Tactically, OpenAI is in a strong position; it doesn’t need to make its existing products relevant. Canvas isn’t a direct replacement for Word or Excel, but it doesn't have to be, because the key is that AI will perform tasks for you. So, why clutter the user interface with a ribbon bar full of features? With OpenAI, much of the work is delegated to the AI. In contrast, M365 CoPilot feels more like an add-on-something you can use if you choose to. But the really clever innovation is Project, every canvas and file in a project the AI can see, call on or modify. With M365/Sharepoint the Excel spreadsheet doesn't know anything about the other documents next to it. Now with a really clever decision-making engine in the form of O1 and soon O2 there is no reason why you cannot just give the AI a hard problem to solve and let it get on with it. We are moving into some interesting times .... but have I stopped my CoPilot subjection? Absolutely!
I think the key point is that most business problems aren’t “hard problems” in the sense that o1 or o3 should be pointed at. They are fairly easy problems with very specific context requirements. The addition of some of these new features make getting this contextual information easier.
@@brightideasagency I believe the answer is that it depends. Most businesses have straightforward processes but often lack understanding of how they can impact one another. Why are some people always busy while others are not? As businesses grow, they often become more inefficient. This is because the inefficiencies also increase in size and impact, eventually slowing the flow of finances and halting an organisation. Leadership in these scenarios consider using AI to help 'fix' these issues by taking the existing process and 'speeding it up', but this is often not the approach that yields the best results. So what is the answer? Donella Meadows authored a book titled *Thinking in Systems*, which explores the cause-and-effect relationships within interconnected processes. It emphasizes concepts such as the use of pull-based systems instead of push-based ones, along with other strategies that encourage processes to be more mindful of their surrounding contexts.
@@DavidROliver this is probably true. However, the issue still comes back to context in my opinion. The reason a lot of change fails is through not correctly understanding the context of the problem - consultants chase down what managers think is wrong rather than underlying problems. This same limitation exists with AI. You could give o1 a wonderfully thorough run down of your business' inefficiencies and ask it to design better processes, but if the foundational understanding driving that dialog is wrong, the AI's ability to solve problems - whether hard or easy - is irrelevant. My greatest focus for business AI is where are the opportunities to give it more context? IMO a business version of Microsoft's Recall would be one such opportunity. AI that can watch you work coupled with a massive context window is potentially a lot more powerful than a frontier model supplied with questionable context.
@@brightideasagency agreed ... I wrote this on another post elsewhere. "Start small by implementing a few basic processes and features. It may be a new team, so it will take a few cycles to bed in. Gather your requirements carefully, paying close attention to safety, security, and regulations. It's also essential to consider your budget, time, and resources. The budget consists of two components: the capital required for development and the operational costs needed for maintenance and optimization moving forward. A crucial part of gathering these requirements is defining what success looks like. Next, think about how your new processes integrate into the broader ecosystem of your business or your customer's business. Understand the context, identify dependencies, and clarify the expected outcomes. Clearly outline what actions individuals will take at each stage; a sequence diagram can be helpful for this. Test what you have created, and start by automating these tests to ensure thoroughness. Your measure during testing is whether it meets the success criteria gathered with the requirements. Iterate! Work on the next version without cramming everything into the first release. You want to minimize the time between customer feedback and delivery. Conduct your development in continuous cycles, showcasing new features and improvements each time, paying close attention on how they must work together. Always ensure that your solution is functional and deployed before focusing on optimization. Where improvements or automation are needed is not always obvious, but your customers will provide valuable insights that should inform your improvement roadmap." I'm not really much of a consultant, I still prefer to build things!
Tactically, OpenAI is in a strong position; it doesn’t need to make its existing products relevant. Canvas isn’t a direct replacement for Word or Excel, but it doesn't have to be, because the key is that AI will perform tasks for you. So, why clutter the user interface with a ribbon bar full of features? With OpenAI, much of the work is delegated to the AI. In contrast, M365 CoPilot feels more like an add-on-something you can use if you choose to.
But the really clever innovation is Project, every canvas and file in a project the AI can see, call on or modify. With M365/Sharepoint the Excel spreadsheet doesn't know anything about the other documents next to it. Now with a really clever decision-making engine in the form of O1 and soon O2 there is no reason why you cannot just give the AI a hard problem to solve and let it get on with it.
We are moving into some interesting times .... but have I stopped my CoPilot subjection? Absolutely!
I think the key point is that most business problems aren’t “hard problems” in the sense that o1 or o3 should be pointed at. They are fairly easy problems with very specific context requirements. The addition of some of these new features make getting this contextual information easier.
@@brightideasagency I believe the answer is that it depends. Most businesses have straightforward processes but often lack understanding of how they can impact one another. Why are some people always busy while others are not?
As businesses grow, they often become more inefficient. This is because the inefficiencies also increase in size and impact, eventually slowing the flow of finances and halting an organisation.
Leadership in these scenarios consider using AI to help 'fix' these issues by taking the existing process and 'speeding it up', but this is often not the approach that yields the best results. So what is the answer?
Donella Meadows authored a book titled *Thinking in Systems*, which explores the cause-and-effect relationships within interconnected processes. It emphasizes concepts such as the use of pull-based systems instead of push-based ones, along with other strategies that encourage processes to be more mindful of their surrounding contexts.
@@DavidROliver this is probably true. However, the issue still comes back to context in my opinion. The reason a lot of change fails is through not correctly understanding the context of the problem - consultants chase down what managers think is wrong rather than underlying problems.
This same limitation exists with AI. You could give o1 a wonderfully thorough run down of your business' inefficiencies and ask it to design better processes, but if the foundational understanding driving that dialog is wrong, the AI's ability to solve problems - whether hard or easy - is irrelevant.
My greatest focus for business AI is where are the opportunities to give it more context? IMO a business version of Microsoft's Recall would be one such opportunity.
AI that can watch you work coupled with a massive context window is potentially a lot more powerful than a frontier model supplied with questionable context.
@@brightideasagency agreed ... I wrote this on another post elsewhere.
"Start small by implementing a few basic processes and features. It may be a new team, so it will take a few cycles to bed in.
Gather your requirements carefully, paying close attention to safety, security, and regulations. It's also essential to consider your budget, time, and resources. The budget consists of two components: the capital required for development and the operational costs needed for maintenance and optimization moving forward.
A crucial part of gathering these requirements is defining what success looks like.
Next, think about how your new processes integrate into the broader ecosystem of your business or your customer's business. Understand the context, identify dependencies, and clarify the expected outcomes. Clearly outline what actions individuals will take at each stage; a sequence diagram can be helpful for this.
Test what you have created, and start by automating these tests to ensure thoroughness. Your measure during testing is whether it meets the success criteria gathered with the requirements.
Iterate! Work on the next version without cramming everything into the first release. You want to minimize the time between customer feedback and delivery. Conduct your development in continuous cycles, showcasing new features and improvements each time, paying close attention on how they must work together.
Always ensure that your solution is functional and deployed before focusing on optimization. Where improvements or automation are needed is not always obvious, but your customers will provide valuable insights that should inform your improvement roadmap."
I'm not really much of a consultant, I still prefer to build things!