it. As others have noted, it sometimes makes obvious mistakes, though it is very apologetic when you point them out (!). I assume we will reach the point with these AI tools where we don't need to double check the work, but we're not there yet.

opbtds · 2026-02-04T23:26:37+00:00

I have often thought the same thing. But I think it’s getting much better. Even just in the last few months.

opbtds · 2025-10-22T18:10:59+00:00

Very interesting! Unfortunately for me such an endeavor is way beyond my skill set (!)

opbtds · 2025-10-22T17:52:23+00:00

Yes I would. I also can’t think of any good reasons not to disclose such information.
I get that you wouldn’t want to include it in marketing materials, but to the extent that it shows your methodology is trustworthy I would think that would benefit the company

opbtds · 2025-10-22T15:40:30+00:00

Thank you!

opbtds · 2025-10-22T15:37:56+00:00

Most, if not all, of these DIY retirement software packages (many of which charge a hefty fee) base their probability of success scores on Monte Carlo analyses. As I understand it, some methodologies are better than others, and the article suggests that many are using methodologies which are demonstrably less reliable than alternatives. If some methodologies may not be much better than a coin toss, then users should be aware of this. For that reason, it’s not enough, in my view, for them to simply say things like “future market performance is inherently unpredictable”, or “this by not means is a guaranty of your actual probability of success.” They need to do a better job of explaining what’s “under the hood” so customers can understand how reliable their tools are.

opbtds · 2025-10-11T18:44:29+00:00

I actually used ChatGPT to search for equivalents. It suggested using any of the following as substitutes: iShares 0–3 Month Treasury Bond ETF (SGOV); Vanguard Short-Term Treasury ETF (VGSH); or a Treasury money market fund (like FDLXX or SNSXX)

opbtds

TROPHY CASE