Engineering essays from the bench.
War stories, architecture decisions, and the occasional tirade. Written by the engineers who shipped it.
API Security Best Practices: A Production Checklist
API security best practices that hold up in production: object-level authorization, full token validation, strict schemas, rate limits and logging, with code.
SIEM and Security Operations: Building a SOC That Works
How to build a SOC around a SIEM: which logs to collect first, detection as code with Sigma, alert tuning, automation, staffing, and when to choose MDR.
React Native for Cross-Platform Apps: Lessons from Production
Lessons from production React Native: architecture decisions, native module integration, performance tuning, and deployment.
Bias and Fairness in Machine Learning: A Practical Guide
How to find, measure and reduce bias in ML models: where bias enters, choosing a fairness metric, Fairlearn code, LLM audits and monitoring in production.
Multi-Cloud Strategy: When It Makes Sense and How to Do It
When multi-cloud is worth the cost and when it is not: good and bad reasons, workable patterns, cross-cloud identity, networking, egress and failure modes.
Incident Response Playbook: Template and Worked Example
How to write an incident response playbook that works at 3 a.m.: roles, severity levels, a template, a full leaked-cloud-key example, and notification clocks.
REST vs GraphQL: How to Choose the Right API Design
REST vs GraphQL for production APIs: caching, N+1 queries, versioning, errors and security, with a decision table and the failure modes each one brings.
Running High-Performance Remote Engineering Teams
A practical guide to building high-performance remote engineering teams with async communication, documentation culture, tooling, and effective management.
How to Fine-Tune an LLM: When It Pays Off, LoRA and QLoRA
When fine-tuning an LLM beats prompting and RAG, how to build the dataset, train with LoRA or QLoRA, evaluate against a baseline and run adapters safely.
How to Scale an Engineering Team From 5 to 50 Engineers
Hiring order, team topology, on-call and ownership for each stage from 5 to 50 engineers, what breaks at each size, and the fixes that hold up.
