How I wrote a working web app with ChatGPT and Claude, and what you can learn from it

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Prelude I’m a professional techie, but no longer a professional developer — my badge and git permissions were handed in over a decade ago. This post reflects my experience using Generative AI tools to build a working web application from the perspective of someone who is extremely rusty on the day-to-day tasks of being a software engineer.

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Forming. Storming. Norming. And the other one… the lesser known history of Tuckman’s team model

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Forming. Storming. Norming. Performing. You may well have heard these stages of group maturity before, but do you know where the theory came from? This article is inspired by the Teamcraft podcast episode, available wherever you get your pods. In 1965 a young psychologist, freshly minted with a PhD from Princeton, joined the Naval Medical

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Part 6: The Best of Both Worlds: Human Developers and AI Collaborators

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How Generative AI will impact product engineering teams — Part 6 | Postscript This is the final part of a six part series investigating how generative AI productivity tools aimed at developers, like Github Copilot, ChatGPT and Amazon CodeWhisperer, might impact the structure of entire product engineering teams. In this final part we consider many of the

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Part 5: Who wins and who loses? How different types of business could be impacted by AI tools.

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How Generative AI will impact product engineering teams — Part 5 This is the fifth part of a six part series investigating how generative AI productivity tools aimed at developers, like Github Copilot, ChatGPT and Amazon CodeWhisperer might impact the structure of entire product engineering teams. In Part 4, we explored: Cui Bono — Who benefits? There are always winners

Part 5: Who wins and who loses? How different types of business could be impacted by AI tools. Read More »

Part 4: If AI coding tools reduce the number of engineers we need, where do we spend our budgets?

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The Impact of AI on Product Engineering teams — Part 4 This is the fourth part of a six part series investigating how generative AI productivity tools aimed at developers, like Github Copilot, ChatGPT and Amazon CodeWhisperer might impact the structure of entire product engineering teams. In Part 3, we explored: What will our new organisations look like? LLMs

Part 4: If AI coding tools reduce the number of engineers we need, where do we spend our budgets? Read More »

Part 3: If engineers start to use AI coding tools, what happens to our product teams?

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Image by author using Midjourney The Impact of AI on Product Engineering teams — Part 3 This is the third part of a six part series investigating how generative AI productivity tools aimed at developers, like Github Copilot, ChatGPT and Amazon CodeWhisperer might impact the structure of entire product engineering teams. In Part 2, we explored: How generative

Part 3: If engineers start to use AI coding tools, what happens to our product teams? Read More »

Part 2: The proliferation of Generative AI Coding Tools and how Product Engineering teams will use them

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Image by author using Midjourney How Generative AI will impact product engineering teams — Part 2 This is the second part of a six part series investigating how generative AI productivity tools aimed at developers, like Github Copilot, ChatGPT and Amazon CodeWhisperer might impact the structure of entire product engineering teams. In Part 1, we explored: The landscape

Part 2: The proliferation of Generative AI Coding Tools and how Product Engineering teams will use them Read More »

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