The biggest barrier to trading automation has always been code. To build a trading bot, you needed Python, APIs, server infrastructure, and weeks of development time. Most traders have great ideas but no way to implement them systematically.

Otomate's Strategy Builder changes this. You describe your strategy in plain English (or French), and the system parses it into structured trading rules that execute automatically. No code. No APIs. No servers. Just your idea, expressed in words, running 24/7 on Ink Chain.

Here is how to use it effectively.

How the Strategy Builder Works

The Pipeline

You describe your strategy in natural language
AI parses your description into structured conditions (using Claude via OpenRouter)
You review the parsed rules and adjust if needed
You backtest on historical data to validate the logic
You deploy with your chosen capital and leverage
A background worker evaluates your conditions every 60 seconds against live market data
When conditions are met, the system executes on your Nado subaccount via bot delegation

The entire process — from idea to live execution — takes about 10 minutes.

What the AI Understands

The parser handles a wide range of trading concepts:

Indicators: RSI, EMA (9, 21, 50, 200), MA (20, 50, 200), MACD (line, signal, histogram) Price conditions: Above/below specific prices, breakouts, percentage moves Position conditions: Position open/closed, current PnL, position size Time conditions: Specific hours, days of week Funding rates: Current rate thresholds Logic: AND (default) / OR combinations

Supported Actions

OPEN_LONG: Enter a long position
OPEN_SHORT: Enter a short position
CLOSE_POSITION: Close current position entirely
ADD_TO_POSITION: Increase current position
REDUCE_POSITION: Decrease current position

Building Your First Strategy: Step by Step

Step 1: Start Simple

The most common mistake is trying to encode a complex 10-condition strategy on your first attempt. Start with one entry condition and one exit condition.

Example input: "Go long BTC when RSI drops below 30. Close when RSI goes above 60 or when I'm down 3%."

What the system parses:

Rule 1: IF RSI(14) < 30 → OPEN_LONG
Rule 2: IF RSI(14) > 60 → CLOSE_POSITION
Rule 3: IF PnL < -3% → CLOSE_POSITION

This is a simple mean reversion strategy. It buys oversold conditions and exits when momentum returns to neutral or when the loss limit is hit.

Step 2: Review the Parsed Rules

After the AI parses your input, you see the structured rules displayed in a review interface. Check:

Are the indicator parameters correct? (RSI 14 vs RSI 7 — the parser defaults to 14 unless you specify)
Are the thresholds right? (Below 30, above 60)
Is the action correct? (OPEN_LONG, not OPEN_SHORT)
Is the logic AND or OR? (Default is AND — all conditions must be true)

If anything is wrong, edit the rules directly or rephrase your description and re-parse.

Step 3: Backtest

Before deploying real money, run a backtest. The Strategy Builder supports 7, 14, 30, and 90-day backtests using historical 1-hour candles.

What to look for:

Profit factor > 1.3: The strategy makes more than it loses
Win rate appropriate for the strategy type: 55%+ for mean reversion, 40%+ for trend following
Max drawdown < your tolerance: If the 30-day backtest shows 15% drawdown, expect 20-25% live
Enough trades: At least 10 trades in the backtest period for statistical relevance

If the backtest looks reasonable, proceed. If it shows a loss or extreme metrics (95% win rate usually means too few trades), refine your rules.

Step 4: Deploy

Configure:

Asset: BTC, ETH, or SOL
Capital: How much to allocate (minimum varies)
Leverage: 1x to 20x (start low — 2-3x recommended)
Delegation: Sign an EIP-712 delegation to authorize the bot to trade on your Nado subaccount

Once deployed, the strategy status changes to ACTIVE and the worker begins evaluating your conditions every 60 seconds.

Step 5: Monitor and Adjust

The strategy detail page shows:

Current status (ACTIVE, PAUSED, STOPPED)
Live indicator values (RSI, EMA, MACD for your asset)
Execution history (every trade the system made, with timestamps and PnL)
Overall PnL

If you need to adjust, pause the strategy first (cannot edit while ACTIVE), make your changes, then reactivate.

Strategy Templates: Proven Approaches

Here are battle-tested strategy descriptions you can use as starting points:

Trend Following

"Go long BTC when EMA 9 crosses above EMA 21 and price is above EMA 50. Close position when EMA 9 crosses below EMA 21. Stop loss at 5%."

Why it works: Captures medium-term trends by entering when short-term momentum aligns with the longer-term trend. The stop loss protects against whipsaws.

Expected profile: 40-50% win rate, 2:1+ average win/loss ratio, 5-10 trades per month.

Mean Reversion

"Go long ETH when RSI drops below 25 and MACD histogram is negative. Close when RSI reaches 55 or profit reaches 4% or loss reaches 2%."

