Functional Level

Overview

At the functional level of our GenAi content, we approach the ability to generate prompts that will create responses that can provide low-level step-by-step instructions on common functions for a specific feature. For example, a functional prompt might ask for instructions on how to create an Actionable Insights Watcher for an expressed purpose.

Impact on GenAI

The impact of software product functional categories on GenAI can be inferred that these categories play a crucial role in shaping the capabilities and contextual understanding of generative AI systems.

While the direct impact may not be explicitly known, it is reasonable to infer that these functional categories contribute to shaping the context and depth of knowledge within GenAI, ultimately influencing its ability to generate relevant and valuable responses in the domain of software product functionalities.

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At this level, we are focusing on the core features for a specific capability within the Pricefx solution:

  • Tasks, specific activities, processes, or operations that a feature is designed to perform. These can include data processing, user interactions, automated functions, and other designated activities aimed at achieving specific objectives.

  • Extension, ability to extend or customize a feature’s abilities through customer add-ons, plugins, or modular Groovy components. These extensions allow users to enhance the functionality of the core software.

  • Best Practices, encompass established guidelines, methodologies, and approaches that are considered optimal for achieving efficient, reliable, and high-quality development, deployment, and usage.

  • Integration, ability of a feature to connect and interact with other Pricefx capabilities, other external systems, applications, or data sources. This includes seamless data exchange and overall interoperability.

  • Configuration, involves the settings, parameters, and customization options that allow users to tailor the software to their specific needs and preferences.

  • Security, encompasses the features and measures implemented to protect the software, its data, and its users from unauthorized access, data breaches, cyber threats, and vulnerabilities.

GenAI Prompt Examples

Below are some examples of GenAI prompts that are operating at this level of contextual understanding:

Functional Prompt: "Provide step by step instructions for creating a price list"

This functional prompt asks the GenAI chatbot to provide detailed step-by-step instructions (function) on how to create a price list (feature) within Price Setting capability. The response might look like this:

Here are the step-by-step instructions for creating a price list in Pricefx:

Step 1: Determine the Prerequisites

  • Make sure you have the necessary components ready, such as products, company parameters, and product extensions.

  • Ensure that you have set up any required calculation logics and workflow logics.

Step 2: Create a Calculation Logic

  • Define the calculation logic that will determine the prices for the products in your price list.

  • You can choose from various pre-built logics or create a custom logic.

Step 3: Select the Products

  • Select the products you want to include in your price list.

  • You can use simple or advanced filters to narrow down your selection.

Step 4: Define the Price List

  • Go to the "Price Setting" module and click "New Price List."

  • Select the appropriate price list type and provide a name for your price list.

  • Define the price list currency and any other relevant settings.

Step 5: Set Up Output Elements

  • Define the output elements for your price list, including the visibility of each element and the logic result field.

  • You can choose from various pre-built output elements or create custom elements.

Step 6: Review and Confirm

  • Review your price list settings and confirm the creation of the price list.

  • Make sure all the information is correct and complete before proceeding.

Functional Prompt: "When is an approval workflow logic called during quote execution"