O.O.O. #21 Reassessing the productivity standard: the AI conversation we are NOT having

I didn’t want to write yet another newsletter about AI.

But the topic has crept into almost every coffee conversation I’ve had over the past few months.

How are you seeing it, Paula? Are companies still hiring the same way? What’s changing?

I don’t have a crystal ball. I don’t know whether we’re at a real turning point or just another cycle in the industry. What I do have are many conversations piled up, many shared impressions.

With CTOs reviewing what profiles they actually need.
With CEOs who don’t want to fall behind.
With managers wondering whether the performance standard has just changed without anyone officially announcing it.

And, amid very different opinions (some enthusiastic, others cautious, others clearly tense) a feeling keeps repeating itself.

It’s not just the way we work that’s changing.

What’s expected from people is changing.

The silent shift in the standard

So what does it actually mean that expectations are changing?

In many hiring processes we’re no longer talking only about experience or tech stack. The conversation is shifting toward other questions: learning speed. Real autonomy. The ability to integrate new tools without someone pushing it from above.

I’m hearing less and less “we need someone with X years in this technology” and more “we need someone who understands the context,” “who moves fast,” “who enjoys experimenting with new ways of working.”

At the same time, another idea appears. One that isn’t always spoken out loud but is clearly present: if certain tasks can now be done faster thanks to new tools, the implicit standard starts adjusting.

It’s a gradual shift of the bar.

If more can be done in less time: what does performing well actually mean now?

This isn’t an immediate or aggressive demand. It’s more subtle. But it repeats often enough that it doesn’t feel like a coincidence.

What a newly created startup is looking for

In startups that are just being created now, the framework is clear from the start.

They’re looking for senior profiles with strong technical foundations and broad knowledge, but above all they’re looking for autonomy, judgment, and business awareness.

And increasingly there’s an additional condition: they want people who have already experimented with automated code generation processes, people for whom this idea of “vibe coding” doesn’t feel unfamiliar.

In that context, the message is transparent.

Speed is part of the DNA.

The pace is high by definition; almost like jumping onto a train that is already moving and accelerating before you’ve even finished sitting down.

Anyone who joins knows that this is the expectation.

The challenge in a scale-up

The challenge appears in organizations that are already running.

Companies with structure. With established teams. With defined processes. With a culture that has been built over time.

What happens when the CEO feels the market is moving fast, but the CTO wants to evaluate things more carefully?

What happens when part of the team embraces the change enthusiastically, while another part observes it with caution or even skepticism?

And in the middle of all this, another factor appears that is rarely spoken about openly, but is clearly there: fear.

Not necessarily fear of immediate layoffs, but fear of falling behind.

Because while here we are debating standards and adaptation, in the United States we see restructurings and layoffs where AI appears as the narrative in the background.

It isn’t always the real cause, but it often becomes the framework that legitimizes broader decisions.

If the message circulating is that now more can be done with fewer people, pressure starts to settle in even if nobody has explicitly said it.

Impatience begins creeping into meetings.

The bar rises without a clear conversation about how or why.

When expectations accelerate faster than the conversation that should support them, friction appears.

Not because ambition is a bad thing, but because the implicit agreement changes without being renegotiated.

Where the disorder begins

The pressure starts to show up in small details.

Constant comparisons. Impatience with timelines. Lower tolerance for gradual learning.

Teams where each person begins experimenting on their own, trying different tools, working in different ways, optimizing individual processes without a shared standard that organizes all of it.

A kind of permanent laboratory emerges.

And that has something very positive about it: energy, curiosity, and the desire to improve.

But it also has a delicate side.

When there is no shared framework, quality begins to blur and each team interprets the change in its own way.

Not because anyone has bad intentions, but because common references are missing. Experimentation multiplies. Tools change. Ways of working diverge.

But there isn’t always a conversation that brings order to all of it.

And that’s where culture begins to tighten.

Because this isn’t just about adopting technology.

It’s about collectively deciding how we want to work with it, what level of expectations we are willing to assume, and how much space we leave for adaptation.

Cultural leadership in a technological moment

The real debate is not whether we should adopt new tools.

That is already happening.

The more complex question is whether we are dedicating the same time and intention to reviewing what we now expect from the people in our teams and how we communicate it.

Because when the standard shifts without an explicit conversation, what suffers is not only productivity.

It’s trust.

A difficult-to-name feeling starts to appear: not knowing exactly what the new criteria will be for evaluating your contribution.

In environments where there has always been clarity about what doing a good job meant, that ambiguity is very dangerous.

This moment requires cultural leadership, not just technological adoption.

It requires sitting down and defining:

• what pace is sustainable
• what level of experimentation is healthy
• what quality we are not willing to compromise
• what support we will offer to those who need time to adapt

Not to slow down change, but to prevent it from turning into a chaotic race.

If organizations don’t reflect on this consciously, the adjustment will happen anyway.

But it will be shaped by external pressure and internal impatience.

And that’s when cultures begin to lose cohesion without anyone being able to point to the exact moment when it happened.