Layering Scenarios with experiments (explorers and AI)
I’m having some trouble figuring out the best way to work with Boldin.
Is the best approach to start with a very basic retirement plan and save that as my baseline, then test major decisions one at a time — things like windfalls, Roth conversion strategies, and Social Security timing?
For example:
- Build and save a baseline
- Run the Roth Explorer on that baseline
- Decide whether to apply or disregard the recommendation
- Then move on to another variable or experiment
But this is where I get confused: wouldn’t I need to duplicate the baseline before applying any Explorer recommendation? Otherwise, if I apply the Roth Explorer changes directly to the baseline, I’ve now changed my baseline.
So would the workflow really be more like:
- Baseline
- Duplicate baseline → run/apply Roth Explorer → save as Roth scenario
- Duplicate baseline → test Social Security strategy → save as SS scenario
- Duplicate baseline → test windfall or other assumptions
- Then create additional scenarios combining the strategies that look promising
Basically, I’m trying to build the plan out in layers so I can understand what each decision is actually doing, rather than changing five things at once and losing track of what caused the result.
For those of you who use Boldin this way, what’s the best workflow between the AI tools, Explorers, and saved Scenarios?
How do you go from a basic baseline to a more fully optimized retirement plan without making the model too complicated to understand?