Consulting essays on two-model routing, observability beyond tokens, batch vs. streaming, actionable cost postmortems, and versioning prompts/policies/models together.
The discipline that decides whether AI survives production
Most AI programs are won or lost after the demo. A model that dazzles in a notebook can quietly drain a P&L or erode trust once it meets real traffic, real latency budgets, and real invoices. MLOps, observability, and cost engineering are the unglamorous disciplines that keep that from happening, and they are where consulting-grade judgment earns its keep, because the defaults are rarely the right answer.
This collection gathers the Stratenity Advisory Team's field-tested patterns for running AI in production economically and reliably. Read together, they answer one question: how do you keep a system fast, observable, and affordable without freezing the ability to ship?
Cost is a design decision, not a line item
Teams tend to discover their AI bill the way they discover a leak, usually after the damage. The fix is architectural: route cheap-first and escalate to a stronger model only when a request warrants it, cache aggressively at the semantic layer, and batch what does not need to be real-time. A two-model routing pattern alone routinely halves inference spend while raising reliability, because the expensive model is reserved for the cases that need it.
Observability beyond tokens
Token counts tell you what you spent, not whether the system is healthy. The metrics that predict incidents are answerability, latency-budget adherence, and drift in output quality over time. Instrument those and a cost postmortem stops being a spreadsheet argument and becomes a concrete list of routing, caching, and prompt fixes.
Version the whole set, not the parts
Prompts, policies, and models fail as a system, so they must ship as a set. Versioning them together, and rolling forward as a unit, is what lets a team move fast without the silent regressions that come from changing one component and hoping the other two still agree.
In this collection
Field notes from the Stratenity Advisory Team. Open any title to read the full essay.
Cheap first, smart second, route only when needed.
Answerability, latency budget, and drift, not just spend.
When nightly jobs beat real-time (and vice versa).
From “too expensive” to concrete routing/caching fixes.
Ship sets, not parts; roll forward safely.
Go deeper with Stratenity frameworks
These essays are the public taste. The full library holds the worked POVs, execution levers, and interactive diagnostics consulting teams use to put these patterns into production.
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