AI Agent, Rules Engine, or Conventional Software: How to Choose
The question is rarely whether a task could use an AI agent. It is how much the input varies and what a wrong answer costs. A practical way to match a task to an approach.
DrieVerse Tech Blog
Field notes from the software, AI and infrastructure work we ship for clients: what we built, the constraint that forced the decision, and what we would tell you if you were about to build the same thing.
The question is rarely whether a task could use an AI agent. It is how much the input varies and what a wrong answer costs. A practical way to match a task to an approach.
A backlog nobody has ordered gets ordered by whoever complained most recently. Here is how to rank automation candidates by the hours they actually return.
If three vendors quote three different projects, the brief may be the problem, not the vendors. Here is what a software project brief actually needs to cover.
Buying and building are not opposites. The real decision is which parts of your stack are commodity, which are differentiated, and what the workaround is already costing you.
Most incident runbooks are either too vague to use under pressure or too detailed to keep current. Here is what actually earns a place in one.
RAG is not a magic fix for a model that does not know your data. It is a specific architecture with real tradeoffs. Here is what it actually does and when it is the wrong tool.
A discovery call is a two-way evaluation. Here is what we are actually listening for, and why some conversations end with us recommending someone else.
Discovery is not a meeting series, it is a deliverable. Here is exactly what a discovery phase should hand you before a single sprint starts.
A tired logo and a brand problem look similar from the inside. Here is the actual test for which one you are facing before you commission either.
A first product version almost never needs microservices. Here is the actual test for when it does, and what a monolith costs you if you guess wrong.
Before the first commit against an inherited codebase, run an audit that answers what it actually does, what depends on it, and what breaks first if you get it wrong.
Automation earns its keep on high-volume, well-defined steps. It fails quietly on judgment calls dressed up as rules. Here is how to tell the two apart before you build.
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