AI Content Series: Scope it

In this blog we explore scoping for our AI content series.

Published by Hamish Kerry

Would you believe we’re already on the fourth instalment of our AI content series? 

Me neither! Let’s get a quick reminder of what happened in the last instalment. 

Last time we used Chat GPT to define the business plan for Finesse, it definitely expedited the process, but was it as accurate as we’d hoped? Well, the verdict is in by way of review from the commercial team, and there are definitely a few shortcomings. 

Be it by fault of question asking, or limited capacity to reference accurate conditions for the articulation of it, financial elements of the business plan left something to be desired. Chat GPT simply wouldn’t put a cost on things that a potential investor would need to assess in order to make accurate judgement on the viability of the business. 

This was a common line of questioning in feedback on the business plan when put to the team. In reality I would have done research to provide answers, but with Chat GPT as my only option, I wasn’t able to disclose anything that represented accurate information on potential return on investment, or income generation from the app.

However, let’s put this shortfall behind us and press on, we’ve got an app to finish! 

On scopes

We talk a lot about the importance of planning with our clients both current and potential. It’s threaded through our processes right from the beginning, you can read more about it here, what we’ve never tested, however, is how an AI would handle the generation of an abridged scope of work. I say abridged here because the full document that would need to be produced as part of a project is something that requires a significant amount more nuance than that which has been proven attainable by  Chat GPT at present. 

Let's see how it handles basic jumping off point, MoSCoW - an important, if slightly binary way to sort the wheat from the chaff. 

Here’s where the advantage of doing all of this work in a single Chat GPT conversation comes in, we’re able to change the way we ask questions to be much more conversational. If you’ve been keeping up with this series so far, you’ll notice how it’s referencing pieces of information from quite far back in the chat history.

Prompt: Break out a featureset based on our conversation using the MoSCoW method

Response: Sure! The MoSCoW method categorises features based on their priority and importance. Here's the feature set for the Finesse app using the MoSCoW method:

MSCW Finesse

We’ve got some good logic here, lets take a look at how it handles the idea of phased development:

Write a scope of work based on a phase 1, phase 1.5 and phase 2 launches of the product Finesse

phase 1 scoping work

Phases of development finesse phase 2

In all fairness, these came out pretty good, there’s nothing to fault with its logic in this case. There’s an understanding of prioritising features based on the aforementioned business plan and MoSCoW exercise. One thing it needed to be prompted on was the inclusion of a monetizable feature in phase 1 to recoup some of those development costs. 

A quick request to rewrite the scope with this in mind gets it back on track though. Thus, we end up with… 

Phase 1 monetisation

The chosen features for the Finesse app are ideal because they create a collaborative and interactive learning environment. They offer early revenue generation and attract users, focusing on enhancing user experience, social networking, and personalised learning. The app's expansion plans include social media functionality, multiple monetization opportunities, a skill marketplace, and verification badges, ensuring a vibrant and successful platform for Millennials and Gen Z.

Couldn’t agree more… 

Up next week

Next time on our AI series, we’ll be deep in the world of midjourney, where we’ll be using it to develop our logo, brand strategy and some initial wireframes for the app! I can’t wait! 


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