Risk of AI Sameness

Everyone is racing to adopt AI tools.  Most people are using AI to create “speed”.  Faster emails. Faster proposals. Faster code. Faster content. And yes, faster is good.  But here’s the quiet risk no one is talking about: if everyone in your company uses the same AI the same way, you may slowly start sounding exactly alike.

Are you ignoring “AI sameness” risk? Without intention, standard AI tools can homogenize your messaging, flattening distinct perspectives into one generic voice. The danger isn’t bad output. It’s average output at scale. AI isn’t going to replace your team. It’s going to standardize them, but not in a good way.

When everyone uses the same tools, trained on the same data, prompted in the same way, you don’t get divergence, you get convergence. Everyone will sound the same, with the same sentence structure and tone, and with the same “polished but generic” voice. Then there is the further danger that over time, unique thinking gets flattened into safe, average, AI-shaped output. Not because your people aren’t smart, but because the tool defaults to the statistical middle.

AI should amplify your edge, not sand it down. AI should sharpen your thinking, make it more opinionated, and more differentiated. If you’re not intentional about how your teams use it, it can lead to this sameness.  What can you do to avoid this sameness?

• Craft your own perspective before prompting AI.  As it relates to the topic, what do you actually believe? What do most people get wrong about this? What would you argue in a debate?
• Use AI to provide you with a draft, not the deliverable. Within that context, establish one strong opinion. Provide one specific example from your world. Craft your own voice so that sentences sound unmistakably like you.
• Add Friction to the output. AI will often be a people pleaser, so challenge your output. Ask what’s missing. Determine if it feels too safe. Consider if it sounds too predictable? If it reads smoothly but doesn’t make you think, that’s a warning sign.

AI naturally drifts toward the statistical middle. Avoiding sameness requires intentionally looking for differences. It must include injecting strong beliefs, specific context, and human judgment layered on top.  And honestly? The companies that figure this out won’t just use AI faster. They’ll use it to amplify their uniqueness.

How to Experiment with ChatGPT

As ChatGPT continues to make waves, is it time to learn more about it? One way to approach this is begin experimenting with ChatGPT within your context.  Learn where ChatGPT can help and where it can benefit you. In other words, what do you want to get out of ChatGPT? This allows you to test your hypothesis and the surrounding assumptions to provide knowledge and insight into whether (in this case) ChatGPT can help you or not. Here is an example.

Start with the question: Can ChatGPT help my team improve? Validate this question. Conduct preliminary research to gauge if this is relevant for your team. Start by finding out if team members are interested in using ChatGPT. This can also help you identify assumptions and if there are any other variables in play that can impact the direction of the experiment. It can also help you narrow down an area that you think ChatGPT can help.  After discussion with the team, team members believe that ChatGPT can help in retrospectives

Craft a hypothesis in a clear sentence on what you expect to find: Include ChatGPT in the retrospective can lead to better root cause analysis.  Some team members had an assumption that ChatGPT could provide root cause analysis capabilities. A hypothesis can help you validate whether ChatGPT can provide better root cause information. You can also use the “if… then” form: if we use ChatGPT during our retrospective, it will provide better root-cause analysis results, leading to more effective actions for improvement.    

Craft the experiment. Now that you have a sturdy hypothesis, it is time to craft your experiment. Describe the steps through your experiment. To do this, consider how long the experiment will run and who will be involved.  In this case, you decide to include ChatGPT in the next three retrospectives in order to get a more meaningful set of results and to have time to determine if the actions are leading to more effective results. Determine who will use ChatGPT during the retrospective and how the questions and statements will be written. Also consider the metric you will use to validate your result and what success criteria you will use to determine if the hypothesis was true (or not).  At this point, it is time to run the experiment. 

Run the experiment. An experiment should be considered as recognized effort and categorized as real work to track in your backlog.  Enact the steps listed in your experiment. Capture observations along the way and results upon the conclusion of the experiment. Get together with those who are involved in the experiment and determine what you’ve learned. Ask the question, did what we learn validate the hypothesis (or not)?  Then determine what decisions you will make as a result of this experiment. In this case, should you to continue using ChatGPT for retrospectives (or not)? Determine if there are any next steps. 

In conclusion, if you are thinking about ChatGPT, the key is to experiment. ChatGPT is a tool like other tools that may benefit you. Brainstorm where ChatGPT can help you in your context. Use the experiment to see if it does. Consider multiple experiments so that you build working knowledge of ChatGPT in your environment and working context.

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If you are interested in learning more about ChatGPT in relation Agile, Teamwork, or experimentation, consider reading the following articles:

• A Discussion with ChatGPT about Agile 
• Are there Dangers with ChatGPT for Agile? 
• Are there Benefits for adding ChatGPT as a team member? 

A Discussion with ChatGPT about Agile

I had a good discussion with ChatGPT about two weeks ago. I started by asking “What is Agile?” The response was that “Agile is a methodology” with a bit more details. While technically incorrect, given the amount of information and vectors it pulled from, it wasn't completely wrong. What I mean by this is that many people, including some “Agile experts”, refer to Agile as a methodology which is incorrect. Depending on where ChatGPT is pulling this information from, this isn’t a surprise.   

• My response: “Agile is a set of values and principles. Some Agile information is not aligned with Agile values and principles and instead rely heavily on Agile processes and methodologies or people's misinterpretation on what is agile”.  
• ChaptGPT's response: You are correct. Agile is indeed a set of values and principles outlined in the Agile Manifesto, and it emphasizes flexibility, collaboration, iterative development, and customer satisfaction. However, misinterpretation or a focus solely on Agile processes and methodologies can lead to a deviation from these values and principles.

