Food for Agile Thought #505: GPT-5, Building Product Sense, The 'Just Ship It' Issue, Future of Scrum Teams
Also: Painted Door Test, GPT-5 Best Practices, Agile AI Agents, Disposable Code
Hello everyone!
Welcome to the 505th edition of the Food for Agile Thought newsletter, shared with 40,569 peers.
This week, Grant Harvey highlights how OpenAI’s GPT-5 merges prior models into a unified system with smarter routing, improved reasoning, reduced hallucinations, and new personal assistant capabilities. Christina Wodtke reframes product sense as learnable pattern recognition, sharpened through structured practice, while Leah Tharin warns that while AI accelerates simple work, over-shipping without impact wastes resources. Ethan Mollick explores GPT-5’s proactive, multi-model intelligence, and Dan Shipper’s team praises its speed, usability, and versatility despite some coding limitations.
Next, Janna Bastow details how painted door tests validate demand before building, saving resources and guiding priorities when used responsibly. Kyle Poyar shares 12 ChatGPT workflows boosting GTM efficiency across marketing, sales, and growth, and OpenAI highlights GPT-5’s coding, reasoning, and customization strengths with new API controls. Dave West contends AI makes Scrum fundamentals more vital. Also, Charity Majors notes that durable code remains crucial even as AI accelerates disposable software creation.
Lastly, Alexis Gauba and Ben Hylak note GPT-5’s strength in engineering and parallel tasks, though writing quality has dipped. Microsoft presents 1,000+ AI adoption cases driving efficiency and innovation. Kevin Kelley reflects on AI’s role in personal, private creation, and StaySassy urges trimming metrics to a few actionable ones. Finally, Pawel Brodzinski stresses communication quality over coding speed as the real driver of estimation accuracy, even with AI-assisted development.
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🏆 The Tip of the Week
(via The Neuron): GPT-5 is here… here’s everything you need to know (so far…)
Grant Harvey reports that OpenAI’s GPT-5 unifies previous models into a single system with smarter routing, boosting coding, reasoning, health, and writing skills, reducing hallucinations, and introducing personal assistant features and expanded developer tools.
Source: The Neuron: GPT-5 is here… here’s everything you need to know (so far…)
🎯 Product
Christina Wodtke: Building Product Sense: Why Your Gut Needs an Education
Christina Wodtke explains that product sense is learned pattern recognition, not magic, and can be developed faster by actively dissecting successful products, analyzing flows, and writing observations to turn gut feelings into informed judgment.
Source: Building Product Sense: Why Your Gut Needs an Education
Author: Christina Wodtke
Leah Tharin: AI’s ‘Just Ship it.’ problem
Leah Tharin argues that while AI speeds up simple tasks, it cannot solve complex problems or speed validation, and over-shipping without impact risks waste, missed opportunities, and ultimately shipping yourself out of business.
Source: AI’s ‘Just Ship it.’ problem
Author: Leah Tharin
Janna Bastow (via ProdPad): Nailing the Painted Door Test: When and How to Fake it Before You Make It
Janna Bastow explains how painted door tests quickly validate feature demand before development, helping teams save resources, de-risk big bets, and prioritize with evidence, while avoiding misuse that erodes trust or delivers misleading signals.
Source: ProdPad: Nailing the Painted Door Test: When and How to Fake it Before You Make It
Author: Janna Bastow
Kyle Poyar: What GTM teams are doing with ChatGPT
Kyle Poyar shares 12 real-world ChatGPT workflows from GTM teams, spanning product marketing, content, growth, and sales, showing how it streamlines research, localization, experimentation, personalization, and insights while cutting time and costs.
Source: What GTM teams are doing with ChatGPT
Author: Kyle Poyar
🧠 Artificial Intelligence
Ethan Mollick: GPT-5: It Just Does Stuff
Ethan Mollick describes GPT-5 as a proactive multi-model system that autonomously selects approaches, suggests next steps, and builds surprisingly complex outputs from minimal prompts, reducing friction for everyday and advanced AI use.
Source: GPT-5: It Just Does Stuff
Author: Ethan Mollick
(via OpenAi): Using GPT-5: Learn best practices, features, and migration guidance for GPT-5
OpenAI outlines GPT-5’s strengths in coding, instruction following, and tool use, plus new API controls for reasoning, verbosity, and custom tools, offering migration guidance and best practices for maximizing performance.
Source: OpenAi: Using GPT-5: Learn best practices, features, and migration guidance for GPT-5
Dan Shipper (via Every): GPT-5: Our hands-on review of OpenAI’s newest model based on weeks of testing
Dan Shipper and team find GPT-5 a fast, simplified daily driver for most users, offering competitive pricing and strong research, writing, and pair programming skills. However, it lags behind Claude Code for large, autonomous coding tasks.
Source: Every: GPT-5: Our hands-on review of OpenAI’s newest model based on weeks of testing
Author: Dan Shipper
Ben Hylak and alexis gauba (via Latent Space Podcast): GPT-5 Hands-On: Welcome to the Stone Age
Alexis Gauba and Ben Hylak share that GPT-5 excels at software engineering, tool use, and parallel task execution, marking a shift toward agent-like behavior. However, it lags in writing quality compared to earlier models.
Source: Latent Space Podcast: GPT-5 Hands-On: Welcome to the Stone Age
Authors: Ben Hylak and alexis gauba
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➿ Agile & Leadership
Dave West (via Scrum.org): AI And The Future Of Teams — Scrum Fundamentals Are Still Relevant
Dave West argues AI will become a valuable Scrum team member, increasing the need for discipline, transparency, and empiricism, making Scrum fundamentals more relevant for both teams and individuals working with AI.
Source: Scrum.org: AI And The Future Of Teams — Scrum Fundamentals Are Still Relevant
Author: Dave West
Charity Majors (via Honeycomb): Disposable Code Is Here to Stay, but Durable Code Is What Runs the World
Charity Majors argues that software is splitting into disposable and durable code, with AI impacting both. Still, durable code remains essential for high-stakes, reliable systems where trust, maintainability, and long-term confidence are critical.
Source: Honeycomb: Disposable Code Is Here to Stay, but Durable Code Is What Runs the World
Author: Charity Majors
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🛠 Concepts, Practices, Tools & Measuring
Kevin Kelly: An Audience of One
Kevin Kelley explores how AI lowers the barriers to creation, enabling people to co-create primarily for personal joy. Most AI-generated works will remain private, serving as self-communication rather than seeking a broader audience.
My hypothesis is that in the near future, the bulk of creative content generated by humans — with the assistance of AI — will have an audience of one. Most art generated each day will be consumed primarily only by its human co-creator.
Source: An Audience of One
Author: Kevin Kelly
staysaasy: You Have Too Many Metrics
The author argues that most teams track too many metrics and waste effort, urging focus on a few actionable ones with clear expectations, regular review, and committed action when results fall outside agreed bounds.
Source: You Have Too Many Metrics
Author: staysaasy
Pawel Brodzinski: The Most Underestimated Factor in Estimation
Pawel Brodzinski argues that in product development, communication quality outweighs coding speed in affecting estimates, with poor communication doubling workload and strong collaboration significantly reducing effort, regardless of AI-assisted coding capabilities.
Source: The Most Underestimated Factor in Estimation
Author: Pawel Brodzinski
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