TL; DR: The Perils of Deterministic Thinking — Food for Agile Thought #388
Welcome to the 388th edition of the Food for Agile Thought newsletter, shared with 46,012 peers. This week, we delve into the perils of deterministic thinking and reflect on what growth may mean for a Scrum team, covering the spectrum from product discovery to DevOps. Also, we suggest strategies to minimize the influence of engineering work’s two most costly factors and point to wrong ideas typically plaguing agile transformation, from installing practices to changing culture to the mystical one-time change effort.
Then, we share real-life examples, including prompts on how product managers already use ChatGPT daily and follow John Cutler, who looks beyond the usual product-market fit approach, claiming that the biggest challenge is Product-Reality Fit instead. Also, we map the problem of creating product goals onto the Cynefin Framework and detail what experimentation entails in the complex or chaotic domain. Speaking of creating goals: you want to mitigate the risk of running in the wrong direction. Ant Murphy suggests an excellent tool for that: the pre-mortem risk analysis.
Finally, Sevawise Games created a free Monte Carlo Estimation tool that supports Parabol’s fine primer on estimation, from Planning Poker to Wall Estimation to #NoEstimates. Moreover, we explore whether we can use ChatGPT-4 to create workshops for agile practitioners; for example, Scrum Masters. Lastly, Dave Gray details the development steps of the well-known Innovation Ecosystem Map.
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🏆 The Tip of the Week: The Perils of Deterministic Thinking
(via Medium): Resisting Deterministic Thinking
Danah Boyd warns of the “deeply entrenched deterministic thinking,” leading many people who “espouse deterministic thinking to believe themselves to be hyper-rational.”
🍋 The Lemon of the Week
(via Medium): Agile Founders Embarrass Themself: SAFe is Agile
Manfred Friedrich rejects notions of many agile luminaries on SAFe, insisting that SAFe is agile, repeating its sales brochure.
➿ Agile & Scrum
: Is Good, Good Enough?
Mark Levison reflects on what growth may mean for a Scrum team, covering the spectrum from product discovery to DevOps.
: Programmer Interrupted: The Real Cost of Interruption and Context Switching
Piotr Karczmarz suggests strategies to minimize the influence of engineering work’s two most costly factors.
(via Leading Agile): 4 Common Misconceptions About Agile Transformation
Mike Cottmeyer delves into wrong ideas typically plaguing agile transformation, from installing practices to changing culture to the mystical one-time change effort.
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🎯 Product
: How to use ChatGPT in your PM work
Lenny Rachitsky shares real-life examples, including prompts on how product managers already use ChatGPT daily.
: Product-Reality Fit (PRF)
John Cutler looks beyond the usual product-market fit approach, claiming that the biggest challenge is PRF instead.
A big challenge is that people underestimate the impact of inertia and overestimate their ability to solve new problems. Each successive failure gets chalked up to poor execution, poor-fit leaders, or similar, and every success gets chalked up to genius. And this can go on for years—with an ever-increasing divergence between product and reality.
(via Medium): Do You Really Want Your Teams to Experiment? Are you Sure?
Grant Gadomski maps the problem of creating product goals onto the Cynefin Framework and details what experimentation entails in the complex or chaotic domain.
📯 Workshop Design with ChatGPT
The following article explores whether we can use ChatGPT-4 to create workshops for agile practitioners; for example, Scrum Masters. While Liberating Structures have simplified the task, workshop design with ChatGPT may provide an alternative.
As you will learn, and despite being prone to lapse into project management speak, ChatGPT is remarkably capable of doing so, provided we feed it suitable prompts. Whether this requirement gives ChatGPT an edge over manually creating workshops remains to be seen.
👉 Learn more: Workshop Design with ChatGPT .
🛠 Concepts, Tools & Measuring
: Monte Carlo Online Estimation Tool
Sevawise Games created a free Monte Carlo Estimation tool.
(via Parabol Focus): 12 Agile Estimation Techniques to Try With your Team
Parabol created a fine primer on estimation, from Planning Poker to Wall Estimation to #NoEstimates.
(via Medium): How To Run a Pre-Mortem: Mitigate against risks that matter
Ant Murphy sketched the steps of running a pre-mortem risk analysis.
🎶 Encore
: The story of an XPLANATiON: How we developed the Innovation Ecosystem Map
Dave Gray detailed the development steps of the well-known map.
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📺 Join 4,000-plus Agile Peers on Youtube
Now available on the Age-of-Product Youtube channel to improve learning, for example, about the perils of deterministic thinking:
- Hands-on Agile 47: How much Product Discovery Is enough? The Confidence Meter Explained with Itamar Gilad.
- Hands-on Agile 46: The Agile Fluency Model ® with Diana Larsen.
- Hands-on Agile 44: Honey, I Shrunk the Backlog with Allan Kelly.
- Hands-on Agile 43: Outcome-Based Product Planning with Jeff Gothelf.
- Hands-on Agile 42: Lean Roadmapping and OKRs with Janna Bastow.
- Hands-on Agile 38: The Product Owner with Roman Pichler.
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Help your team to learn about the perils of deterministic thinking by pointing them to the free Scrum Anti-Patterns Guide :
🗞️ Last Week’s Food for Agile Thought Edition
The post Food for Agile Thought #388: Perils of Deterministic Thinking, ChatGPT for Product Work, Interruption & Context Switching, Pre-Mortems appeared first on Age-of-Product.com .