How I save an hour a day using Generative AI

2023 is the year of generative AI with ChatGPT, Bing AI chat, Google Bard, and AI image generation creating a lot of hype, as well as legitimate concerns over the potential misuse of the technology and if the technology is going to take our jobs. Technology seems to be moving so fast that what is written about it today is outdated tomorrow. And the same prompt will get a different answer the next time it is asked. From the Wired Magazine review: ” Imagine trying to review a machine that, every time you pressed a button or key or tapped its screen or tried to snap a photo with it, responded in a unique way—both predictive and unpredictable, influenced by the output of every other technological device that exists in the world. The product’s innards are partly secret. The manufacturer tells you it’s still an experiment, a work in progress; but you should use it anyway, and send in feedback. Maybe even pay to use it. Because, despite its general unreadiness, this thing is going to change the world, they say. “

Some of the valid concerns about this technology:

  • Privacy concerns and data misuse
  • Deepfakes and misinformation
  • Bias and discrimination in AI-generated content
  • Unemployment due to automation

Despite the hype and the concerns, I have found some real-world applications of this technology that have made it part of my daily workflow and have saved me, on average, one hour of work time per day. In this post I will cover some of the ways I use generative AI like ChatGPT on a daily basis:

Meeting research

In my role as a Senior Director of Power Platform at Hitachi Solutions, I have many meetings. Before the meeting, I want to be prepared, including knowing about the company with which I am meeting, if there has been any big news about them recently, and the people with which I am meeting. This was all possible pre-generative AI, but this makes it much easier and less time-consuming.

The tool: Bing AI chat, because it combines generative AI with web search, so it returns recent information from LinkedIn and other sources.

The prompt: give me recent news for [company name] and the background of the following people who work for the company: [name], [name], [name], [name]

The result is a concise summary of recent news about the company and bio of the key meeting attendees.

Time saved: 30 minutes per meeting

Meeting preparation

I am also the president of the HOA in my small neighborhood. This week was our annual community meeting, and as the meeting chairperson, I wanted to make sure that I was following the correct parliamentary procedure for this type of meeting. I actually took a class on parliamentary procedure once, but that was 30 years ago, so I’m a little bit rusty. I couldn’t remember what the procedure was for amending a motion.

The tool: ChatGPT 4.0 model

The prompt: give me the parliamentary procedure and order of operations for a neighborhood meeting in which officers will be elected and please also provide the parliamentary procedure for amending a motion, and does it happen after the main motion has been seconded?

Time saved: 1.5 hours

Meeting minute creation

After an important meeting, such as the HOA meeting or many work-related meetings, I want to capture meeting minutes reflecting who was there, when it was, and what was discussed or decided.

The tool: ChatGPT

The prompt: Create meeting minutes for the meeting on [date] with attendees [list of attendees] topics discussed [list of topics] next steps/action items [list of action items]

If it is a specific type of meeting, such as the HOA meeting, ChatGPT will give you the standard meeting format/section such as existing business, new business, or general discussion, and you can in subsequent prompts refine it.

Time saved: 30 minutes

Agenda creation

In my line of work, we do many workshops, which are sets of meetings such as an agile business discovery. Creation of the agenda for these workshops can be time-consuming, such as getting the list of meetings formatted in an attractive manner with times for each session, then making changes to it, such as adding in breaks can be very tedious. Say you need to move one meeting because of some stakeholder’s availability, it can lead to great frustration in having to reformat the agenda.

The tool: Chat GPT

The prompt: Generate an agenda for an agile discovery workshop that begins at 9:00 am with each session running for 60 minutes with a break around noon for lunch. include the following sessions: Persona definition, current process review, to-be process definition, story mapping, and prioritization. include the start and end times for each session.

The result is a table with each session, the start and end time for each session, and the lunch break.

Say you then want to refine it by moving a session, adding a session, changing the times, etc, you can do so in subsequent prompts.

Time saved: 1.5-2 hours per workshop.

Table creation

In my role, I also frequently estimate projects for low-code app development and automation. This often includes modeling resource mixes in a resource plan. I use multiple tools, including Excel to do this, but making changes, especially for quick modeling purposes can be tedious.

Generative AI makes tables.

The tool: ChatGPT 3.5 model

The prompt: generate a table with the following columns: Resource, a column for weeks 1-25 and a total column. Add the following resources: Solution Architect, Technical Architect, Developer, Data Scientist for 40 hours per week and project manager for 20 hours per week

The result is a markdown for table definition, copy to Dillinger, Typora, Visual Studio Code, etc and you have your table. ChatGPT automatically knows that the total column should total the week columns.

Then if you want to change it so the data scientist doesn’t start until week 3, just say “move the data scientist to week 3.”

Time saved: 30 minutes or more, depending on the changes you want to model

Answering questions

Much of my day is spent answering questions from colleagues and customers. Some of those questions require a technical or detailed answer requiring web research, such as a RFP response with questions about specific products. Example: Can you explain the licensing for Microsoft Power Apps.

The tool: Bing AI chat, because I can point it to a specific website

The prompt: Please summarize the pricing options for Microsoft Power Apps from

The result is a concise summary with the answer to the question that I can include in my email or response (after wordsmithing).

Time saved: 5-10 minutes per question


In my current role, I don’t get to develop as much as I used to, but I get to work with many smart developers. But on Saturday I wanted to organize my vinyl LP collection by building Power Automate flow to help me get album information and update my collection on

The tool: ChatGPT

The prompt: please give me instructions to build a custom connector for Power Automate to

The resulting answer gave me step-by-step instructions, including where to go on the discogs website, what URL’s to use, and how to populate them into the Power Automate connector reference. And the connector created worked to retrieve album information.

This is a very eye-opening experience and shows how much more powerful this is compared to regular web search–it is combining two separate things (creating a custom connector in Power Automate and the API reference on the discogs website) to give a working answer.

Time saved: 3 hours


I’m the weekend cook in my family, and ChatGPT is now my cookbook. I have made over twenty meals using ChatGPT, and nothing recommended has been bad or disappointing yet. What I love about it is that, unlike most cooking blogs, it doesn’t make you read the author’s life story or how much their kids like it, it just gives the recipe. And it is fantastic for suggesting things when you give it a list of ingredients that you have on hand. Then if the resulting recipe needs to be resized to make more or less food, or if you don’t have one of the ingredients and need to make a substitution, you can easily refine the recipe in subsequent prompts.

The prompt: I have [list ingredients] what can I make?

other prompts: give me a recipe for chicken enchiladas

Time saved: 20-40 minutes of searching for recipes


Generative AI with ChatGPT and Bing have replaced numerous other apps in my daily workflow and have saved me significant time from normal tedious tasks. I think this illustrates how this technology will continue to change how we work in the future. Just to note, I’m careful to not include sensitive, private, or customer-specific details in my prompts, but by using tools like ChatGPT to create the wireframes of things like answers to general questions or standard agile workshop agendas, I can then take the content generated and edit and enhance, while saving significant time in the process.

One thought on “How I save an hour a day using Generative AI

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s