Most frontend teams optimise build speed.
But few measure how much work is unnecessarily repeated.
We ran into this problem while working on larger frontend systems:
- multiple developers
- multiple apps
- shared dependencies
- constant CI runs
On paper, builds were “fast”.
In practice, we were still wasting time
The Symptom
Our CI pipeline looked healthy.
But we noticed:
- small changes triggered large rebuilds
- identical graphs were recomputed across runs
- the same dependencies were resolved repeatedly
- different apps rebuilt overlapping work
Nothing was technically broken.
But everything was being repeated.
The Root Cause
The issue wasn’t tooling performance.
It was an assumption:
Every build starts from zero.
That assumption forces:
- graph rediscovery
- redundant transformations
- duplicate dependency resolution
- no shared memory between runs
At small scale → acceptable.
At team scale → expensive.
Measuring the Cost
** Even without precise metrics, the pattern was clear:**
- identical work across CI runs
- repeated build steps across developers
- overlapping dependency graphs across apps
Speed improvements didn’t solve it.
They only made repetition faster.
The Shift
Instead of asking:
How do we make builds faster?
We asked:
Why are we rebuilding valid work at all?
The Solution Approach
The key idea is simple:
Treat the build as a persistent graph system, not a disposable process.
This means:
- remembering valid work
- tracking changes at graph level
- invalidating only what changed
- reusing work across runs
Where Ionify Fits
This is the problem Ionify is designed to solve.
Not by optimising execution speed, but by eliminating unnecessary repetition.
Final Thought
Most build discussions focus on speed.
At scale, the real problem is wasted work.
And wasted work isn’t a performance problem.
It’s a memory problem.