Embedding business logic into prompt templates

Embedding business logic into prompt templates involves structuring your prompts in a way that allows specific business rules or operations to be included dynamically. This allows for more tailored and context-sensitive responses when interacting with AI models, as well as ensuring that the responses are aligned with the goals and constraints of a business. Here’s how you can approach it:

1. Define the Business Logic Clearly

Before embedding business logic into the prompt template, it’s important to clearly define the business logic or rules that govern your operations. This might include:

• Calculations (e.g., price calculation based on certain discounts or tax rates)

• Business constraints (e.g., allowable working hours, regions served)

• Decision-making rules (e.g., if a customer selects a specific option, another option becomes available)

2. Designing the Template Structure

A good template has placeholders for dynamic inputs but also embeds the logic in such a way that the AI model can consider the business rules when generating responses.

Example: Pricing Calculation Template

Scenario: A business needs to calculate the price of a product after applying a discount and tax.

Template:

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"The base price of the product is {base_price}. 
Apply a discount of {discount_percentage}%. 
After the discount, the new price is {discounted_price}. 
Now, apply a tax rate of {tax_percentage}% to the discounted price. 
The final price after tax is {final_price}. 
Please ensure that the price never goes below {min_price}."

Logic Implementation:

• discounted_price = base_price * (1 - discount_percentage / 100)

• final_price = discounted_price * (1 + tax_percentage / 100)

• Ensure that final_price >= min_price

Here, the placeholders are filled dynamically with values based on business logic, such as calculating the discounted price and ensuring that the final price doesn’t fall below a certain threshold.

3. Embedding Business Rules into Prompt Logic

In some cases, it’s not just about inserting static values, but embedding conditions or rules that the AI can check or calculate as part of the prompt.

Example: Sales Region Eligibility Template

Scenario: A company sells products to specific regions, but some products may not be available in certain locations. This needs to be factored into the prompt template.

Template:

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"The customer is requesting a product in the {region}. The product is available in the following regions: {available_regions}. 
Please confirm whether this product can be shipped to the {region}."

Logic Implementation:

• if region in available_regions: return "The product can be shipped."

• else: return "The product is not available in the specified region."

Here, the AI needs to check if the customer’s region is part of the available regions list, ensuring that business logic (product availability) is adhered to.

4. Handling Complex Business Logic with Conditional Logic

In some scenarios, the business logic may require more complex operations, such as conditional logic, loops, or external data fetching. You can embed these conditional rules into your prompt template like so:

Example: Employee Eligibility for Bonus Template

Scenario: Employees are eligible for a bonus based on their performance score and the number of hours worked.

Template:

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"The employee has a performance score of {performance_score} and worked {hours_worked} hours. 
The threshold for bonus eligibility is a performance score of {bonus_threshold} and at least {min_hours} worked hours. 
Please confirm if the employee is eligible for a bonus."

Logic Implementation:

• if performance_score >= bonus_threshold and hours_worked >= min_hours: return "Employee is eligible for a bonus."

• else: return "Employee is not eligible for a bonus."

In this case, the AI can dynamically evaluate the conditions based on input values to determine whether the employee qualifies for a bonus, reflecting the embedded business logic.

5. Providing Specific Context in the Template

You can also provide business-specific context in the prompt to guide the AI’s responses. This ensures that the AI’s output is aligned with company norms, objectives, or preferences.

Example: Customer Support Template

Scenario: A company wants to maintain a tone of empathy and helpfulness in customer support communications.

Template:

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"Customer’s issue: {issue_description}.
The support team’s response should include:
1. Empathy: Acknowledge the customer's frustration or inconvenience.
2. Resolution: Provide a clear next step for resolving the issue.
3. Thankfulness: Thank the customer for their patience or for bringing up the issue.

Ensure that the response follows the company’s tone of being kind and professional."

Logic Implementation:

• Using the placeholders, the AI would craft a response that acknowledges the customer’s problem and uses the company’s tone and business approach in the response.

6. Iterative Refinement

Once you’ve embedded the business logic, you’ll likely need to refine the templates over time based on user feedback or evolving business processes. Continuous iteration and improvement are crucial to ensuring that the templates are fully aligned with the business goals.

By embedding business logic directly into your prompt templates, you ensure that your interactions with AI remain consistent with the goals and constraints of your business. This not only increases the efficiency of automation but also ensures that AI responses are more relevant, accurate, and aligned with your operations.