Insights
What we actually learned shipping migrations, lakehouses, model lifecycles and agent systems into production — including the parts that went badly. No gated PDFs, no vendor talking points, no AI-generated filler.
LangChain will get you a working agent on your data in an afternoon. The question is whether you can still change it in half a year. Here is where we draw the line.
Read itThe platform now covers tools, retrieval, serving, tracing and evaluation. It does not cover the three things that decide whether your agent survives contact with production.
Read itEvery agent you add multiplies latency, cost and the number of ways the system can be confidently wrong. Here is the test we apply before adding a second one.
Read itMost enterprise ML teams have tracking and think they have a lifecycle. The gap shows up the first time someone asks which model is in production and who approved it.
Read itStart here
Bring your current architecture, data volumes and the workloads that hurt. You leave with a target-state diagram on Databricks, the three changes that would cut the most cost or latency, and an honest answer on whether you need us at all.
No slide deck. No procurement process. One senior architect on the call.