Advising enterprise leadership and engineering teams on multi-agent orchestration, LLM FinOps token optimization, and deterministic governance. Proven production delivery across AWS, Google Cloud, DoiT, and PayPal.
Architectural Leadership & Delivery Across Leading Cloud & AI Ecosystems
Helping engineering teams avoid the common traps of moving LLMs from prototype to production
Unoptimized LLM architectures hemorrhage budget when scaling from 100 to 100,000 requests per day.
Monolithic system prompts fail unpredictably under production edge cases, causing silent hallucination loops.
Direct user-to-LLM interfaces risk exposing proprietary enterprise context and falling prey to adversarial prompts.
Reference architecture for reusable agent factory extending GenAI accelerator playbooks with governance-by-default.
Production governance framework for foundation models, agents, and multi-model workloads with compliance controls.
Helping enterprise organizations design, evaluate, and scale cost-optimized intelligence
Production systems design mapping business requirements into specialized multi-agent graphs, multi-modal frameworks, and reliable RAG pipelines.
Infrastructure audits for token overhead. Implementing cost-based model routing, prompt caching, and cost-efficient tier-2 models to curtail spend.
Production evaluation loops, automated guardrails, PII scrubbing, and vulnerability protections to meet enterprise compliance and auditability.
Tailored corporate workshops, architectural walkthroughs, and hands-on GenAI labs delivered by an O'Reilly and Udacity caliber instructor.
How enterprise engineering teams can reduce model inference costs by up to 75% using hierarchical model routing, semantic prompt caching, and cost allocation telemetry.
Deconstructing why single-prompt LLMs fail in production and how state machine graphs with structured validation barriers guarantee predictable agent output.
A pragmatic guide to implementing agent identity, least-privilege tool execution via Cedar policies, and automated PII sanitization in multi-tenant environments.
See projected savings using model routing, prompt caching, and architecture tiering