Practical guidance on AI integration, cloud migration, DevOps, and custom software — written by the engineers who ship it.
Choosing between a monolith and microservices isn't a permanent identity — it's a sequencing question. Here is a framework for deciding which one you need now, and a real case where going back to a monolith cut infrastructure cost by 90%.
RAG and fine-tuning get compared as if you have to pick one. In practice they solve different problems — RAG handles knowledge that changes, fine-tuning handles behavior that shouldn't. Here is how to decide which your project actually needs.
Not every application should move to the cloud the same way. Here's the framework for deciding which workloads to lift-and-shift, which to re-architect, and which to leave alone.
Picking the wrong software development partner costs more than a bad invoice — it costs months of rework and a codebase you don't fully understand. Here is a practical framework for vetting one before you sign anything.
An MVP isn't a smaller version of your product — it's the fastest, cheapest way to find out if anyone wants it. Here is how to scope one that actually validates your idea instead of just shipping fewer features.
Zero-downtime deployment isn't one technique — it's a choice between blue-green, canary, and rolling strategies, each with a different cost and rollback profile. Here is how they actually differ, and the database migration step that breaks most 'zero-downtime' releases anyway.
Off-the-shelf software wins on speed and low upfront cost. Custom software wins when your workflow, data, or differentiation no longer fit what you can buy. Here is how to tell which side of that line your business is on.
AI integration costs range from about $10,000 for a single API-based feature to $500,000+ for a production agent platform. Here is what actually drives that number, and how to keep your project on the cheap end of its range.
