Runbot unveils the AI Agent Optimiser: Conversational AI that’s transforming bot creation

Creating an efficient trading bot has long been a challenging journey. It required combining technical expertise, patience, and dozens of manual trials. Beginners quickly gave up. Even advanced users wasted precious time. With the launch of its AI Agent Optimiser, Runbot changes the rules. This new conversational assistant turns strategy optimization into a simple exchange with an artificial intelligence. No code. No technical lines. Just a clear discussion that leads to more effective strategies.

Artificial Intelligence Serving Real Obstacles

Building a bot is one thing. Optimizing it is another. In traditional no-code tools, designing a basic strategy remains accessible. But improving it, increasing its yield, reducing drawdown, or adapting it to the market requires time, trials, and a lot of intuition. Three obstacles hinder the majority of users:

• Lack of time: manually adjusting each parameter takes hours;
• Lack of expertise: it is difficult to know what truly matters;
• Human biases: decisions often rely more on instinct than on data.

The AI Agent Optimiser provides a clear solution: a smart co-pilot that reads your strategy, understands your goals, and offers targeted improvements in natural language.

Introduction to Runbot: A Complete No-Code Platform

Before diving into the details of the AI Agent, let’s recall what Runbot is. It is a no-code platform dedicated to the creation, testing, and monetization of crypto trading bots. Each strategy becomes an NFT that can be rented or sold on the integrated marketplace.

Runbot offers powerful and intuitive tools:

• Composer: build your bot with sliders and simple rules;
• Optimizer: manually adjust its settings;
• AI Agent: automatically optimize strategies via a conversation;
• Execution via webhooks: secure and non-custodial;
• Marketplace: generate passive income by monetizing your bots.

Its goal is to democratize algorithmic trading by combining AI, blockchain, and an intuitive interface.

How Does the AI Agent Optimiser Work?

Once the strategy is created and backtested, the user can activate the AI Agent from the editor. A chat window opens. From there, the exchange begins.

1. The user explains their objective

Example: “I want to reduce drawdown” or “Improve profitability“.

1. The AI analyzes the strategy

It reviews indicators, triggers, timeframes, leverage levels…

1. Suggestions appear

The AI proposes precise modifications: EMA period, adding an RSI, adjusting stop loss, etc.

1. The user validates

The user chooses the optimization that best matches their goals (higher APR, fewer risks, more trades, etc.)

1. A new backtest is launched

The optimized strategy is tested automatically, and the results are displayed.

This interaction only takes a few minutes, with no technical knowledge needed.

📘 See the complete guide here: AI Agent Optimiser

🎥 Watch the video tutorial here: AI Agent Optimiser Video

Detailed Example: Creating and Improving a Bot with the AI Agent

To fully understand the usefulness of the AI Agent Optimizer, let’s take a concrete case. The idea is to start with a simple strategy, then improve it using the artificial intelligence integrated into the Runbot platform.

Step 1: Configuration

The user opens the Runbot strategy editor and sets up a trading bot using the no-code interface.

They choose a basic indicator to build their strategy:

• Indicator: EMA (Exponential Moving Average)
• Period: 100
• Timeframe: 4 hours

This setup serves as a simple starting point, often used to follow a medium-term trend.

Step 2: Adding the EMA Indicator

The user defines entry and exit rules based on EMA crossovers. They also choose position parameters:

• Entry: the bot opens a long position when the price crosses the EMA upward
• Exit: the position is closed when the price goes back below the EMA
• Leverage: ×3
• Position Type: long only

At this stage, the strategy is ready to be tested.

Step 3: Defining the Leverage

The user chooses a moderate leverage, here x3, suitable for intermediate profiles. 

This leverage increases exposure without overly increasing the initial risk.

Step 4: Entry Trigger

The entry trigger is based on a simple logic: follow the upward trend.

If the price touches the EMA from above (touch down) then the bot opens a buy position (long).

