ValueTempo

Blog

March 2026

Why AI Pricing Requires Three Layers: Architecture, Observability, and Trust

A Clay case study - AI pricing works when buyers can predict value, usage, and cost before committing. This article analyzes Clay's new pricing architecture using the AVS Trust Rubric and shows why Clay's pricing architecture improved, but AVS Trust score dropped from 81% to 75%.

March 2026

What I Learned Vibecoding an AI Startup Tool using Lovable + Claude Code

A build-in-public note on what broke, what worked, and what vibecoding an AI product taught me about reliability, production readiness, and trust infrastructure.

February 2026

Trust is the new growth constraint in AI

A practical way to make value, usage, and cost feel predictable — why pricing drift becomes trust drift, and how AVS gives operators a shared map.