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Practical guides to AI-driven development, full-stack architecture, and solving production problems.
Showing 1–12 of 100 articles
Decide when a simple solution has reached its limits
Recognize when a simple architecture needs to evolve by measuring constraints, comparing focused alternatives, and planning a reversible transition.
Turn a recurring incident into a maintainable engineering checklist
Turn recurring incidents into focused engineering checks with clear triggers, evidence, owners, and verification instead of an ever-growing generic checklist.
Use AI to compare two fixes without delegating the decision
Use AI to compare engineering fixes through constraints, counterexamples, and observable tests while keeping technical judgment with the development team.
Find the smallest safe fix when several layers look suspicious
Find the smallest safe bug fix by testing competing causes, protecting existing behavior, and choosing evidence over broad speculative refactoring.
Debug a production-only bug with a small evidence bundle
Build a small, redacted evidence bundle for production-only bugs so environment differences can be investigated without guessing or exposing customer data.
Choose caching only after defining what may become stale
Choose a cache only after defining acceptable staleness, ownership, invalidation, and recovery so faster responses do not return misleading data.
Set a performance budget that can fail in CI
Create a practical CI performance budget with stable test conditions, observable user journeys, and clear thresholds that detect meaningful regressions.
Fix slow image delivery without sacrificing clarity
Fix slow web images by checking intrinsic dimensions, responsive sizing, compression, caching, and layout stability without making every asset blurry.
Diagnose memory growth in a long lived web process
Diagnose growing Node.js memory by separating heap usage, buffers, retained references, and resource lifetime before increasing the memory limit.
Find why a page feels slow even when the API is fast
Learn to diagnose a slow page when its API is fast by separating network timing, JavaScript work, rendering, and interaction feedback.
Create a threat model for an AI enabled full stack feature
Threat-model an AI feature by tracing untrusted inputs, retrieval, tool authority, tenant boundaries, and consequential outputs into testable abuse cases.
Run end to end tests without touching production customer data
Run end-to-end checks with isolated environments, synthetic accounts, safe providers, explicit target guards, and cleanup that remains reliable after failure.
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