In order to make any informed decision, you should have a clear understanding of the intended outcome.

Clarifying Intended Outcome through Differentiators

To identify differentiators, think not what you want to build, but what you want to solve. In developing new products or features to an existing product, focus should be put on how your product differentiates from existing providers (or lack there of). If existing providers exist, you should reevaluate whether the effort to build those features yourself is worth more than just buying it.

For example, in our bicycle rental application, how we accept payments in itself is not a key differentiator. All rental companies will need to take in payments. However a customer's payment experience and the processes that power that experience such as single sign on, integrated mobile pay, refund process, or scan a card could be differentiators.

To begin documenting, start with a brief description of the problem or challenge. Elaborate on pain points for users, a gap in the market, or an opportunity to improve an existing process. When thinking about these problems, think in terms in of qualitative or quantitative results. Ask yourself how do you measure whether or not your solution is solving the problem?

To expedite this process we have created a as a start to capture the key points about this. You can . Finding balance between execution and research is a fine line and something to be mindful of. It is easy to end up in an endless cycle of analysis This can result in waiting too long to enter the market or ultimately not spending the development time needed to deliver a project at all. On the other hand, jumping into a project too quickly without the right level of research ends can result in products that already exist or do not solve a problem that really exists, often at a financial or time cost to the creator.

Everyone can have an idea, what and how you execute is what drives a successful delivery. Be prepared that it is a process that you are not likely to be successful on your first attempt. Keep going knowing that the journey itself is valuable. Whenever I struggle with this process I remember a lyric from “Always Wear Sunscreen”: “Whatever you do, don't congratulate yourself too much, or berate yourself either. Your choices are half chance. So are everybody else's.”

Let’s go through some prompts on how we can use AI to help build our bicycle rental application:

• How many Americans own bikes?

• How often do American ride bikes?

• What are some problems with bike ownership?

• How many bike rental business are there?

Some key considerations in responses during ideation, is when the data was last up to date. Markets, customer demands, and technologies change daily and a downside to large language models is they are often created "at a time". Meaning their data has a fixed end date and it cannot provide realtime information. To identify when a large language model was last , you could ask it or look at it's configuration.

Once your problem statement is defined, the next step is to gather requirements for the application. This could involve finding the key features and functionality required, as well as any technical constraints or limitations.

Generative AI, like ChatGPT, can play a valuable role in defining requirements for user stories, which helps streamline project planning and development. User stories are high-level descriptions of the desired functionality of a product from the perspective of a user or a customer. They describe the intended outcome but do not delve into the specifics of how that outcome will be achieved. Requirements, on the other hand, are more detailed and specific, outlining the exact features, functionality, and constraints of the system to be developed.

In the context of software development, requirements are critical for both the development team and stakeholders, as they serve as the foundation for understanding and agreeing upon the project's scope and objectives. Generative AI can assist in refining and elaborating on these requirements by providing insights, suggestions, and alternative perspectives.

Here are some examples of prompts that can be used with ChatGPT to further define business requirements:

1. "Given the user story about a customer renting a bicycle, what are some additional functional requirements that should be considered?"

2. "What non-functional requirements should be taken into account for a real-time messaging application?"

3. "Considering the user story of a bank customer transferring money between accounts, what security requirements should be in place?"

When gathering requirements, it's crucial to consider the human aspects, as these can have significant implications on the project's success. These aspects include legal, compliance, financial, and emotional requirements, which are often interrelated.

Example: Requirement considerations

Legal requirements refer to the need for the project to adhere to applicable laws and regulations. For example, a financial application must comply with data privacy laws and financial regulations. ChatGPT could be used to generate prompts or questions that help identify relevant legal concerns, such as "What are the data privacy regulations that apply to our application?"

Compliance requirements involve ensuring that the project follows industry standards, best practices, and internal policies. Examples include accessibility standards, security certifications, or corporate guidelines. ChatGPT can assist in identifying these requirements by generating prompts such as "What industry standards should our project adhere to?"

Financial requirements pertain to the budgetary constraints and financial objectives of the project. ChatGPT can help to clarify financial aspects by generating questions like "What is the estimated total cost of ownership for this project?" or "How will this project generate revenue?"

Emotional requirements focus on the user experience and the emotional impact of the product on its users. These requirements may involve user satisfaction, ease of use, or the aesthetics of the interface. ChatGPT can be employed to explore these aspects, with prompts like "How can we design the user interface to evoke a sense of trust and reliability?"

In conclusion, generative AI, like ChatGPT, can be a powerful tool in defining requirements for user stories, taking into account various aspects such as legal, compliance, financial, and emotional factors. By providing targeted prompts and generating insightful responses, generative AI can help streamline the requirement gathering process, ensuring a more robust and well-rounded foundation for project development.

Once your problem statement and intended outcome is well defined. You'll want to create and prioritize the features that will be included in the bicycle rental application.

This involves breaking down the user stories into smaller tasks and estimating the time and effort required to complete each task. Features should be prioritized based on their importance to the customer and their impact on the overall project.

Test-driven feature development is one the best ways to write and identify features for an application.

Given-When-Then

Given-When-Then is a testing framework that helps to write and organize automated tests by breaking them down into three distinct parts:

The ideation template provides key areas to document in the largely human driven Ideation knowledge area.

Problem Statement

Now that we have features that describe the actions and interactions that users will have with the bicycle rental application, we will create user stories to develop from. User stories should be developed collaboratively with stakeholders and end-users, and should focus on delivering value to the customer.

User stories are defined work items that describe features and functionality that power an end user action.

User stories typically have the following characteristics :

• Have a description that summarizes the use case the user story is solving

With the problem statement clear, requirements defined, and user stories groomed, you will be in an informed state to appropriately use generative AI to generate new ideas and concepts for the software application or requirements that should be met to ensure project success. This could involve providing LLM with a brief description of the software application and asking it to generate potential features, user stories, or use cases.

Example: Generating features for a bicycle rental application

The below sections cover a broad scope of ideation and refinement approaches with references to concepts often discussed in product management, project management, and agile frameworks for developing an application. If you have leveraged these frameworks before, then some of content may be redundant, but the intent is to create new perspectives in how generative AI can be used to accelerate or improve the quality of these activities.

In relation to generative AI, you can use prompts to help identify problems, create new ideas to solve those problems, elaborate on existing solutions, or challenge your own thoughts through other suggestions.