or doing experiments wrong? And some ABJ testing

Generously, a bot has summarised like this, so you can skip this episode if it's not what you want to listen to.

The concept of "viable" in the context of product development and relationships emphasises its importance over "simply achieving the minimum" to get to green on the next iteration/shipping.

Viability includes ensuring a product or solution is effective for the creator, the customer, and the environment and that it should be meaningful.  It's an easy trap to fall into focusing on the minimum by skipping the critical "minimum meaningful specific" instead of favouring the "minimum I can flag green on the project chart"

The speaker also touches on insecurity in product development, suggesting that accepting they exist and addressing insecurities leads to robust and impactful outcomes. 

Encourage embracing inconvenience and addressing hard questions to create long-term viable and significant work. Finally, the speaker advises listing and being specific about the various viability aspects to ensure that solutions serve their intended purpose effectively.

How can you dare to focus more on viable early and recurring?

To make the meaningful specific as small as possible into the hands of a real user, a real customer or whoever you aim to help who also cares about getting that specific help - so you can learn what matters and quit what doesn't as fast as possible, with as little waste as possible. And especially waste that your future self doesn't thank you for because you were too rushed to cut corners to get to green today.

The generous Autobot said this about today's episode

it emphasises the importance of a collaborative, multiplayer mindset in adapting to the speed of technological advancements. It highlights the need to enhance processes across various aspects, not just individually. In the workplace, it urges reflection on how team members contribute to organisational success, considering their roles, learning speeds, and collaborative efforts.

The piece also explores the difference between human and AI ideas, underlining the significance of cooperation in our rapidly advancing world. Historical misconceptions, like the flat earth theory, are cited to demonstrate how human understanding evolves slowly, advocating for openness to new ideas. The example of handwashing in surgery, which took decades for doctors to accept, illustrates human reluctance to embrace new concepts.

Finally, the text poses a reflective question: if one isn't actively helping others learn and adapt to new technologies, are they truly participating in the collaborative environment knowledge management of today (multiplayer with async singleplayer threads), or are they isolated in the old ways of working (locked single-player mode)

Personal sounding board in today's arena
Choose your HARD problem, and YOUR people who care about that problem don't just say it.

In today's fast-evolving landscape, choosing "your meaningful specific hard problem" and "your people" affected by it is crucial. Soft skills like empathy, understanding, and re-learning have always been essential. They are the core of this 10-year-old podcast, yet today, it's more important than ever.
It's also becoming more accessible and easier to have your software-based sounding board give you tailored, specific answers instantly. This is great, yet bias and filters also pose a risk. AI-powered Ways of Working are already here, and middle managers are greatly affected since most of their work is coordination, communication, resourcing, and decision-making - stuff software often does way better, way more straightforward and without the cost of delay. An illustration in comparison. LinkedIn job ads will have a "get a resume review" button
a year from now; many people will say thanks for helping us train our users to click this button. Top on this service is now an Autobot that will do this for 1% of the price and 90% of the results, making it critical for those who used to live "of/within" that boxed-in service - they now need to find other, better revenue and thus better ways to help their people.

Way of working agile resistance from managers - that kind of transparency and owning what is committed and what not is hard

Automation - SLA, KPI, OKR fulfilment. Often, I've encountered we don't want that automated since that would give conflicting reports with those PowerPoint where I've given myself some poetic freedom not to show all, to round a few metrics up for years, etc.
An organization will only learn to run experiments for continuous risk reduction and better experiences faster and more often. What is the core of this for those you serve? And what experiments and learning should go where since not every initiative should be a win if your organisation aim to do better.

Ask yourself what complex and challenging problem might be worth it and for whom we ask yourself a meaningful specific. You need to be precise; otherwise, you can't follow up if it's working for its intended outcome or if you're becoming better at solving this specific problem.

Ask yourself this question.

What happens when your Autobot instantly gives time back to your boss or client
while also leaving no room for conflicting reports?

You can ask any meaningful, specific question about any problem like this from many perspectives.
Perhaps your client is a higher-up, getting time stolen from conflicting reports, which might help.
Perhaps your client is middle management, juggling multiple perspectives from both upwards and peers.

Perhaps your client is forward-orienting and Happy to let go of sunk cost.
Perhaps she is defending sunk cost whatever it costs?

Asking yourself questions like this, with empathy and daring to choose a whom, daring to choose a what, daring to ask ourselves, does it work great for those we aim to help?
And where is that heading in the big ocean-like waves of change?

Who are you in this and what do you want to become? AND who cares about having those problems solved well in a way that will get you and them there?

There is likely a third more effort, cost, and risk than you perceive and accept. Are you holding space for this? If not, is it worth pursuing?

Peer pressure during our school years often leads to groupthink, causing us to lose our identity in the quest to fit in.

Growing up, for me, it rarely led to anyone's elevation. Instead, it taught me to hide and remain within the margins.

However, the right kind of pressure, combined with a peer, cohort, any group of choice or a mentor's keen observation, can profoundly impact. When we and those we care about hold us accountable for our actions and words, helps us see what we said we would and show us our wants. It helps us to stand up for our beliefs consistently in what we do and say.

You become a reflection of the company you keep.

You directly mirror the expectations of your peer group.

You're not a tree. You can find new places and new groups without moving, yet not without reflecting on your time, and efforts and owning your behaviour

EVERYTHING you do in your work is, from other people's perspectives, a movable part.
Are you designing with that in mind? Are you rearranging what others hold fixed?

It's a wonderfully powerful constraint if embraced, yet often we're surprised by it.

thinking out loud on how do you approach thinking about the unthinkable?
Measuring the unmeasurable?

if discipline is a journey of discomfort and joy, how do we improve?
if doubt and a wavering mind are the opposite of discipline how could "that what if" help those you serve?

is it thus a feeling? if we choose to be resolute in our behaviour it looks a lot like discipline

When working its important we embrace data, metrics, and predictions AND what's hard to measure, quantify, and touch ourselves.

for example when conducting due diligence for our systems, we must consider operations, cybersecurity, privacy by design, AI, sustainability, scalability, costs, and robustness. Equally important is the well-being of the people we serve and those who operate and maintain our systems for their intended purpose. What can be backed up by metrics, code, and documentation? and what is hard to measure yet still needs to be translated into disciplined execution to serve its intended outcome.


As always I don't know and love hearing your thoughts on this.

Below is an image intended to show that you always have your digital twin permanently everywhere and it's impossible to know or measure all it's being used for. Generated by leonardo.ai by some nudges by me