WRITING

Blog

We occasionally write about building production AI systems, hard engineering decisions, and what actually works in the field.

A practical roadmap for agentic AI integration

How to introduce agentic AI into an existing business without turning the first release into a risky platform rewrite.

What to log, trace, and measure before giving AI agents real operational responsibility.

How to use human review, approvals, and escalation paths to make AI automation safer and more useful.

Practical starting points for AI agents in support, CRM, account operations, and customer-facing workflows.

How to decide whether an AI feature belongs inside a mobile app, and how to design it so users actually benefit.

Why launch time, frame stability, network behavior, and battery use directly affect whether users keep a mobile app.

A practical way to compare native, shared-code, and cross-platform mobile options without framework hype.

The backend pieces that make AI products reliable: queues, permissions, state, audit logs, integrations, and cost controls.

How to design least-privilege access, audit trails, and data boundaries for AI agents that can use tools.

The practical gap between an impressive AI prototype and a reliable production system that teams can operate.

A practical Golub Softworks field note on designing agentic AI systems around real operational boundaries, not loose prompts and disconnected tools.