💸 Cost engineering is product engineering for AI

PM LLM Cost Management
(2026 Edition)

Keeping an AI product profitable takes five deliberate cost levers: caching repeated queries, routing simple requests to smaller models, compressing prompts, batching when latency allows, and negotiating enterprise pricing once volume is real. Healthy AI products target 60–70%+ gross margin, and cost engineering alone can add 10–30 points without hurting quality.

By Naman Goyal · Product manager · Builder of PM Streak · Updated July 3, 2026

5 cost levers and 4 pricing traps for AI product PMs.

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5 Cost Levers

1.

Cache aggressively — repeated queries shouldn't hit the model

2.

Route by complexity — small model for simple, big model for hard

3.

Compress prompts — fewer tokens = lower cost

4.

Batch when latency allows

5.

Negotiate enterprise pricing once volume is real

4 Pricing Traps

Flat-rate pricing on usage-heavy users

No fair-use cap on power users

Forgetting fine-tuning increases per-request cost

Over-using top-tier models for simple tasks

FAQ

What's a healthy gross margin for AI products in 2026?

Targeting 60–70%+ for SaaS-shaped AI products. Below 50% becomes hard to defend at scale. Cost engineering (caching, routing, prompt compression) typically adds 10–30 points of margin without quality regression. PMs who don't engage with cost end up with venture-funded but unprofitable products.

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