How we think
about what's next.
Why most AI agents fail in production (and how to fix them)
Building a demo agent is easy. Building one that runs 40,000 decisions a day without hallucinating, looping, or silently failing — that's a different problem entirely. Here's what we've learned.
Web3DeFi protocol security: what audit firms won't tell you
We've shipped multiple protocols that went through major audits. Here's what auditors catch, what they miss, and how we think about security from day one.
AutomationThe 80/20 of business automation: where to start
Most companies over-engineer their first automation. After mapping hundreds of workflows, here's how we identify the highest-leverage starting point every time.
EngineeringNext.js at scale: lessons from 3 years of production apps
From routing decisions to RSC adoption, incremental builds to edge functions — the non-obvious architectural choices we've made and why they held up.
AIRAG isn't retrieval — it's context engineering
Everyone calls it retrieval-augmented generation but the bottleneck is never retrieval. It's knowing what context an LLM actually needs to reason correctly.
Web3Token design mistakes that kill protocols before launch
Bad tokenomics can undermine a technically perfect protocol. These are the five mechanism design failures we see most often — and how to avoid them.
EngineeringWhy we stopped using ORMs for complex queries
ORMs are great until they're not. After hitting the ceiling on three different projects, we rebuilt our data layer around raw SQL + typed query builders.
AutomationIntegrating 14 data sources without losing your mind
The unglamorous reality of data pipeline work: mismatched schemas, rate limits, silent failures, and the tooling decisions that made it manageable.
AIEvaluating AI agents: beyond accuracy metrics
Accuracy alone doesn't tell you if an agent is production-ready. Here's the evaluation framework we use before shipping any autonomous system.