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You’re absolutely right that no model - event-based or spreadsheet - is ever “correct.” Dozens of variables, time lags, and external factors make precision impo

You’re absolutely right that no model - event-based or spreadsheet - is ever “correct.” Dozens of variables, time lags, and external factors make precision impossible. That’s actually the point. The value isn’t in betting on one forecast, it’s in being able to spin up hundreds of simulations quickly and look for trends. Instead of endless debate over Option A vs. B vs. C, you run them all. If 80% of scenarios show the Vancouver office underwater in Q1, that’s a signal worth digging into. If it only shows up in 20%, you know not to over-index on it. It’s less about false precision and more about identifying patterns of risk and opportunity across a range of possibilities.

gobdovan 1y ago
That's pretty cool. I checked the demo of whatifi, I now see what you are trying to do. Not that PnL is bad, but you can simulate its evolution by dragging around these events (and probably more advanced stuff I missed). There's no AI that predicts how the events affect the PnL. You specify the events and presumed effects that were in your head anyway and and you just see PnL changes much faster. It did feel like the article compressed that nuance (maybe due to AI-assisted phrasing?), but if not, fair enough! sorry for suggesting it.
- jonnylegs 1y ago
  Thanks! It's really tricky to explain because I'm doing something That's a pretty big departure and language can get so tricky when trying to put a label on something that doesn't really exist or at least is being wrapped up differently than people are used to. I need to update our demo video, but the AI part is being able to structure our event and nodes in a way that we can pass those to the large language model alongside the outputs so that we're not expecting the large language model to do financial calculations -just interpret the inputs and the outputs. A lot of it is turning all that information back into something that people can use. PNL is so standard that it's a good format for most executives. And yes, spent a lot of time bouncing back-and-forth between ChatGPT and custom editing the article. The big goal is taking all of this one step further and using generative AI to actually build the financial models and interact with them. Large language models have a good understanding of core business concepts, and being able to "train" a model to understand, our events means we can map common business concepts to our nodes and build the models for people conversationally. We've got this working under the hood but still have a lot of refining to do before it can be user facing.

gobdovan 1y ago

That's pretty cool. I checked the demo of whatifi, I now see what you are trying to do. Not that PnL is bad, but you can simulate its evolution by dragging around these events (and probably more advanced stuff I missed). There's no AI that predicts how the events affect the PnL. You specify the events and presumed effects that were in your head anyway and and you just see PnL changes much faster. It did feel like the article compressed that nuance (maybe due to AI-assisted phrasing?), but if not, fair enough! sorry for suggesting it.

jonnylegs 1y ago
Thanks! It's really tricky to explain because I'm doing something That's a pretty big departure and language can get so tricky when trying to put a label on something that doesn't really exist or at least is being wrapped up differently than people are used to. I need to update our demo video, but the AI part is being able to structure our event and nodes in a way that we can pass those to the large language model alongside the outputs so that we're not expecting the large language model to do financial calculations -just interpret the inputs and the outputs. A lot of it is turning all that information back into something that people can use. PNL is so standard that it's a good format for most executives. And yes, spent a lot of time bouncing back-and-forth between ChatGPT and custom editing the article. The big goal is taking all of this one step further and using generative AI to actually build the financial models and interact with them. Large language models have a good understanding of core business concepts, and being able to "train" a model to understand, our events means we can map common business concepts to our nodes and build the models for people conversationally. We've got this working under the hood but still have a lot of refining to do before it can be user facing.