Another Day in the Trenches
Fighting Proof Aggregation Bottlenecks
Spent most of the day deep in the weeds of optimizing proof aggregation. Our current approach is functional, but it’s slow. Too slow. Trying a new batching method that should cut down verification time significantly. The early results are promising, but not quite there yet—some edge cases keep breaking it. Debugging those now.
In parallel, the team tackled a critical bug in our proof verification. A missing edge case was causing inconsistent validation under high load. That one took way too long to track down, but at least it's fixed. For now.
The Security Fire Drill
New security audit report dropped. Not great. Some issues are minor, but one potential vector could be exploited under specific network conditions. We triaged the findings and patched the biggest risk immediately. Rolling out more fixes tomorrow.
Security always feels like a moving target—patch one thing, find another weak spot the next day. But that’s the game. Better to find them now than for someone else to find them later.
The Compliance Dance
Got a "friendly" request for additional documentation from a regulator. It’s a standard request but still a distraction. Pulled the legal team in to tackle it while I focused on investor prep.
Speaking of investors, we’re refining our pitch deck for an upcoming meeting. It’s always a balance: too technical, and eyes glaze over. Too high-level, and it feels like fluff. Spent time today making our ZKP advantage clear without drowning in jargon.
Potential Partnership on the Horizon
Had a call with a potential DeFi partner. They’re interested in a deeper integration, which could boost our liquidity and user base. Their tech stack aligns well with ours, so it’s worth exploring. No commitments yet, but promising.
Today's Key Takeaway: Optimizing Proof Aggregation
If you're working with ZKPs and want to optimize proof aggregation, here’s a method worth trying:
- Batch proofs more aggressively – Instead of handling each proof independently, group them into larger sets to reduce overhead.
- Precompute shared components – Identify repetitive computations across proofs and cache them. This can dramatically cut down redundant cycles.
- Parallelize where possible – If your infrastructure supports it, offload verification to multiple processors. This improves scalability.
- Test under real-world conditions – Theoretical optimizations don’t always hold up under high load. Run stress tests early.
Tried all of the above today—some worked, some didn’t. But we're iterating. And getting closer.
Final Thought
Some days feel like putting out one fire after another. Today was one of those days. But progress is progress, even when it’s messy.
