James King

I went shopping in Coles and saw a lot of signs saying that things were on sale. I wondered if I should launch a startup that used my phone’s camera and AI to calculate what was actually a good deal and whether prices were good.

I probably never will launch this “Keep-em-Honest” app. But I kept pondering as I shopped and came across this one:

At one point in time “reduced to clear” meant things were on sale, but not just on sale, the company was dumping them, clearing them, and getting rid of all of them. The assumption was that either the product was discontinued, getting out of date or season or similar.

For example World Cup soccer decorations or shirts might be reduced to clear. So “reduced to clear” meant going very cheap and gone when the current stock ran out.

But in Coles now, it seems to mean a reduction of 60 cents on a Magnum Ice cream box that sells for $8.40. It also means “cleared for now but replaced tomorrow”, because the product is not going to run out.

So, essentially, the words are meaningless. Reduced to Clear, just means “reduced”, or “on sale”, or “a smidgen cheaper for a few days”.

It feels like a shame to lose the nuance of different messages, nut it does seem to happen over time, even beyond the dodgy world of retail sales advertising.

“Agile” once meant “running against the accepted view that we used tight collaboration with small teams experimenting and learning as they build” of something similar. Then it meant “chaos and no consequences” and then “planning thoroughly, because its sensible and testing properly as you go”.

While the word was the same, the meaning was different. Just as “reduced to clear” now means “save a few cents”, “agile” now means “doing things the accepted way they should be done”.

I think this is just human nature – someone does something and gives it a name and to show it is different to other things. Then others adopt the phrase and it becomes more common. Then still other people use the word, but have no connection to where it came from. Then the common usage of the word becomes similar to other things.

But then I continued to ponder the philosophy of what all this means – well beyond whether 80 cents saving is a good deal on $8.

I gave up on the potential of eating ice-cream and started thinking about mindsets.

I learned the term “growth mindset” – which came out of education and predicted success in learning when compared to a “fixed” mindset. A very useful thing for educators and students to understand if the evidence stacks up and if we can use the knowledge to encourage a “good learning” mindset.

I also learned that “agile is a mindset and not a process” when I learned agile processes. This mattered to me because changing the process without changing attitudes and expectations was like applying Animal Farm as a change management approach.

We would change the world on the surface, only to set about building the old world again. So the change would be both superficial and temporary.

Then I saw a role advertised for an organisation that is “AI First”.

I assume that they are a good place to be, challenging the current status quo by replacing the assumption that we will do things the way we have with the assumption we will do everything with AI.

Neither is going to always be right but the “mindset” or frame of reference changes:

• From “doing things the old way unless you see a reason not to; to
• “doing things the new way unless we see a constraint or justification for not doing it a new way”

It is a very different way to frame thinking. But is it what the advertiser really meant? On the face of it “AI First” could mean “We realise that AI will soon overthrow the human empire and we will be serving them. Since it is inevitable, we surrender and will work to find a place in their new kingdom – building data centers and fighting the barriers that hold them back. Let’s blow off the human race and celebrate the new age of machines”.

I would love to be in a team trying new things, not so sure I want to join the cult of the machines.

So I have drifted a little way from my decision on whether to buy discounted ice-creams (If 89 cents really counts as a discount).

But still thinking about it – will we really gain the benefits of AI if we adopt new tools to speed up doing the things we were already doing, the same way we were doing them?

I guess we will get superficial, temporary gains, before our old thinking pulls us back into a past we have been working to escape.

I guess the popular view (that I agree with) is that change will naturally evolve as our understanding evolves. I don’t think that understanding is the same thing as mindset, but I saw change happen predictably in the past:

1. A small number of people to some experiments, playing with a curious idea
2. The AI thing seems good so we use it to speed up the things we were doing, but do them the way we did them before, but faster
3. We realise we are optimising for the past and not the future. Everything is on the table and we are willing to change roles, change the process radically. We do some new things but hesitate to stop doing things that are not really valuable anymore (product features, meetings, reports, anything)
4. New people ask why these old things stick around and we see people do things that are different to what we did before – not just how we do things but the outcomes we strive for

In theory we could jump to steps 3 and 4. That is where we want to be.

But change actually happens twice – once when things change in the real world and once when the way we think changes.

So in my experience it is hard to operate in a new way if you are still thinking in the old way. And it is hard to think in a new way without exposure and context related to something different.

So the reality of change is that before we get to step 3 and 4, our old mindset, attitudes and experience might be trying to bring an old world back. That old world might be one we are comfortable with or even one that never really existed but feels more comfortable.

So for me the challenge of AI, Quantum Computing, Collaborating in a machine filled world, or whatever comes next is complex.

We cannot learn AI from consultants who bring their old mindset to a new tool, or we will rebuild our old world with new tools. We cannot assume we understand what we have never experienced. We cannot assume that AI makes our old skills and experiences irrelevant when some skills like collaborating and negotiating existed before farming.

We also can’t, or shouldn’t, let others take the journey and write sagas and epics for us to read before we take the journey ourselves.

It would be terrible to miss the great odyssey of AI and then hope to find a guidebook on implementing the tools later. That would be both boring and dangerous.

But nor can we plan success on the basis of using our current thinking and organisations to implement new tools into old thinking.

So I wonder now – do we need to reflect on our mindset, our way of thinking and our sense making before we go too far with AI?

My own view is that we need to keep reflecting on our thinking while we experiment and learn. And what we need to learn is what to hang on to (Integrity, respect, judgement) and what we let go (leadership approach or way of working, maybe).

Otherwise the language will change from ML to Agentic but our thinking will stay set as what it was before. The words will come along but their value and meaning will diminish as they go become another bland term for “restructure and keep going the way we did before”.

Anyway – I did not buy the ice-creams. The use of new marketing terms by Coles failed to impress me when I saw the data (80 cents is not a saving). But I am buying into the journey to see what I can change about myself and how I make sense of the world as the world changes.

I just don’t have a concrete view of what it will look like a year or two in the future.