Most things are harder to understand than they appear. Not because they are complicated, but because we stop too early. At the surface. At the abstraction. At the explanation that feels good enough.
Real understanding lives underneath, in the structure and trade-offs you only see once you start pulling things apart. This is a place for going that far.
Like a walnut, the mind only reveals itself once you crack it open.
I work across AI, distributed systems, databases, and infrastructure. The deeper I go, the more I notice how much useful knowledge is scattered across docs, talks, and conversations that never get written down clearly.
Cracking Walnuts is my attempt to write what I wish I had while learning. Not surface-level overviews, but deep dives that deal with real trade-offs instead of pretending there's always a clean answer.
Everything here comes from something I've built, debugged, or spent too long trying to understand. If it helped me think more clearly, it's worth writing down.
How distributed databases actually work. Spanner, CockroachDB, ClickHouse, Apache Iceberg, and the real trade-offs between them.
Authorization models, end-to-end encryption, passwordless auth. How systems protect data and verify who you are.
QUIC, WebTransport, BGP. The protocols that move data across the internet and why they matter.
AI agents, machine payments, autonomous systems. Exploring what's actually being built right now.
Multi-tenant systems, domain-driven architecture, scalable patterns. Solving real problems, not textbook ones.
If something I wrote was useful, or wrong, or you just want to talk about this stuff, I'd love to hear from you.
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