Zoom's summary from Lean Coffee 10th April 2025
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Leon Hewitt
May 1, 2025, 10:47:05 AMMay 1
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We decided to try out Zoom's AI note taking tool. Here's how it summarised our ramblings...
Don't forget that it's lean coffee next week: 8th May. 7.30 for 7.45 on the usual zoom link.
You show me yours.... (LLM usage)
The team discussed the use of AI for note-taking and facilitation in meetings. They found the AI note-taking feature useful, as it allows them to focus on the conversation rather than taking notes. However, they noted that the AI's understanding of scrum masters and software development is limited. They also considered creating their own version of AI for software development, but acknowledged the challenges of filtering out irrelevant information. The team then proceeded with a discussion on the possibility of creating useful software using only AI.
Is it possible to create useful software using only AI (yet)?
Charles discussed a student project where they were to use AI to create a useful product from internet sources. He was concerned about the possibility of the AI producing something completely different each time. Dimitry suggested that iterations are necessary and that feedback could be obtained by looking at the results. Murray mentioned that there are Youtube videos demonstrating the use of AI to produce useful applications. Chris suggested that AI could be used as an assistant to a human, but it would not be able to create something useful on its own. He emphasized the importance of clear specification for AI to create something useful.
The team discussed the limitations of AI in understanding and replicating human specifications. Chris emphasized that AI is only as good as the input it receives, and poor specifications will result in poor outputs. Jim shared insights from a recent AI conference, highlighting that AI is not a replacement for developers but rather a tool that enhances efficiency and quality. Dimitry added that the effectiveness of AI depends on the problem's complexity and the human's ability to explain it. The team agreed that AI's capabilities will continue to grow with experience and usage.
Murray and Leon discussed the challenges of maintaining code produced by AI and junior developers. Murray emphasized the importance of non-functional requirements like maintainability and security. Charles agreed, noting the difficulty in specifying good code to AI or junior developers. Chris Matts suggested using AI to help developers understand code bases by creating a document of good code attributes and generating prompts to rewrite code in a more understandable way. Murray questioned how often code gets rewritten, while Chris Matts clarified that the goal is to improve understanding of existing code, not replace it.
Murray discussed the challenges of defining good code and the importance of understanding code at different levels of proficiency. He shared a YouTube video demonstrating the creation of an AI agent for Slack. Chris clarified that understanding code involves writing a document about one's level of comprehension, regardless of the original author's skill level, to facilitate code maintenance and improvement.
In the meeting, Chris shared a valuable tool called Notebook LM, which he found particularly useful for reading difficult articles. He demonstrated how to upload articles and generate a discussion between two people, which he found helpful for understanding complex topics. Murray also shared a link to a YouTube video about AI-powered retrospectives, which he found useful.
The team discussed their experiences with AI tools, particularly Chat GPT. Charles shared how he used Chat GPT to rewrite a blog post in corporate style, while Chris shared a cautionary tale about how a recent update in Chat GPT's censorship policies affected its responses. Murray also shared his experience with a corporate performance appraisal tool. The team agreed that AI tools can be both helpful and misleading, depending on the context and the tool's settings.
Murray discussed the evaluation process based on self-set priorities and the use of AI tools for feedback. He mentioned the importance of accuracy and readability in feedback, and how AI can assist in this process. Leon and Charles agreed on the potential benefits of using AI for feedback, including reducing the influence of personal writing styles. John shared his experience with using AI for writing, highlighting the benefits of AI in providing context and summarizing content.
Is there any good agile literature since 2010?
Murray discussed the concept of "vibe coding" from Andre Kapathy, co-founder of Open AI, which involves describing a problem in a few sentences as a prompt for AI source code. Charles and John agreed that this concept could be beneficial. Is there any good agile literature since 2010? Ian recommended the book "Accelerate" by Nicole Forsgren, which uses data from the State of DevOps report to analyze connections between techniques and outcomes. However, Chris disagreed, stating that the book has been misused at the executive level and has not addressed the real problem of disconnect between business funders and the people doing the initiatives. He suggested that metrics that the business cares about are needed. John agreed with Chris's point about the failure of the book to extrapolate all the way back out.
The group discusses the misapplication of popular business books and the role of thought leaders in the agile community. Chris argues that thought leaders can be damaging by suppressing good ideas and promoting concepts prematurely. The conversation shifts to the fragmentation of agile disciplines and the need for collaboration, especially in light of emerging technologies like AI. Murray suggests that current advancements in software development are mostly fine-tuning existing ideas, and recommends books by John Cutler and Emily Weber for further insights.
