Working principles • what guides my decisions

Engineering Principles

These are working principles, not universal rules. Each one links to a case study or note where the trade-off became concrete.

[01]

STATE & DATA GRAPH

Local-first is almost always worth the complexity.

PROOF IN PRODUCTION // [CASE STUDY]Local Beam — Enterprise P2P Sync Engine

[02]

AI ARCHITECTURE

The application owns control flow; the model owns language.

PROOF IN PRODUCTION // [FIELD NOTE]Why most AI agents are over-engineered

[03]

INFRASTRUCTURE SELECTION

Boring infrastructure wins until proven otherwise.

PROOF IN PRODUCTION // [FIELD NOTE]I rejected Pinecone, GraphQL federation, and Kafka

[04]

PERFORMANCE & UX

Measure latency budgets before optimizing algorithms.

PROOF IN PRODUCTION // [FIELD NOTE]Building internal tools people use

[05]

RELIABILITY & INGRESS

Every distributed system needs explicit failure boundaries.

PROOF IN PRODUCTION // [SYSTEM REVIEW]Stripe Webhook Delivery & Reliability Infrastructure

[06]

AI INFERENCE SLA

Schema validation at the boundary makes bad inputs visible early.

PROOF IN PRODUCTION // [FIELD NOTE]Designing AI workflows people can actually maintain

[07]

CONCURRENCY & ACID

Atomic SQL metering prevents race conditions without table locking.

PROOF IN PRODUCTION // [CASE STUDY]PingPanda — Atomic Quota Metering & Edge Ingestion

Engineering Dialogue

Want to challenge these tenets?

I am always interested in a well-reasoned disagreement about systems, constraints, and trade-offs.

Initializing System StateSUB-100MS EDGE SLA // INGRESS ROUTING