Step 5: Exit Rules

To exit a position, the user chooses clear and symmetrical rules: first, if the asset price falls 5% below the entry price, the trade is closed. Second, as soon as the price touches the EMA from below (touch up), if a long is ongoing, it is closed; otherwise, a short is opened. The other take profit rule is the TP ATR .

Step 6: Free Backtest + Stats Reading

The user runs a free backtest directly in the Runbot interface.
The results appear immediately:

• The strategy works, but the drawdown is high
• The success rate remains low
• Gains are irregular, with phases of underperformance

This is where optimization becomes necessary.

Step 7: Discussion with AI to Optimize the Strategy

The user activates the AI Agent Optimizer integrated into the platform. A chat window opens. They state their objectives:

• “Reduce the drawdown”
• “Improve the success rate”

The AI analyzes the existing strategy and suggests modifications:

• Reduce the EMA period (for example from 100 to 50) for more reactive signals
• Add a second indicator such as RSI or Bollinger Bands to filter out false signals
• Implement a stop loss and a take profit, adapted to the observed volatility level

The user validates the suggestions and runs a new test.

Step 8: Results, Comparison: Strategy Improved After Optimization

The second backtest confirms the strategy improvement:

• Drawdown significantly reduced
• Improved gain/loss ratio, with more consistent performance
• More stable equity curve, which strengthens the bot’s reliability over time

In a few minutes and without technical expertise, the user transforms a basic strategy into a high-performing bot, ready to be deployed… or monetized.

Why is it a True Game Changer?

The AI Agent Optimizer does not just assist the user; it profoundly transforms how they create and optimize their bots. Where manual strategy adjustment took hours, a few minutes are now enough to obtain a concrete and relevant result. This time saving redefines the efficiency of the creation process.

Accessibility is another fundamental change. No more programming skills required nor deep reading of technical indicators. Artificial intelligence interprets objectives expressed in natural language and proposes suitable settings, thereby eliminating technical complexity.

In terms of performance, AI relies on historical data analysis to identify the most effective combinations. It rigorously adjusts parameters, improving results while limiting risks. 

This new tool allows for greater scalability: by facilitating the creation of robust strategies, it opens the way to producing several quality bots, usable on the marketplace. Each user can now develop their portfolio of strategies without prior expertise and access new sources of income.

Monetization & Marketplace: Benefits for Creators

Every strategy created on Runbot is automatically turned into an NFT. This means it can be sold or offered for rent on the integrated marketplace. The more performant and well-optimized the strategy is, the more it attracts users seeking ready-to-use solutions.

The AI Agent plays a key role here: it helps creators reach a quality level faster that makes their bots competitive and attractive. Thanks to this intelligent support, users can consider a real business around strategy design, with potential regular income. This mechanism transforms bot creation into a full-fledged economic model, accessible to the widest audience.

Best Practices and Important Reminders

Even with such a powerful assistant as the AI Agent, some fundamental rules of algorithmic trading must remain at the heart of the approach. A backtest, no matter how successful, never guarantees future performance. Market conditions evolve, and a strategy that was effective yesterday can become obsolete tomorrow.

It is also important to avoid over-optimization. By adjusting parameters too finely, one risks producing a fragile strategy, too dependent on the past and poorly adapted to real market fluctuations. To limit this risk, it is recommended to diversify bots. By spreading exposure across multiple strategies, the resilience of the entire portfolio is strengthened.

Finally, applying strict rules in money management remains essential. Defining appropriate position sizes, limiting potential losses, and securing gains should be an integral part of every strategy. Artificial intelligence assists, but it is always the trader who retains control over their decisions.

With the AI Agent Optimiser, Runbot takes a new step in democratizing algorithmic trading. Creating, testing, and improving bots becomes simple, fast, and accessible to everyone.

👉 Start your first test on Runbot.io
📘 Access the full guide: AI Agent Optimiser

$400 worth of $RBOT tokens will be won (10 winners, $40 each) tomorrow, Friday, June 27, via a major contest taking place on the Read 2 Earn platform. 100 credits will also be offered to each participant. Register for Read 2 Earn now by clicking the button below!