Why it works: RSI below 25 is a genuine extreme. Combined with MACD confirmation (histogram negative = momentum is weak), it catches oversold bounces with defined exits.

Expected profile: 60-65% win rate, 1:1 average win/loss ratio, 3-6 trades per month.

Breakout

"Go long SOL when price rises above the 20-period high and RSI is between 50 and 70. Take profit at 8%. Stop loss at 3%."

Why it works: 20-period high breakouts capture the start of new impulse moves. The RSI filter avoids buying into already-extended moves.

Expected profile: 45-55% win rate, 2.5:1 average win/loss ratio, 2-4 trades per month.

Momentum Pullback

"Go long BTC when EMA 9 is above EMA 21 and EMA 21 is above EMA 50 and RSI drops below 40. Close when RSI goes above 70 or when loss exceeds 4%."

Why it works: The triple EMA alignment confirms a strong uptrend. RSI below 40 in an uptrend signals a pullback — a high-probability entry point. This is the institutional pullback buy.

Expected profile: 55-60% win rate, 1.5:1 average win/loss ratio, 2-5 trades per month.

Funding Rate Play

"Go long BTC when the funding rate drops below -0.03%. Close when funding rate goes above 0.01% or after 24 hours."

Why it works: Extremely negative funding means shorts are paying dearly. This creates buying pressure as shorts close. The 24-hour time limit prevents holding if the thesis does not play out.

Expected profile: 55-60% win rate, 1:1 ratio, depends on funding rate volatility.

Advanced Techniques

Multi-Condition Strategies

Combine multiple indicators for higher-conviction entries:

"Go long BTC when any of these are true: RSI drops below 20, or price drops more than 5% in one day. Close when RSI goes above 60."

The key phrase "any of these" tells the parser to use OR logic instead of the default AND. This creates a strategy that triggers on either condition — casting a wider net for oversold opportunities.

Cooldown Periods

Prevent the strategy from re-entering immediately after an exit:

"Go long ETH when EMA 9 crosses above EMA 21. Close when EMA 9 crosses below EMA 21 or loss reaches 3%. Wait at least 4 hours between trades."

The cooldown prevents whipsaw re-entries during choppy crossover periods. The system enforces this as a minimum time between executions of the same rule.

Global Stop Loss

Add an account-level safety net:

"Go long BTC when RSI drops below 30. Close at RSI 60 or loss 3%. If total account drawdown reaches 10%, stop the strategy completely."

The global stop loss is checked before every rule evaluation. If your subaccount equity drops below the threshold relative to your initial deposit, the strategy closes all positions and stops.

Best Practices

1. One Asset Per Strategy

Do not try to trade BTC and ETH in the same strategy. Create separate strategies for each asset. This keeps the rules clean and makes it easier to diagnose issues.

2. Always Include a Stop Loss

Every strategy should have a defined maximum loss per trade. Without a stop loss, a single trade in a strong adverse trend can consume your entire allocation.

3. Start with Low Leverage

2-3x leverage is sufficient for most strategies. Higher leverage amplifies both gains and losses — and more importantly, it reduces the distance to liquidation. A 5% adverse move at 10x leverage is a 50% loss.

4. Backtest Before Deploying

Always. Even a 7-day backtest can reveal obvious flaws (like a strategy that trades 200 times in a week, or one that never trades at all).

5. Monitor the First Week Actively

Even though the strategy runs automatically, check it daily for the first week. Verify that the live trades match what you expected based on the backtest. If something looks off, pause and investigate.

6. Do Not Over-Optimize

If your backtest win rate jumps from 55% to 80% by adding a fourth condition, be suspicious. You are likely overfitting. The simplest version that is profitable is usually the most robust.

Strategy Lifecycle

Strategies on Otomate follow a clear lifecycle:

DRAFT: Created and parsed, awaiting deployment. You can edit freely.
ACTIVE: Live, evaluating conditions every 60 seconds. Cannot edit (pause first).
PAUSED: Temporarily stopped. Can edit rules, leverage, amount. Can resume to ACTIVE.
STOPPED: Permanently stopped. Cannot reactivate. Create a new strategy instead.

Only one strategy can be ACTIVE per user at a time. This prevents conflicting signals from multiple strategies on the same subaccount.

The Automation Advantage

Manual traders make roughly 5-10 trading decisions per day before fatigue degrades their judgment. An automated strategy makes zero-fatigue decisions every 60 seconds, 24/7 — that is 1,440 evaluations per day, 10,080 per week.

More importantly, the strategy never:

Skips a signal because it is "not feeling confident"
Holds a loser because "it might come back"
Increases size after a loss to "make it back"
Misses a 3 AM setup because it was sleeping

The Strategy Builder gives you the discipline of an algorithm with the creativity of a human trader. You provide the insight. The system provides the consistency.

Define your edge in words. Let the automation do the rest.

Don't trade. Automate.