Food For Thought #89: Scaling Agile Is Futile, Scrum in Asia, How to Kill Features

Age of Product’s Food for Thought of April 30th, 2017—shared with 7,968 peers—features two heavyweight agile champions on why scaling agile is futile. We also can confirm: the further east you go the less Scrum works. Sorry, we needed to address the elephant in the room.

On the product side, we dive deep into how to kill features and why this is important for any aspiring creator of a great product. (Spoiler alert: those embrace simplicity.) We also talk about the “cigarettes” of the B2C web industry, and what it takes to get ‘lean startup’ as a concept going in an enterprise.

Lastly: we learn about the unfortunate trend of creating local maxima due to a lack of long-term thinking. Enjoy Labor Day!

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Food For Thought #88: Big Bang Agile, Hail Failure, Syncing Sales

Age of Product’s Food for Thought of April 23rd, 2017—shared with 7,693 peers—celebrates lasagne from Colgate, pardon me: failure, and why C-level execs believe in big bang agile transitions. (Of course, we know they need passion from ones in the trenches, and Thoughtworks believes that, too.)

We then dive deep into the fetish of estimations, and why agile process-fetishists might turn the DoR into a stage-gate. (Sneaking in the dark side through the backdoor, so to speak.)

On the product side, we have another look at our nemesis, the sales team, and we learn why chefs supposedly make good product managers. Lean startup aficionados might enjoy the MVP, MMF, and MRF analysis.

Lastly: Up your game of convincing other people of your ideas with storytelling and learn right from the source.

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Food For Thought #87: Lipstick Agile, Distributed Agile, Remote Agile, 400 Slack Communities

Age of Product’s Food for Thought of April 16th, 2017—shared with 7,528 peers—enjoys in this issue lipstick agile, tragile, and wagile. Also, we learn why US-made tomato paste represents a success story for self-management aficionados, who – by the way – may soon be joined by venture capitalists like Fred Wilson.

We then dive deep into hands-on tips on how to improve distributed agile in general, and the remote product backlog refinement in particular.

On the product side, it is again all about product discovery, outcome vs. output, real-time, continuous user research, and how Jeff Bezos intends to keep Amazon relevant – by inventing on behalf of customers.

Lastly: If you haven’t yet contributed to the ‘Scrum Master Salary Report 2017’ hurry up and join 435 peers who already did so. And one more thing: We have a list of 400 Slack Communities. Just in case, you may free time at hands.

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Food For Thought #86: Dual-Track Agile, 11th State of Agile, Clarity Metrics, Product Psycho Tricks

Age of Product’s Food for Thought of April 9th, 2017—shared with 7,402 peers—celebrates the 11th Annual State of Agile Report by VersionOne, despite the fact that it reveals a most unsettling news about SAFe.

We ask whether a scrum master should aim for putting herself out of a job, or whether having more than one team at a time is sustainable. We also learn how to support the product owner (and the team) in slicing user stories in the right way.

On the product side, this issue is all about dual-track agile, product discovery, early adopters, and getting the minimum viable product right. Okay, one for the road: ever heard about clarity metrics? Gotcha… 😎

Lastly: We risk a glimpse at the dark side of product design with Uber’s behavioral psychology experiments. Thank you, Travis!

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Food For Thought #85: Agile Success by Trust and Safety, PM Coding, Machine-Learning Overlords

Age of Product’s Food for Thought of April 2nd, 2017—shared with 7,272 peers—revisits the agile mindset, links to the best new podcast on agile issues in months and provides hardcore statistics and scientific proof that trust works and is essential for building an agile organization.

On the product side, Ellen Gottesdiener provides insight into the confusing discussion about the minimum viable product, we learn to identify anti-patterns that point at a dysfunctional product organization, and we breathe a sigh of relief: no coding required when you want to be a product mensch.

Lastly: We learn about Elon Musk’s passion for preventing humanity from falling victim to machine-learning overlords. (A good read if you’re struggling to understand the difference between the Terminator, and the narrow AI, that will put myriads of oncologists out of work.)

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