I was tidying my books late one evening when I noticed how long my subscription statement had become. Editor, AI coding environment, metered API usage — I felt like I was using all of them, yet I had never once counted which ones were actually paying for themselves.
This article is the record of that inventory. Instead of comparing Antigravity, Cursor, and Bolt on features, I look at a single question: how many saved hours does it take to pay back the monthly fee?
One caveat up front. The efficiency differences below are my impressions, not measurements. Pricing also keeps changing, so I won't quote amounts — I'll leave you a way to work them out from your own numbers.
Read pricing by how it grows, not by the sticker
Before asking which plan is cheaper, I check how the bill behaves when you use the tool heavily.
- Close to fixed cost: heavy use barely moves the bill, so the budget is predictable.
- Metered usage mixed in: the bill varies by month and jumps in heavy months.
- Tiers driven by counts or capacity: you look up one day and you're on the next plan.
Which product falls into which bucket can change with every pricing update. So open each official pricing page and classify it yourself — it takes five minutes.
I once left an agent running for hours without a usage cap and froze when the next invoice arrived. Since then my rule is: any environment with metered usage gets a spend alert before I use it seriously.
The metric changes with the kind of work
The same tool "pays back" differently depending on where you use it. I split my work into three.
Client projects: time to delivery maps directly to income. An environment that can plan and carry out changes across many files helped most when I inherited an existing codebase. For daily implementation, tests, and small fixes, editor responsiveness and stable completion add up quietly instead.
Maintaining my own apps: what matters is understanding the whole codebase and keeping changes consistent. For a long-running product like a wallpaper app, not breaking existing behavior is worth more than shipping something new.
Prototypes and demos: speed is everything. A browser-based generator was a good fit for having something running before the next day's meeting. The catch is the move to another environment once a prototype grows into the real thing.
What I realized is that "which one is best?" was the wrong question. Choose your main tool by the weight of this month's work, not by a ranking — that is the line I draw.
Work out break-even with your own numbers
How do I check whether a fee is paying back? I put my figures into this short script.
It answers one thing: how many hours per month must a tool save before it covers its cost, stated as numbers instead of a feeling.
# breakeven.py — how many saved hours per month cover a tool's fee
# Replace every number with your own records (values below are examples)
def breakeven_hours(monthly_cost: float, hourly_rate: float) -> float:
"""Hours per month you must save to cover the fee."""
return monthly_cost / hourly_rate
def monthly_net(saved_hours: float, hourly_rate: float, monthly_cost: float) -> float:
"""Value of saved time minus the tool fee, per month."""
return saved_hours * hourly_rate - monthly_cost
if __name__ == "__main__":
hourly_rate = 40.0 # your effective hourly rate: total earned / total hours worked, not a quoted rate
tools = {
"Tool A": {"cost": 60.0, "saved_hours": 10}, # monthly fee and *measured* saved hours
"Tool B": {"cost": 30.0, "saved_hours": 4},
"Tool C": {"cost": 30.0, "saved_hours": 0.5},
}
for name, t in tools.items():
be = breakeven_hours(t["cost"], hourly_rate)
net = monthly_net(t["saved_hours"], hourly_rate, t["cost"])
verdict = "paying back" if net > 0 else "review it"
print(f"{name}: break-even {be:.1f} h/mo / measured {t['saved_hours']} h / net {net:,.0f} -> {verdict}")I restrict saved_hours to measured values on purpose. If you guess, every tool comes out profitable. A timer or your commit history is enough: compare against how long the same kind of task took before.
Use an effective rate — total earned divided by total hours worked — rather than your quoted rate. A quoted rate leaves out sales and meeting time, and makes payback look better than it is.
What surprised me most when I tried it: a rarely used plan fell straight into "review it" the moment I entered a measured number. I had an environment I'd barely opened.
A rough split when you use more than one
When I combine tools, I assign roles like this. It fits my way of working, so treat it as a starting draft.
Main tool : the one I touch every day (daily coding, tests, small fixes)
For big changes : used a few times a month for multi-file changes or redesigns
For prototypes : used before client meetings or to test a new ideaFor tools I only use a few days a month, a monthly plan is lighter than an annual one, because I can downgrade or cancel in quiet months. For the main tool I touch daily, switching to annual billing is often cheaper when it's offered (check the official discount).
The hidden cost of switching
Easy to overlook is what a switch actually costs.
- Relearning keybindings and feel, with lower output until you adapt
- Rebuilding per-project setup such as linting, debugging, and hooks
- Moving over prompts and rule files you've polished for yourself
The third grows with everything you've accumulated. When I consider switching, I trial the new environment for one month on a small new project. I don't let go of my current main tool until the new one has a track record. That's another line I draw.
If you can only pick one
My order of questions, for those who can't afford to combine:
- What takes up more than half of this month's work — daily implementation, large changes, or prototypes?
- In that kind of work, which environment showed the largest saved hours in the script above?
- Can you put a spend cap on its billing?
If the answer to the third is no, I'd hesitate to make it your main tool.
If you plan to work in a team, license and sharing terms are set separately from individual plans. Checking the official team plan conditions before headcount grows spares you a migration later.
This week
Once you close this page, write down what you pay each month and how many days you actually used each tool in the past month. Then enter your figures in the script and see whether anything lands in "review it."
I've come to feel that counting your own statement once gives a far more reliable answer than reading yet another comparison article.
For a related angle, see Antigravity vs Cursor vs Bolt: a production decision.