Insights, guides & engineering notes
Practical writing on web and mobile development, cloud, and building software that ships.
Agentic Refactoring: Large-Scale Codebase Migrations
Run large-scale codebase migrations with agentic development workflows: break the work into verifiable chunks, use codemods as safety nets, and ship confidently.
Structured Outputs From LLMs: A Practical Engineering Guide
Learn how structured outputs and schema enforcement make AI engineering reliable — get LLM responses that feed safely into downstream code without parsing failures.
Choosing an AI Agent Framework: A Buyer's Guide
Compare AI agent frameworks by observability, state management, and real production fit — not feature lists — so you choose one you can actually operate at scale.
Offshore vs Nearshore Software Development Compared
Compare offshore vs nearshore software development on timezone overlap, escalation latency, and real cost — not just hourly rates — before choosing a partner.
Concurrent React: useTransition and useDeferredValue
Master concurrent React features useTransition and useDeferredValue to fix input lag on heavy filtered lists — no debounce hacks required.
SwiftUI vs UIKit: Choosing for New iOS Apps
SwiftUI vs UIKit: learn which framework fits new iOS apps in 2026 based on deployment targets, team skill, and where UIKit escape hatches are still required.
Web Authentication Patterns: Sessions vs JWT Tokens
Learn which web authentication patterns actually fit your app. Compare server sessions vs JWT tokens on security, scalability, and token storage tradeoffs.
LLM API Providers Compared: OpenAI vs Anthropic
Compare LLM API providers on per-token cost, rate limits, latency, and structured-output reliability to route requests by task, not brand loyalty.
Prompt Patterns for Coding Agents That Ship Real Code
Master agentic coding with reusable prompt patterns — decompose, constrain, cite-the-file, and stop-condition shapes that move agents from plausible to correct output.
Prompt Engineering Techniques for Reliable LLM Output
Master prompt engineering techniques that produce reliable LLM output — built on failure analysis and iteration, not one-line tricks. A practical guide for AI engineering teams.
Deploying AI Agents: Serverless vs Long-Lived Workers
Choose the right AI agent deployment model: serverless functions vs long-lived workers. Covers state, timeout limits, cost, and production AI agents.
In-House vs Outsourcing vs Staff Augmentation Guide
Compare in-house vs outsourcing vs staff augmentation to find the right software development model for your product stage and burn-rate tolerance.