Silkate insights on AI Engineering.
Four different techniques, four different problems they solve, one client conversation that conflates all of them every week. Here's how we decide which knob to turn.
Frontier models are the default reach for every new feature. They shouldn't be. We moved three production workloads off frontier APIs to smaller domain-tuned models and the numbers were better than we expected.
Prompt engineering was the right framing when the prompt was the whole input. It isn't anymore. Here's how we think about context as a budget and what changed in our workflow.
What we learned wiring up the Model Context Protocol across three enterprise multi-agent pilots - the orchestration patterns that held up in production and the ones that quietly fell apart.
When an autonomous agent acts on production data, the question "who did this?" needs a real answer. Here's how we modelled agent identity, scoped permissions and audit trails for an enterprise rollout.
Generic RAG works fine on Wikipedia. It falls apart on regulatory filings, footnoted financial statements and tables that don't fit on one page. Here's the pipeline we built when the off-the-shelf approach hit the wall.