New tech earns its way in. We evaluate honestly, prototype before we promise, and only adopt tools that solve a real problem better than what already works.
We're not anti-new. We are anti-rewriting-the-stack-because-it's-Tuesday. New tools and new models genuinely change what's possible — but most of them don't change what's wise.
Our test is straightforward: does this technology solve a real, named problem better than what we already have, given the cost of adoption, training, and ten years of maintenance? When the answer is yes, we move. When the answer is unclear, we prototype against a real workload and make the call from data.
AI is a good current example. We use it where it removes drudgery and improves outcomes, and we leave it out where it would add fragility, opacity, or risk that the user hasn't agreed to.