Before we started building o2, we kept running into the same assumption over and over again: that certain tradeoffs in trading systems are unavoidable.
Speed vs transparency.
Performance vs decentralization.
Good UX vs onchain execution.
Most teams don’t question these constraints. They optimize within them.
We decided to question the constraints instead.
This post isn’t a feature breakdown but a reflection on what we learned while trying to design a trading system that doesn’t rely on hidden execution layers or off-chain interpretation to work at scale.
A few things became very clear early on:
Many “performance” gains in DeFi come from pushing complexity off-chain, not from better design.
Transparency stops being meaningful once execution logic lives somewhere users can’t verify.
Systems that look fine at low volume often reveal their real costs only under pressure.
Building fully onchain was slower and more complex than taking shortcuts. But it also forced discipline. Rules had to be explicit. Incentives had to be enforceable. Behavior had to be anticipated, not patched later.
One unexpected outcome was how much this changed how we thought about incentives. Once rules are enforced as code, they stop being guidelines and start shaping real behavior. That changes everything in competitive trading environments.
We wrote up a deeper version of these insights here, if you’re interested in the full thinking behind it:
👉 https://paragraph.com/@o2dotapp/performance-without-compromise
I’d be genuinely curious how other builders think about these tradeoffs, especially anyone who’s had to balance performance, transparency and long-term reliability in production systems.
Top comments (3)
I think for such platforms, trust matters the most and when the entire DEX is onchain it helps to build the trust and without any tradeoffs is the cherry on top.
Love to see that. What's the best way to look at the architecture of the app?
You can dig into the architecture overview in the docs: docs.o2.app They go into Sway contracts, order books, registries, executor layers, APIs etc. I’d start there for a full system view.