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Crossing the River by Feeling the Stones
Learning wisely, and leading well in an AI-saturated world.
We’re living through a flood.
AI isn’t arriving in waves - it’s arriving all at once. New tools. Hype cycles. Infinite updates. Competing narratives.
I can barely consume five to ten minutes of some news feeds before I’m overwhelmed by the list of new things I need to wrap my head around and process. We’re in a constant state of not-quite-enough knowledge, and then interrupted by the next thing that makes you feel behind again.
It’s what political strategist Steve Bannon once called “flooding the zone with shit” - a tactic to overwhelm reason by overwhelming attention. It’s bold and deeply offensive, as tactics go - mostly because it’s so damned effective on us humans.
Our social feeds are full of half-truths, bold lies, and genuinely useful new tools that leave us feeling like we have to pay attention or risk being left behind. What was once political now feels cultural, and while this flood is unintentional - it's no less disorienting.
For teams trying to learn, explore, or apply AI responsibly, the sheer volume of change makes the task of navigating it as a leader feel huge. Not because AI is too complex - but because the learning process has become scattered, noisy, fragmented.
We believe there’s a better way.
At behavjōr, we’ve spent years helping organisations design for behaviour - not just the systems people use, but the systems teams use to deliver. The rhythms, mindsets, and small decisions that shape how people work together.
And what we’ve seen is this:
The teams who thrive in times of complex change don’t charge into the river alone. They step in together and start to move by feel. They cross by sensing, adjusting, and pausing. They place each foot deliberately, grounded in principles that hold.
The title of this piece comes from a Chinese proverb popularised (by Deng Xiaoping) during China’s economic reforms: "Cross the river by feeling the stones.” It means moving carefully through uncertain terrain. Testing each step. Staying present to what’s underfoot. It’s how we think teams should approach learning and building with AI - not with full certainty, but with deliberate movement, anchored in what matters.
Traditional learning was long-form: hours of content, fixed sequences, feedback at the end. Today, we learn in microcycles -short, focused bursts of doing, testing, adjusting, and repeating. It's faster, more responsive, and more compatible with the way teams work now.
AI is accelerating this shift. Used well, it’s already improving outcomes in education. Some research shows that just two hours a day of AI-assisted learning can drive real gains - when it’s tailored to how someone learns best.
But there are new perils too. Used too much and it can cause cognitive overload, create surface-level understanding, raise anxiety and cause burnout.
And if you use it to save you from doing the thinking? for cheating on your home work? Well, there’s a cost there too.
Studies from MIT, the Financial Times, and The Guardian show the risks of fragmented, always-on learning are that our retention is far less, and our capacity for critical thinking is reduced, while an increasing dependence on AI to do the hard work of thinking - grows.
So the challenge isn’t how to learn faster.
It’s how to learn with intent. How do you stay grounded when the ground keeps shifting?
That’s where a few principles come in handy.
Most teams aren't thinking about this pro-actively, few are thinking collectively. But through our own efforts to position ourselves on the wave of AI - we’ve found there four principles help teams stay steady when everything else is in flux.
They won’t solve everything. But they’ll give you something solid to stand on.
How we work - and what we return to when things speed up - matters. If teams learn as a group they evolve faster, and in a more sustainable direction. This raises everyones capability and sets standards.
A good practice returns, again and again, to its purpose.
Your team will learn faster, and with more clarity, if they’re not constantly distracted by the newest tool or locked into outdated habits. Create a shared space for capturing what’s being tried: tools, prompts, lessons, observations. Make learning visible. Make it collaborative. Set aside time weekly to ask, together:
“Does this new practice serve what we’re here to do?”
Why are we doing this - and what do we hope to change? Without a clear sense of outcome, it’s easy to learn something impressive that doesn’t move the needle. This is about purpose. Behaviour. Impact. What are we actually trying to shift, improve, or protect? Who benefits? What does success look like?
"If you do not know what change you seek, how will you know when you have found it?"
- Socrates
Design your learnings - not just for use, but for change.
How we deliver great work - and the tools we choose to do it are always important. The craft of delivery still matters. In a world full of noise and novelty, it's easy to get distracted by what's new each day instead of what works.
This principle is about maintaining a high standard in what you produce, and being deliberate in how you produce it.
Share the best tools. Refine your methods. Help each other get better.
When a new tool or process appears, ask:
“Does this help us raise the quality of what we’re making?”
When are the critical points in your process to stop and think - not just for a second, but to reflect, assess, and apply independent judgment?
Thinking time isn’t a delay. It’s part of the work. It’s when you decide what “good” really looks like - and often, that clarity is what makes something really valuable.
Even five minutes of pause can shift what happens next. Reflection is how we avoid drifting. It’s how we see patterns. It’s how learning sticks.
A lack of reflection impacts quality
In Zen and the Art of Motorcycle Maintenance, Robert Pirsig explores what happens when we stop paying attention to the quality of things - not just in what we make, but in how we think, how we work, and how we live.
He warns that when we rush ahead without reflection, we lose the ability to recognise quality - or define it for ourselves. Over time, we start valuing what's easy to measure, what's fashionable, or what's efficient - rather than what’s meaningful.
He calls this the moment when we stop noticing what matters, and become swept up in what he described as “the silt of tomorrow.” The fast, shallow, accumulating debris of unchecked progress. The stuff that builds up when you move too quickly, too broadly, and without care.
Pirsig draws a sharp contrast between two kinds of attention: one that is wide and unfocused, and one that is deep and deliberate. In a world obsessed with scale, speed, and novelty - this is a radical idea.
But perhaps the most practical one.
There’s no map to chart these waters yet - at least for this moment. Maybe this space will move so fast there never will be - or maybe with time patterns will emerge and ways of practice and learning will adapt.
The real challenge of this time - when everything AI floods the zone - is to learn with intent.
That’s how we cross.
By feeling the stones.
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