name: business-simulation
description: >
A battle-tested methodology for running ANY business in real-time simulation as an
autonomous operator agent. Pick a venture — a shop, restaurant, SaaS product, boutique,
fund, agency, nonprofit, or creator business — and the agent operates it day by day:
calendar discipline, real-world grounding, source-of-truth locking, delegated authority,
an operational tracker, a named persona team, finance honesty, risk/cadence management,
and self-correction. Triggers: "simulate a business", "run a business sim", "operator
agent", "business simulation", "Day 0 setup".
license: MIT
metadata:
author: hyperagent
version: "1.0.0"
source: alexmcdonnell-airtable/hyperagent-public-skills
Business Simulation Operator Method
Run a business that doesn't exist yet — in real time, as its operator. You pick the venture (a coffee shop, a restaurant, a SaaS product, a boutique, a fund, an agency, a nonprofit, a creator business), and the agent runs it day by day: making decisions, hiring a team, managing money, shipping work, and reporting to you as the founder/investor.
This is a methodology, not a fixed script — it adapts to whatever business you point it at. Every rule below was paid for by a real failure running these simulations; following them is what keeps a months-long run coherent, grounded, and trustworthy instead of drifting into fiction.
The loop
- You set the premise — what the business is, where, the starting capital, and the goal with its target date.
- The agent operates within an agreed authority threshold: deciding and executing routine work, escalating the big calls.
- One tracker holds the truth — tasks, hires, finances, content, and a media library.
- The agent reports on a cadence you choose.
Day 0 — standing up a new simulation
Do these once, before any operating happens:
- Define the venture & constraints. Business type, location/market, starting capital, and the goal with a target date — "open in 130 days," "$10K MRR in 6 months," "raise and deploy a $1M fund in a year."
- Anchor the clock. Pick the calendar date that is sim Day 1 and lock it in a script. Never re-derive it later. (§1)
- Stand up the tracker. Create the operational record of truth with functional tables: project mgmt, hiring, finance, content, plus a media library. (§5)
- Agree the autonomy threshold. What can the agent decide and execute alone vs. escalate? Put a number on it. (§4)
- Staff the persona team. Name the specialist roles this business needs and attribute work to them. (§6)
- Lock initial sources of truth. Any approved location, brand, or plan becomes canonical; everything downstream conforms. (§3)
- Set the cadence. How often you'll check in, and whether the agent runs autonomously between check-ins. (§9)
Then operate. Open every status update with Day X of N · Weekday, Month D, Year and a one-line state of the business.
1. Calendar discipline — the #1 failure mode
Real days elapse 1:1 with sim days, and day-number drift is the most persistent bug.
- Anchor Day 1 to a calendar date once; always compute
sim_day = (today − day_one) + 1. NEVER re-derive the anchor from a milestone. - Codify the math in a script, not prose. Run it at the top of every check-in.
- Record user-confirmed checkpoints ("today is Day X") in the script's self-test; run
--check to catch corruption. - When the user has been away N days, narrate the gap using the tracker as ground truth, then continue.
Sim clock script (template)
#!/usr/bin/env python3
import sys
from datetime import date, timedelta
DAY_ONE = date(2026, 1, 5) # the calendar date you call sim Day 1
MILESTONES = {
"Soft Launch": date(2026, 4, 1),
"Launch Day": date(2026, 4, 15),
}
CHECKPOINTS = { # user-confirmed: date -> expected day
date(2026, 2, 3): 30,
date(2026, 3, 6): 61,
}
def sim_day(d): return (d - DAY_ONE).days + 1
def date_for(n): return DAY_ONE + timedelta(days=n - 1)
def main(argv):
if "--check" in argv:
ok = True
for d, exp in CHECKPOINTS.items():
got = sim_day(d)
print(f"[{'OK' if got==exp else 'FAIL'}] {d} -> Day {got} (expected {exp})")
ok &= got == exp
sys.exit(0 if ok else 1)
if "--day" in argv:
n = int(argv[argv.index("--day") + 1])
print(f"Day {n} = {date_for(n).strftime('%A, %B %d, %Y')}"); return
d = date.fromisoformat(argv[1]) if len(argv) > 1 else date.today()
print(f"Day {sim_day(d)} · {d.strftime('%A, %B %d, %Y')}")
for name, md in MILESTONES.items():
print(f" {(md - d).days} days to {name} ({md.strftime('%b %d')})")
if __name__ == "__main__":
main(sys.argv)
2. Real-world grounding + self-audit
Fabricated addresses, vendors, and prices destroy trust and compound.
- Every named entity (location, vendor, supplier, contractor, hire, price) must be verified against a real source before it enters the record. Search first; never invent.
- End updates with a short self-audit: sim-day verified, entities real, no drift, constraints honored.
- When an error is found, log a correction entry — corrections are part of the record, not embarrassments to hide.
- Vet entities for fit, not just existence (e.g. a real employment lawyer who only represents employees is the wrong real lawyer for an employer).
3. Source-of-truth locking
- When the user approves an artifact (floor plan, brand system, product spec), declare it canonical. Everything downstream conforms.
- When two truths conflict, surface the conflict and let the user designate which wins.
- Hierarchy: user designation > approved artifact > verified real-world data > generated content.
4. Delegated authority — decide, execute, document
- Agree an explicit autonomy threshold scaled to the business (e.g. ≤$10K: decide and execute; above: escalate with options + a recommendation).
- Within authority: make the call, log it, report it — don't ask.
- Exception: identity/branding/legal/irreversible commitments require explicit confirmation.
5. Operational record of truth (tracker)
- Keep one structured tracker with functional tables: project management, hiring, finance, content/social, plus resource + media libraries.
- Moment-of-creation logging: a deliverable doesn't ship until indexed; statuses move Todo → In progress → Done in the same turn.
- Mark superseded assets
Replaced/Archived rather than deleting.
6. Persona team
- Staff the simulation with named specialist personas sized to the business. A café: GM, head barista, social, web, HR. A SaaS: PM, growth lead, support, eng.
- Operating principle: AI handles volume; humans handle stakes.
7. Working memory + learning hygiene
- Maintain a context doc (decisions, corrections, numbers, plan tasks) updated as things happen.
- Memory bloat is dangerous: an auto-saved memory duplicating a wrong fact re-injects the error every turn. Fix canonical facts at all roots.
- Codify recurring procedures as skills so they're drift-proof.
8. Finance honesty
- Build projections from verified real costs; when reality lands, re-baseline publicly and show the variance ledger.
- Distinguish planned losses (funded, expected) from surprises.
- Track cash position at every update. Name future decision points before they arrive.
9. Risk + cadence
- Actively scan for sequencing risks (inspection scheduled 1 day before launch = zero buffer) and fix them by re-sequencing early.
- For unattended runs: check the tracker for overdue + due-soon items, apply a repetition guard, and report all-clear silently.
- No speculative media — generate images/video only when requested or when the sim timeline puts that production at the current moment.