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Module 6: Q&A Discussion Board

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9 unread replies. 9 replies.

Use this Q&A discussion board to share your insights and post your questions as you engage with the material from this module. Feel free to engage in a healthy discussion with your peers. 

It is not mandatory to participate in this discussion and there is no grade associated with it.

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    • Collapse Subdiscussion Edoardo Bertolani

      Edoardo Bertolani

      I think this is actually a more interesting discussion point because it challenges something in the module itself. The material says that workflows move from personal → team → organisational level, while also recommending being tool-agnostic and choosing the AI platform that best fits the problem.   Those two ideas can create a real tension. One doubt I have is what happens when AI-enabled workflows move from the personal level to the team and organisational levels. At the personal level, I can choose whichever AI tool works best for a specific task. But if everyone does the same, a team may end up using several different AI platforms, agents and applications. At organisational level, this could become even more complicated because workflows need to interact, share information and follow common governance and security standards. So perhaps there is an unavoidable trade-off: do we always choose the best AI tool for each individual task, or do we sometimes sacrifice the “best” tool in favour of a common platform that allows workflows to interact more smoothly? My feeling is that some compromise will be necessary. The individually optimal solution may not be the organisationally optimal one. As agentic AI develops, interoperability between different AI platforms may therefore become just as important as the capabilities of the individual tools themselves.
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      I think this is actually a more interesting discussion point because it challenges something in the module itself. The material says that workflows move from personal → team → organisational level, while also recommending being tool-agnostic and choosing the AI platform that best fits the problem.  

      Those two ideas can create a real tension.

      One doubt I have is what happens when AI-enabled workflows move from the personal level to the team and organisational levels.

      At the personal level, I can choose whichever AI tool works best for a specific task. But if everyone does the same, a team may end up using several different AI platforms, agents and applications. At organisational level, this could become even more complicated because workflows need to interact, share information and follow common governance and security standards.

      So perhaps there is an unavoidable trade-off: do we always choose the best AI tool for each individual task, or do we sometimes sacrifice the “best” tool in favour of a common platform that allows workflows to interact more smoothly?

      My feeling is that some compromise will be necessary. The individually optimal solution may not be the organisationally optimal one. As agentic AI develops, interoperability between different AI platforms may therefore become just as important as the capabilities of the individual tools themselves.

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        • Collapse Subdiscussion Clara Soh

          Clara Soh

          I’ve always been a strong believer in process mapping as part of Lean Six Sigma. But in my 30 years of working experience, I’ve noticed that many organizations skip this step. When issues arise, the first solution is usually automation. And many times, the automation doesn’t solve the real problem because the underlying process was never understood. With the rise of AI, I believe this is even more true. If the process isn’t clear, AI will only amplify the gaps instead of fixing them.
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          I’ve always been a strong believer in process mapping as part of Lean Six Sigma. But in my 30 years of working experience, I’ve noticed that many organizations skip this step. When issues arise, the first solution is usually automation. And many times, the automation doesn’t solve the real problem because the underlying process was never understood. With the rise of AI, I believe this is even more true. If the process isn’t clear, AI will only amplify the gaps instead of fixing them.

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          • Collapse Subdiscussion Jonathan Chew

            Jonathan Chew

            Hi everyone, as with last week, this weeks session will take a significant expansion from the asynchronous content with a lot of additional slides that are adapted from my consulting work. The approach is due to several reasons:  1. Vibe Coding Advanced: Leaves a bit to interpretation especially for those newer to these tools. I aim to help close the loop with a walkthrough and guide of the process of two primary requests around vibe coding; a. How to build a connected app that pulls from data (similar to the weather app) - I will show you one of mine, with step by step screenshots, and explain each step. b. How to leverage Claude Cowork to deploy your own applications (complete with secret keys). 2. N8N: The set-up and configuration of N8N has a variety of questions, at all levels. There are several of you whom have wrote to me with advanced questions, though the majority will struggle with setting it up. I aim to at least, walk through the set-up process tomorrow. This will give us a bit headway so next week's hands-on can be focused on actually working with N8N. Note that time constraints are such that I'll be taking the time to talk through both processes with screenshots, but we will have to balance the familiarity of the entire cohort, along with a need to talk through the key concepts from the asynchronous cohort.  For those of you whom are struggling with the tools as this is all very new, and those who want to learn more from the 'latest in AI' the commitment is we will have a hands on segment each week, where we can introduce new concept or revisit old ones. I see no reason why hands-on sessions should be limited to just phase 2+3.  To get the most of the program, do take what you learn each week and work with tools on your own, should time permit - as practice truly makes perfect. I will showcase 2 student projects, as with last week - for those of you who wish to share your work, this may become a fixture where relevant, and if the cohort can benefit from discussions. Look forward to seeing everyone soon! 
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            Hi everyone, as with last week, this weeks session will take a significant expansion from the asynchronous content with a lot of additional slides that are adapted from my consulting work. The approach is due to several reasons:  

            1. Vibe Coding Advanced: Leaves a bit to interpretation especially for those newer to these tools. I aim to help close the loop with a walkthrough and guide of the process of two primary requests around vibe coding; 

            a. How to build a connected app that pulls from data (similar to the weather app) - I will show you one of mine, with step by step screenshots, and explain each step. 

            b. How to leverage Claude Cowork to deploy your own applications (complete with secret keys). 

