Financial Modeling
Someone asks what happens if we hire eight instead of four and push the price up ten percent. The honest answer is that it will take until Thursday, because the model has to be copied, the assumptions unpicked from the formulas, and the outputs re-laid-out. So the question gets answered with a guess, or it gets answered late. Either way the model is not doing the job it exists to do, which is to make a decision cheaper to think about.
A Skynet agent shortens that loop. It builds the scenario from your existing model and your actuals, runs the variants you describe, and shows you the comparison with every assumption stated. When the CEO asks a follow-up, the follow-up is minutes, not another Thursday.
How it works
Ground it in actuals
Connect the ledger and hand over your current model. The agent builds from your real historical performance and your existing structure, so the baseline is your business rather than a template’s idea of one.
State the assumptions out loud
Every driver the agent uses — growth rate, headcount cost, churn, collection timing — is written down explicitly rather than buried in a cell. You can see them, argue with them, and change them.
Run scenarios in plain language
Describe the variant the way you would say it in a meeting. The agent builds it, runs it, and puts the outputs next to the base case with the deltas called out.
Show the sensitivity
The agent identifies which assumptions actually move the outcome and which barely matter. That is usually the more useful output than the number itself — it tells you what to argue about. A model is a set of estimates; the judgment about what to believe stays with you.
Build it from a prompt
Say what you want to compare.
What you get is a model whose assumptions are arguable, because they are visible, and a scenario loop short enough to use during a conversation instead of after one. The numbers still need your judgment. The difference is that you spend your time applying it rather than rebuilding tabs.