Breaking the prompt bottleneck - an LLM harness for reusable context

Breaking the prompt bottleneck - an LLM harness for reusable context targets a $9.6B = 160,000 AI product teams x $60,000 ACV. Buyer definition: product or platform engineering teams at mid-market and enterprise companies that embed LLM features and need centralized orchestration, context management, and observability. ACV rationale: platform subscriptions, onboarding, integrations, and support at enterprise pricing. total addressable market with medium saturation and a year-over-year growth rate of 30-50% year-over-year growth in LLM tooling and orchestration adoption driven by enterprise pilots moving to production.

Key trends driving demand: RAG and vector DBs maturity -- more teams are using retrieval augmented generation which requires robust context pipelines and makes a harness valuable.; Function calling and structured outputs -- deterministic LLM integrations lower error rates in chained flows and enable orchestration layers to automate state transitions.; Platformization of AI features -- teams prefer a single orchestration layer rather than point solutions for prompts, embeddings, and logging.; Cost sensitivity and token efficiency -- as call volumes rise, tooling that reduces repeated prompting and token waste has a direct ROI..