I was happy to see that it was aware of the Agile Values and Principles as this is how Agile is defined by the Agile Manifesto which is the seminal information defining Agile. And as I mentioned in my previous article, The Dangers of ChatGPT to Agile, there is a lack of quality evaluators on the numerous Agile articles and presentations in cyberspace that indicate if the information provided is right or wrong, good or bad.

Two weeks later (today), I asked ChatGPT the same question, “What is Agile.” This time it included the Agile Values and Principles as part of its long-winded response that included:

"Agile is an iterative and incremental approach to project management and product development that emphasizes flexibility, collaboration, and continuous improvement. It was created as a response to traditional, plan-driven project management methodologies that often struggled to adapt to changing requirements and deliver value in a timely manner.

Here are some key aspects of Agile:

1. Values and Principles: Agile is guided by the Agile Manifesto, which outlines four core values: individuals and interactions over processes and tools, working software over comprehensive documentation, customer collaboration over contract negotiation, and responding to change over following a plan. These values prioritize human-centric approaches and adaptability.
2. Iterative Development, 3. Cross-functional Teams, 4. Continuous Improvement, 5. Customer Collaboration, 6. Flexibility and Adaptability" (Note: I removed the details of 2 thru 6 from ChatGPT as this wasn’t relevant to this article).  

While ChatGPT will continue to develop and response to my queries, I am happy to see that it is using my (and others’) input to fine-tune its language model and improve its responses.

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If you are interested in learning more about ChatGPT in relation Agile, Teamwork, or experimentation, consider reading these additional articles:

• Are there Dangers with ChatGPT for Agile? 
• How to Experiment with ChatGPT 
• Are there Benefits for adding ChatGPT as a Team Member?

Startupbucks (aka Starbucks) the OaaS Innovation Incubator

As I was momentarily pausing from working on a presentation, I leaned back and noticed that there was quite a bit of “business” occurring in my local Starbucks.  There were a lot of enthusiastic conversations with a collection of open laptops, notebooks, tablets, and more being used to share, illustrate, and note ideas.  This wasn't the first time I’d seen this same level of engagement in a Starbucks. 

Then something occurred to me.  I was witnessing an incubator of business, non-profit, and personal ideas being generated and matured.  Of course some people are there for just a coffee and a chair to relax.  Others are there for a quick pick-me-up for the day or remainder of the day.  Alternatively, it was clear that Starbucks was this place where business was happening, where new ideas were being generated, where collaboration was happening, and where progress was being made.  It was an incubator of innovation! 

That’s where it occurred to me, Starbucks was part coffee shop and part office-as-a-service (OaaS) incubator.  I therefore have redubbed Starbucks to Startupbucks!  The first part of the name (Startup) is a place where new ideas come to life and blossom surrounded by the aroma of coffee beans.  The second part of the name (bucks) is coincidentally where hopes for financial reward is part of the innovation dream.   I wonder how much business has been conducted in Startupbucks and much money this translates into?   Next time you are in Starbucks, take a look around.  Are you seeing the same thing that I am?  Finally, thank you Starbucks and the many coffee shops like you for providing us this OaaS that makes a great incubator of ideas and haven for progress!    

Divergent Thinking is Great for Innovation and Agile

Divergence is a concept that implies that something is different or develops in a different direction.  Divergent thinking takes this concept and applies it to help you gain new insights and solutions.  This concept can be extremely important in achieving an innovation mindset.  This can benefit your focus on innovation and agility leading to better business results.  

For a company, divergent thinking can be used as a technique that provides an opportunity to create an internal market place of ideas.  These ideas can then be discussed, refined, and evolved into multiple solution options. 

Divergent thinking provides individuals, teams, and companies with the ability to consider lots of possible ways to satisfy a business need. Once divergent thinking occurs, there is a need to pair this with convergent thinking so that one solution is decided upon and experimented with. 

Unfortunately Divergent thinking isn’t encouraged in many of work cultures.  While most companies will say they want new and innovative ideas, there is an angst to move quickly to an answer which typically negates the possibility of sufficient divergent thinking.  Converging too soon reduces options and opportunity. 

If you are looking to infuse a mindset where innovation can thrive, then explicitly introduce divergent thinking into your organization.  Innovation is often introduced in the form of hack days.  This is periodic and event driven.  A more effective approach may be to apply continuous divergent thinking throughout many of the steps of your idea to delivery (aka, end-to-end) process. 

Some may ask, “What is to keep divergent thinking from distracting or slowing down our work?”  The simple answer is to apply a time-box technique for divergent thinking.  A brief example is if you have a business opportunity (aka, idea), allow for a period of time to silently identify all possible solutions.  Place the ideas onto large post-ids and post them up.   

The key is to conduct the divergent thinking silently since this ensures no negative or anchored prejudice interferes.  Divergent thinking works best when ideas can flow freely without opposing opinions.  Once the time-boxed divergent period is concluded and all of the ideas are collected, then convergence may commence.

Divergent thinking is a great way to gain new insights and ideas for solutions to business problems and products.  If you are looking for ways to infuse innovative thinking into your organization, consider applying divergent thinking.  Divergent thinking may allow you to come up with the next generation idea or the 10x gain which can lead to better business results.