At EdSmart, AI is no longer a pilot program. It’s becoming part of how we build, how we make decisions and how we improve the platform our customers rely on every day.
In the last month, we’ve had weeks where 100% of our code was written by AI, with our whole engineering team now working this way by default.
That is an important milestone for us. But the more important question is: what does it mean for our customers?
EdSmart is not a new product being built from scratch.
Our platform has been developed over 12 years and supports schools in managing important communications, processes and interactions with their communities. That means every change needs to be considered carefully.
Reliability, security, usability and duty of care remain fundamental.
Using AI does not change that responsibility.
What it changes is where our engineering team can spend its time.
By using AI to support more of the repetitive implementation work, our engineers can spend more time on the areas where their expertise adds the most value: architecture, solution design, problem solving and understanding how a change will work in the real world.
For customers, that means we can move from idea to improvement more quickly, while maintaining the oversight and discipline expected of a platform used by schools every day.
.jpg)
One of the biggest benefits of AI-assisted development is not simply that code can be produced faster.
It is that our team has more capacity to think.
Instead of spending as much time on routine development tasks, our engineers can focus more deeply on questions such as:
That shift matters.
The value of software is not measured by how much code is written. It is measured by whether it makes life easier for the people using it.
AI gives us an opportunity to spend more of our effort on exactly that.
Nine months ago, AI adoption within our engineering team was low and scepticism was high.
We deliberately avoided treating adoption as a top-down mandate.
Instead, we demonstrated what good use looked like, gave the team room to experiment safely, learned from external frameworks and progressively developed our own standards.
That has allowed capability to build across the team while keeping human oversight firmly in place.
We are already seeing the impact in the pace at which work can move through engineering.
For schools, the benefit is straightforward: useful improvements can reach customers sooner.
That might mean resolving pain points faster, responding more quickly to customer feedback, improving existing workflows or creating new capabilities that previously would have taken considerably longer to deliver.
There is an important distinction between using AI to accelerate development and handing responsibility over to AI.
We are doing the former.
Our engineers remain accountable for the solutions we design, the code that enters the platform and the quality of what we release.
AI can help generate code, explore options and reduce repetitive effort. It does not replace engineering judgement, testing, review or governance.
If anything, our goal is to use the time AI gives back to strengthen those higher-value activities.
For customers, that means greater speed should not come at the expense of trust.
.jpg)
We are now embedding these practices into the way our engineering team operates permanently and beginning to apply the same thinking across other parts of EdSmart.
For us, becoming AI-native does not mean adding AI to everything for the sake of it.
It means asking a more fundamental question:
If we were designing the way this work happens today, knowing what AI can now do, would we still do it the same way?
Sometimes the answer will be yes.
Increasingly, it will be no.
That creates an opportunity to rethink processes, remove unnecessary work, improve decision-making and put more human effort into the things that genuinely require experience, judgement and understanding.
For EdSmart customers, our move toward AI-native ways of working should ultimately be visible in the outcomes rather than the technology behind them.
You should expect us to:
We are still early in this transition.
But what began as experimentation is becoming a new way of working across EdSmart.
And the measure of whether we are getting it right will not be how much AI we use.
It will be whether our customers get a better product, faster.
We're not treating this as a sprint result to celebrate and move on from. We're building it into how we run engineering permanently, because the thing that got us to 100% wasn't the tools — it was the judgement to use them well. That judgement is what tells us when AI speeds up good decisions and when it would speed up bad ones. On a platform schools depend on, that distinction is the whole job.
So the number isn't really the achievement. The achievement is that our team now makes that call, correctly, by default — and that's exactly what schools have always trusted us to get right. We just do it faster now.
EdSmart enhances your core systems
Get Started
.jpg)
.png)
.png)