> forward_deployed
Cost Optimization
In forward deployed work the infrastructure bill lands on the customer's cloud account, which means cost is a product feature they can read line by line. I engineer for that bill explicitly.
> what this looks like in practice
▸Compute sizing adapted per tenant cloud on the AI-Infused QE Platform: the same Kubernetes-orchestrated deployment scales its footprint to each customer's workload instead of shipping one oversized default.
▸Per-tenant cost telemetry in the FinOps layer, so every tenant sees their own spend, split between infrastructure and LLM usage, and can hold the platform accountable.
▸Token and model-routing economics (see Token Optimization) treated as first-class cost levers alongside infrastructure.
▸Frugality as an architecture constraint in my independent builds: WealthOS is sized for free-tier deployment today with documented seams for horizontal scale, and Loop Copilot runs its full stack on Railway with CI/CD.
> where it shows up
The AI-Infused QE Platform (customer-visible FinOps across AWS, Azure, and GCP), WealthOS, and Loop Copilot.