PM LLM Routing
(2026 Edition)
PM LLM routing is the practice of directing each request to the cheapest model that still meets quality and latency bars — tiering by complexity, routing by latency budget, routing sensitive tasks to vetted models, spreading load across vendors, and caching before routing. Done well, it cuts model spend 30–60% without a quality hit.
By Naman Goyal · Product manager · Builder of PM Streak · Updated July 3, 2026
5 routing strategies and 4 pitfalls.
Build Routing PM Skills — Free →5 Strategies
Tier by complexity — small/medium/large model per task
Route by latency budget — fast models for inline, slow for async
Route by safety — sensitive tasks to vetted models
Use multiple vendors for resilience
Cache aggressively before routing
4 Pitfalls
Routing based on cost alone — quality regressions show up later
No A/B testing of routing decisions
Routing logic that's a black box no one understands
Vendor lock-in through tightly-coupled tooling
FAQ
Is model routing worth the engineering complexity?
For products with material AI cost, yes. Routing typically saves 30–60% on model spend without quality regression. The engineering investment pays back fast at scale. For small or experimental products, default to one good model and optimise later.
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