Concept
Predictable by default. AI on purpose.
Most automation asks you to trust a black box. Deterministic-first starts from the opposite place — plain, predictable steps by default, with AI added only where you decide it earns its keep.
Same in, same out
Run it again. Get the same thing.
A deterministic step takes the same input and produces the same output — every time, with nothing left to interpretation. Ask a model the same question three times and you'll get three different answers; run a plain step three times and you get the same one, three times.
Deterministic step
$0 · repeatable · auditable
AI step
~$ · varies · needs a check
On purpose
AI is the exception, not the default.
Every step in a Destaris workflow starts out plain — reading a webhook, checking a condition, writing to a database. AI only enters where you explicitly turn it on for a single step, never as the default engine running underneath everything else.
That's the whole idea behind AI opt-in per step: you pick exactly where a model gets a say, and the rest of the workflow runs — fast, free, and predictable — without one.
Why it matters
What predictability buys you.
Auditable
Read every step and know exactly what it will do — no hidden reasoning trace to take on faith, no model deciding something you can't see.
~Free to re-run
Deterministic steps cost nothing to repeat. Re-run the whole workflow as many times as you need without watching a token meter climb.
No surprises
Same input, same output, every single run. The boring 90% of automation stays exactly that — boring, in the best way.
Go deeper on deterministic-first
Read the concept doc for the full model — what counts as deterministic, how AI opts in per step, and how determinism shows up as a first-class signal on the canvas.