logo
episode-header-image
Jul 2024
44m 17s

Untrapping Product Teams and Getting Rid...

One Knight in Product
About this episode

David Pereira is a product leader, speaker and regular blogger who loves to contribute to the wider Agile and Product communities with insights from his own career, including some of the mistakes he's made and not just the successes. David was recently tempted into writing a book, the newly released "Untrapping Product Teams" where he provocatively rails against "bullshit management" and tries to inspire us all to affect change in our organisations (but step-by-step). We talked all about themes from the book, as well as what it meant to have an endorsement from Marty Cagan.

Episode highlights:

 

1. When someone starts doing something differently and delivering value, people get curious

Sometimes it can seem almost impossible to change things yourself, but you don't have to change it all at once. If you can start showing the impact of smaller changes that deliver value then you can get both interest and buy-in from stakeholders. This gives you permission to try more things.

2. The more bullshit you handle the less value you create

David coined the term "bullshit management" to represent the work you have to do in many low-performing product companies. Bullshit management is where you spend all your time working on the work around the work, prioritising requirements with no context and being actively prevented from delivering value to your users, and it has to stop.

3. Collaborative flow trumps coordinative flow

Coordinative flow is when you spend more time in meetings about the work and struggle to align people than you do actually doing the work. It's focused on outputs and gives you someone to blame when it goes wrong. Collaborative flow is when teams come together to work on problems... collaboratively and use what they know to uncover what they don't know.

4. You don't need to die on every hill

Sometimes you have to hold your nose and do things in ways that you don't believe are effective, or actively destructive. This is part and parcel of the job and something you have to get used to. As long as you can find small ways to make an impact in some areas, you can give way in other areas. Rome wasn't built in a day.

5. If you really want to make an impact, ask more questions than you give answers

We're all primed to look clever and give answers as quickly as we can but product people need to think deeper than that and ask good questions. Why do we really need that? What does success really look like? What don't we know?

Check out "Untrapping Product Teams"

"Untrapping Product Teams guides you to simplify what gets unintentionally complicated and equips you to overcome dangerous traps while steadily driving customer and business value. This isn't just another book about product management. It's a thought-provoking guide filled with simplicity, encouraging you to act today for a better tomorrow."

Check it out on Amazon.

Contact David

You can catch up with David on LinkedIn or check out his website.

Related episodes you should like:
Up next
Aug 17
CPO Stories: Jamie Mercer - TrustedHousesitters
In this episode, I speak with Jamie Mercer, Chief Product Officer at Trusted Housesitters, the global pet care and travel marketplace disrupting two industries at once. Jamie has previously held senior product roles at VoucherCodes, Skyscanner, Student Beans and IVC Evidensia, an ... Show More
48m 12s
Aug 11
CPO Stories: Shiri Mosenzon Erez - commercetools
In this episode, I speak with Shiri Mosenzon Erez, Chief Product Officer at commercetools, a global leader in enterprise composable commerce that supports thousands of retailers in hundreds of countries, enabling tens of billions of dollars in revenue annually. Shiri's career jou ... Show More
46m 47s
Aug 4
CPO Stories: Hannah Kershaw - Domestic and General
In this episode, I speak with Hannah Kershaw, Chief Product Officer at Domestic and General, a company that you might not have heard of but absolutely need in your corner the next time your dishwasher breaks. Hannah's journey took her from marketing to e-commerce, into product le ... Show More
44m 13s
Recommended Episodes
Aug 2024
ChatGPT has a language problem — but science can fix it
AIs built on Large Language Models have wowed by producing particularly fluent text. However, their ability to do this is limited in many languages. As the data and resources used to train a model in a specific language drops, so does the performance of the model, meaning that fo ... Show More
36m 50s
Jul 22
Are World Models the Key to AGI?
A groundbreaking Harvard study trained AI on 10 million solar systems and found it perfectly predicted orbits but completely failed to understand gravity, raising questions about whether LLMs can develop true world models. While companies pour billions into scaling, Meta's Yann L ... Show More
21m 28s
May 2023
TinyML: Bringing machine learning to the edge
When we think about machine learning today we often think in terms of immense scale — large language models that require huge amounts of computational power, for example. But one of the most interesting innovations in machine learning right now is actually happening on a really s ... Show More
45m 45s
Aug 2023
Cuttlefish Model Tuning
Hongyi Wang, a Senior Researcher at the Machine Learning Department at Carnegie Mellon University, joins us. His research is in the intersection of systems and machine learning. He discussed his research paper, Cuttlefish: Low-Rank Model Training without All the Tuning, on today’ ... Show More
27m 8s
Feb 2017
MLG 002 What is AI, ML, DS
Links: Notes and resources at ocdevel.com/mlg/2 Try a walking desk stay healthy & sharp while you learn & code Try Descript audio/video editing with AI power-tools What is artificial intelligence, machine learning, and data science? What are their differences? AI history. Hierarc ... Show More
1h 5m
May 8
MLG 035 Large Language Models 2
At inference, large language models use in-context learning with zero-, one-, or few-shot examples to perform new tasks without weight updates, and can be grounded with Retrieval Augmented Generation (RAG) by embedding documents into vector databases for real-time factual lookup ... Show More
45m 25s
Sep 2024
Large Language Model (LLM) Risks and Mitigation Strategies
As machine learning algorithms continue to evolve, Large Language Models (LLMs) like GPT-4 are gaining popularity. While these models hold great promise in revolutionizing various functions and industries—ranging from content generation and customer service to research and develo ... Show More
28m 58s
Feb 2017
MLG 001 Introduction
Show notes: ocdevel.com/mlg/1. MLG teaches the fundamentals of machine learning and artificial intelligence. It covers intuition, models, math, languages, frameworks, etc. Where your other ML resources provide the trees, I provide the forest. Consider MLG your syllabus, with high ... Show More
8m 11s
Mar 2024
Figure 01 humanoid robot
Genuine-friend.com. The super capabilities of Figure 01, the humanoid robot developed by the startup Figure, are attributed to its integration with OpenAI's advanced AI technologies. Here's how OpenAI contributes to Figure 01's exceptional capabilities based on the provided searc ... Show More
16m 38s