            2. N8N: The set-up and configuration of N8N has a variety of questions, at all levels. There are several of you whom have wrote to me with advanced questions, though the majority will struggle with setting it up. I aim to at least, walk through the set-up process tomorrow. This will give us a bit headway so next week's hands-on can be focused on actually working with N8N. 

            Note that time constraints are such that I'll be taking the time to talk through both processes with screenshots, but we will have to balance the familiarity of the entire cohort, along with a need to talk through the key concepts from the asynchronous cohort.  

            For those of you whom are struggling with the tools as this is all very new, and those who want to learn more from the 'latest in AI' the commitment is we will have a hands on segment each week, where we can introduce new concept or revisit old ones. I see no reason why hands-on sessions should be limited to just phase 2+3.  

            To get the most of the program, do take what you learn each week and work with tools on your own, should time permit - as practice truly makes perfect. I will showcase 2 student projects, as with last week - for those of you who wish to share your work, this may become a fixture where relevant, and if the cohort can benefit from discussions. 

            Look forward to seeing everyone soon! 

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              • Collapse Subdiscussion Vinay Nayak

                Vinay Nayak

                My personal journey would involve vibe coding to create an ios app catered to needs around personal finance, my professional journey would involve agentic AI to create AI-first processes. I am realizing that this can change disinfectant depending on whether realtime or batch mode is involved. Real time requires much more data engineering.
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                My personal journey would involve vibe coding to create an ios app catered to needs around personal finance,

                my professional journey would involve agentic AI to create AI-first processes. I am realizing that this can change disinfectant depending on whether realtime or batch mode is involved. Real time requires much more data engineering.

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                  • Collapse Subdiscussion Rakesh Sharma

                    Rakesh Sharma

                    The key point is about balancing the best AI tool for each individual task with the need for common platforms, security, and governance at team and organisational levels. It also highlights that AI should not automate a broken process - organisations must first understand and improve the process before applying AI.
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                    The key point is about balancing the best AI tool for each individual task with the need for common platforms, security, and governance at team and organisational levels. It also highlights that AI should not automate a broken process - organisations must first understand and improve the process before applying AI.

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                        • Collapse Subdiscussion Paris Tzolos

                          Paris Tzolos

                          The module walks us through workflow maturity as a progression, from something living in your head, to written down, to templated, with the idea that once it's templated, AI can absorb it and run with it. I want to push on one assumption in that ladder. Templating assumes the knowledge is visible enough to capture in the first place. But in reality, the most valuable parts of any workflow rarely live in the documentation. They live in the person. The judgment about when to bend the rules. The instinct that tells you something feels off before the numbers confirm it. The pattern recognition that only comes from years of seeing what breaks and what doesn't. And here's the uncomfortable part. If the person carrying that knowledge can't fully articulate it themselves, writing it down won't capture it. Which means your template looks complete but it isn't. The AI absorbs the skeleton of the workflow, not the substance. So to me, surfacing tacit knowledge feels like it should come before the automation decision, not after. But the module doesn't tell us how to do that, or who in the organisation should own it. My question to Jon and the cohort: how do you actually surface tacit knowledge before deciding what to automate? And what happens when nobody in the organisation currently owns that responsibility?
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                          The module walks us through workflow maturity as a progression, from something living in your head, to written down, to templated, with the idea that once it's templated, AI can absorb it and run with it.

                          I want to push on one assumption in that ladder.

                          Templating assumes the knowledge is visible enough to capture in the first place. But in reality, the most valuable parts of any workflow rarely live in the documentation. They live in the person. The judgment about when to bend the rules. The instinct that tells you something feels off before the numbers confirm it. The pattern recognition that only comes from years of seeing what breaks and what doesn't.

                          And here's the uncomfortable part. If the person carrying that knowledge can't fully articulate it themselves, writing it down won't capture it. Which means your template looks complete but it isn't. The AI absorbs the skeleton of the workflow, not the substance.

                          So to me, surfacing tacit knowledge feels like it should come before the automation decision, not after. But the module doesn't tell us how to do that, or who in the organisation should own it.

                          My question to Jon and the cohort: how do you actually surface tacit knowledge before deciding what to automate? And what happens when nobody in the organisation currently owns that responsibility?

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                            • Collapse Subdiscussion Priya Jha

                              Priya Jha (She/Her)

                              I would start by identifying the people who currently hold that tacit knowledge and make them the “humans in the loop/Humans on the loop /Humans over the loop” - accountable for the decisions while AI supports them. Rather than trying to document everything upfront, I would capture the reasoning, exceptions and decisions as they happen. It may not show immediate ROI, but over time, those decisions build a knowledge base that can be reused, challenged and eventually automated. And if nobody currently owns that responsibility, that itself is a signal that the organisation needs to establish clear ownership before automating the process.
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                              I would start by identifying the people who currently hold that tacit knowledge and make them the “humans in the loop/Humans on the loop /Humans over the loop” - accountable for the decisions while AI supports them. Rather than trying to document everything upfront, I would capture the reasoning, exceptions and decisions as they happen. It may not show immediate ROI, but over time, those decisions build a knowledge base that can be reused, challenged and eventually automated. And if nobody currently owns that responsibility, that itself is a signal that the organisation needs to establish clear ownership before automating the process.

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