Once work becomes visible, evaluation can become visible too. A salesperson can use one workflow to prepare for a demo, while their manager uses another to evaluate that preparation against clear criteria. The manager still applies judgement, but not from scratch and not by instinct alone. That’s how performance evaluation becomes more consistent, more useful and fairer.

Lego works because the bricks are standardised. The value compounds because the same components can be reused to build something new. Work rarely functions like that. Most tasks are reinvented by each person, in each team, inside each workflow. But once an important task is properly designed, it can become a reusable component — improving every workflow that depends on it.

Once tasks become reusable components, performance improvement stops being a series of isolated fixes. Two people in different parts of the organisation may be working on completely different outputs, yet struggling with the same underlying task. If that task is captured, designed and improved once, the value compounds. That’s when work starts to behave like a system — a Performance Guidance System.

A Performance Guidance System is not another tool sitting alongside the others. It’s a guidance layer that helps people use their tools, knowledge and workflows more effectively. Like a satnav, it reduces the need to stop, search, remember or guess. And unless people understand that distinction, they’ll judge it through the wrong lens.

We don’t need to wait for the perfect platform. Notion may show what’s possible, but guided workflows can start with the tools organisations already have. The real limitation isn’t technology — it’s that most businesses haven’t defined their work, captured what good looks like, or embedded guidance where people need it. That’s where L&D can start becoming genuinely useful.

Performance enablement is bigger than business improvement. If people can only perform within the limits of their environment, then the design of work shapes what organisations are capable of achieving — from companies and charities to governments and health services. We’re not just redesigning workflows. We’re engineering the conditions that allow people to do their best work.

AI makes everything feel urgent, but the principles underneath performance improvement are timeless. Someone will always need to understand the work before technology can support it. That means the ability to deconstruct, analyse and improve work is not a passing AI skill. It’s an evergreen capability — and those who create space to ask better questions will be the ones who remain valuable.

Experts often struggle to explain how they do what they do. The skill is real, but much of the process is tacit — hidden in judgement, experience and instinct. That matters because AI needs clarity: instructions, context and guardrails. So the ability to unpack expert performance, make it visible and design around it is becoming one of the most valuable skills we have.

There’s an irony in using emails to argue that performance improvement shouldn’t rely on content. But emails can still do something useful: shift mindsets. Before people redesign work, they first need to care. That’s where learning experiences still matter. Not as the solution to performance problems, but as the spark that helps people see why the work itself needs to change.

The course may be finished, but the work is only just beginning. AI is racing ahead, yet most organisations still haven’t built the basic systems that help people perform: guidance, standards, feedback, measurement and continuous improvement embedded into the work itself. That’s the real opportunity ahead — not another tool, but a new discipline for enabling performance. Workflow Engineering.