Examples
Real scenarios, real predictions.
A sample of what MiroFish gives back when you describe a scenario. Each one is a prediction — a weighted set of outcomes, not a single answer. Tap any example to predict your own version.
“Predict what happens if I quit my $120k job to go full-time on my side project with 10 months of runway.”
MiroFish predicts three main paths. Base case (~50%): the project reaches ~$4k MRR by month 8 — not enough to replace income, forcing a part-time job or a raise. Upside (~25%): an early channel compounds and you clear ramen-profitable by month 6. Downside (~25%): runway runs out before product-market fit. The deciding factor isn't the runway length — it's whether you already have a repeatable way to reach the first 50 customers.
“We're raising prices 15% on our 800 mid-market customers. Predict the churn-adjusted revenue impact over 12 months.”
Predicted net revenue rises 9–12% in the base case as added per-seat revenue outweighs a 3–5% churn bump concentrated in your lowest-engagement accounts. The sensitivity factor is usage, not price: heavy users barely flinch, light users leave. The signal to watch is support-ticket sentiment in the two weeks after the change.
“Predict whether relocating from Chicago to Lisbon for my partner's role works out for both of us.”
The prediction hinges less on cost-of-living math (which pencils out) and more on whether you can rebuild remote or local work within ~6 months. Base case: a rocky first quarter, stabilizing by month 9. The most sensitive variable is your own income continuity — predictions where that's solved before the move land in the good branch far more often.
“Will our $49/mo tool land in a crowded category? Predict the first 90 days.”
MiroFish predicts a slow-burn base case: 40–90 signups in 90 days, 8–15% converting to paid, unless one differentiator gets a foothold in a niche. The deciding factor is positioning sharpness, not feature count. The tripwire: if week-2 activation is below 35%, the prediction shifts toward the stall branch.
“Predict the outcome of hiring a senior eng who's brilliant but a known culture risk.”
The prediction splits hard on one factor: whether they report into a manager who sets norms or onto a flat team. With strong management, base case is a 2–3x output bump and contained friction. Without it, the predicted downside — two quiet departures within six months — carries enough weight to dominate the expected value.
“Predict how the market reacts to our competitor's surprise acquisition announcement.”
MiroFish predicts a short-lived sentiment swing rather than a structural shift: attention spikes for ~2 weeks, then reverts unless integration stumbles publicly. The most sensitive factor is whether your shared customers perceive lock-in risk — that's the branch worth watching, via win/loss notes, not the stock chart.
“Predict my financial position in five years if I max retirement contributions vs. paying down a 6% mortgage early.”
Predicted net-worth paths are closer than they feel emotionally. The base case slightly favors investing given the rate spread, but the prediction is highly sensitive to one assumption — your actual realized return — which is exactly the variable you can't control. The signal: if rates climb past your expected return, the branches cross.
“My cofounder and I disagree on direction. Predict how the next six months go if we don't realign.”
MiroFish predicts decision latency, not a clean break, as the base case: shipping slows, the team senses the rift, and one of you disengages by month 5. The deciding factor is whether a forcing function (a board, a fundraise, a deadline) lands before the drift hardens. The tripwire is meeting tone — when debates stop, that's the bad branch arriving quietly.
Have a scenario of your own?
Describe your scenario and MiroFish predicts the likely outcomes — with probabilities and the reasoning behind each one.