The meeting concludes with participants expressing gratitude and saying their goodbyes.
Don't forget that it's lean coffee next week: 8th May. 7.30 for 7.45 on the usual zoom link.
You show me yours.... (LLM usage)
The team discussed the use of AI for note-taking and facilitation in meetings. They found the AI note-taking feature useful, as it allows them to focus on the conversation rather than taking notes. However, they noted that the AI's understanding of scrum masters and software development is limited. They also considered creating their own version of AI for software development, but acknowledged the challenges of filtering out irrelevant information. The team then proceeded with a discussion on the possibility of creating useful software using only AI.
Is it possible to create useful software using only AI (yet)?
Charles discussed a student project where they were to use AI to create a useful product from internet sources. He was concerned about the possibility of the AI producing something completely different each time. Dimitry suggested that iterations are necessary and that feedback could be obtained by looking at the results. Murray mentioned that there are Youtube videos demonstrating the use of AI to produce useful applications. Chris suggested that AI could be used as an assistant to a human, but it would not be able to create something useful on its own. He emphasized the importance of clear specification for AI to create something useful.
The team discussed the limitations of AI in understanding and replicating human specifications. Chris emphasized that AI is only as good as the input it receives, and poor specifications will result in poor outputs. Jim shared insights from a recent AI conference, highlighting that AI is not a replacement for developers but rather a tool that enhances efficiency and quality. Dimitry added that the effectiveness of AI depends on the problem's complexity and the human's ability to explain it. The team agreed that AI's capabilities will continue to grow with experience and usage.
Murray and Leon discussed the challenges of maintaining code produced by AI and junior developers. Murray emphasized the importance of non-functional requirements like maintainability and security. Charles agreed, noting the difficulty in specifying good code to AI or junior developers. Chris Matts suggested using AI to help developers understand code bases by creating a document of good code attributes and generating prompts to rewrite code in a more understandable way. Murray questioned how often code gets rewritten, while Chris Matts clarified that the goal is to improve understanding of existing code, not replace it.
Murray discussed the challenges of defining good code and the importance of understanding code at different levels of proficiency. He shared a YouTube video demonstrating the creation of an AI agent for Slack. Chris clarified that understanding code involves writing a document about one's level of comprehension, regardless of the original author's skill level, to facilitate code maintenance and improvement.
In the meeting, Chris shared a valuable tool called Notebook LM, which he found particularly useful for reading difficult articles. He demonstrated how to upload articles and generate a discussion between two people, which he found helpful for understanding complex topics. Murray also shared a link to a YouTube video about AI-powered retrospectives, which he found useful.
The team discussed their experiences with AI tools, particularly Chat GPT. Charles shared how he used Chat GPT to rewrite a blog post in corporate style, while Chris shared a cautionary tale about how a recent update in Chat GPT's censorship policies affected its responses. Murray also shared his experience with a corporate performance appraisal tool. The team agreed that AI tools can be both helpful and misleading, depending on the context and the tool's settings.
Murray discussed the evaluation process based on self-set priorities and the use of AI tools for feedback. He mentioned the importance of accuracy and readability in feedback, and how AI can assist in this process. Leon and Charles agreed on the potential benefits of using AI for feedback, including reducing the influence of personal writing styles. John shared his experience with using AI for writing, highlighting the benefits of AI in providing context and summarizing content.
Is there any good agile literature since 2010?
Murray discussed the concept of "vibe coding" from Andre Kapathy, co-founder of Open AI, which involves describing a problem in a few sentences as a prompt for AI source code. Charles and John agreed that this concept could be beneficial. Is there any good agile literature since 2010? Ian recommended the book "Accelerate" by Nicole Forsgren, which uses data from the State of DevOps report to analyze connections between techniques and outcomes. However, Chris disagreed, stating that the book has been misused at the executive level and has not addressed the real problem of disconnect between business funders and the people doing the initiatives. He suggested that metrics that the business cares about are needed. John agreed with Chris's point about the failure of the book to extrapolate all the way back out.
The group discusses the misapplication of popular business books and the role of thought leaders in the agile community. Chris argues that thought leaders can be damaging by suppressing good ideas and promoting concepts prematurely. The conversation shifts to the fragmentation of agile disciplines and the need for collaboration, especially in light of emerging technologies like AI. Murray suggests that current advancements in software development are mostly fine-tuning existing ideas, and recommends books by John Cutler and Emily Weber for further insights.
The meeting concludes with participants expressing gratitude and saying their goodbyes.
Kevin Rutherford
May 1, 2025, 10:49:45 AMMay 1
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Pretty comprehensive!
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