StratCraft

The Same Strategy.
Four Generations.
See the Difference.

Moving Average Crossover with stop-loss and position sizing — implemented four times, from a 1990s scripted signal tool to an AI-generated StratCraft strategy. The logic never changes. The cost of implementation does.

See the Code ↓
Gen 3.5AI-Native Era
StratCraft Natural Language → AIWe Are Here
User prompt to StratCraft:

"Create a Moving Average Crossover strategy for SPY on daily bars.
Buy when the 20-period SMA crosses above the 50-period SMA.
Sell when it crosses below. Apply a 1% stop-loss per trade.
Risk 2% of portfolio per position. Run a full backtest from 2020."
StratCraft generates:
# Generated by StratCraft AI — do not edit manually
# Strategy: MA Crossover SPY Daily | Generated: [timestamp]

from stratcraft.core import Strategy, Signal, RiskModel

class MACrossover(Strategy):
    fast_period: int = 20
    slow_period: int = 50
    stop_loss_pct: float = 0.01
    risk_per_trade: float = 0.02

    def on_bar(self, ctx):
        fast = ctx.sma(self.fast_period)
        slow = ctx.sma(self.slow_period)

        if ctx.cross_above(fast, slow):
            size = ctx.risk_size(self.risk_per_trade, self.stop_loss_pct)
            ctx.buy(size, stop=ctx.price * (1 - self.stop_loss_pct))

        elif ctx.cross_below(fast, slow):
            ctx.close_all()
Lines of Code (human)
6 lines
Time to Backtest
< 5 minutes
Expertise Required
None
Runs Locally
Yes — your machine only

You described the logic. StratCraft wrote the code, validated it, and ran the backtest. Strategy never left your machine.

The Numbers, Side by Side

Gen 1Gen 2Gen 3Gen 3.5
Lines written by human~30~55~506 (natural language)
Setup time1–2 hrs4–8 hrs1–3 weeks< 5 min
Dynamic position sizingNoManualPlatform APIAuto-generated
Runs locallyYesYesNo (cloud)Yes
IP stays on your machineYesYesNoYes
Expert coding requiredYesYesYesNo

What the Code Tells You

1

The logic never changed. Moving Average Crossover with stop-loss and position sizing is the same strategy in all four generations. What changed is how much engineering you need to express it.

2

Gen 3 solved the wrong problem. It eliminated operational complexity (multi-asset, risk frameworks, cloud infrastructure). It did not eliminate the requirement to hand-code every strategy. That bottleneck remained.

3

Gen 3.5 eliminates the bottleneck. When AI writes the code, the constraint shifts from engineering hours to the quality of your ideas. That is the inflection point.

Gen 4:Paradigm Shift

Ready to leave the code bottleneck behind?

Try StratCraft Free Read the Full Evolution Story