More workshops just add to the chaos. What the top 1% of AI teams do instead.

More workshops just add to the chaos. What the top 1% of AI teams do instead.

PLUS: Human-in-the-loop is not a compromise. Our data show the opposite.

From the aibl team

Not long after ChatGPT fell on us back in 2023, my colleagues and I started scoping AI training courses. What would people need to understand? How could they gain competence and competitive advantage in a few hours of on-demand education? As it turned out, we were a bit early to the game. Leadership at client companies didn’t know what they didn’t know, and didn’t want to train people on a technology they hadn’t vetted (and being honest, didn’t understand themselves).

In the mother of all understatements, a fair bit has happened since then, and yet many companies are still looking for the right kinds of training to unlock the human side of their cyborg teams.

Max Haining has answers. Max is the founder of 100 School, an AI capability business. He’s spent the last two years studying what separates the teams that have genuinely changed how they work from the ones still waiting for the tools to do it for them. The gap, he argues, is behaviour. You can read the full interview below.

Our research data this week is about people too. ‘Humans in the loop’ aren’t a sign of weak AI workflows. On the contrary, we find that the companies that are successfully extracting real ROI tend to have more human intervention, not less. Both threads are on the table next Tuesday at #growthLIVE. If you haven’t applied to attend yet, don’t delay.

Why most AI training changes nothing and what to do instead

“For the last two years, organisations have been chucking mud at the wall,” says Max Haining. “Now lots of companies are thinking: we’ve made a huge investment here. How do we actually turn it into results?”

Max is the founder of 100 School, an AI capability business. He’s spent the last two years studying what separates the teams that have genuinely changed how they work from the ones still waiting for the tools to do it for them. The gap, he argues, is behaviour.

The best teams he’s observed haven’t just got faster; they’ve escaped whole categories of work. He calls them the Navy SEALs of AI. They “feel like they’re living in the future. Ultimately, they’re not doing any of the same tasks as two years ago.”

Most organisations aibl works with are nowhere near that. The tools are in place; the ways of working haven’t followed.

Watch the full video interview:

aibl’s Research: The Human Conditions for AI-Driven Efficiency

The human conditions for AI-driven efficiency

Our message this week is dead simple: the definition of AI success isn’t to get people out of the loop.

The data back up what we’ve been hearing in our interviews with successful operators. The companies focused on revenue growth that report positive ROI actually have more human intervention in their core AI workflows than their peers, not less.

We’re still at the stage where people have more institutional knowledge, instinct, and creativity than any AI system. The point isn’t to automate what people can still do better — it’s to restructure how time is spent and value is created.

Product spotlight of the week

This week we’ve been tracking DOJO AI, a platform that just closed a $6 million seed round and is gaining momentum with mid-market marketing teams running a broad channel mix on lean headcount.

Most teams are managing a dozen or more separate tools for paid media, SEO, content, and reporting, with nothing connecting them. DOJO pulls those channels into one system, where AI agents monitor performance, surface issues, and in some cases act on them rather than flag them.

The clearest fit for mid-market firms is a growth-focused team with real spend across Google, Meta, and LinkedIn but not enough people to run deep analysis on each. Customers including PensionBee and Morningstar report lower acquisition costs, though figures are vendor-reported. Pricing starts at $499 per month with a 7-day trial.

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