DISCIPLINE / ARCHITECTURAL BLUEPRINTSSYSTEMS INTEGRITY

AI SOLUTIONARCHITECTURE.

Demos thrive on chaotic prompts. Production demands deterministic architecture. I design modular, schema-validated AI systems with strict guardrails, predictable state machines, and transparent human-in-the-loop escalation paths.

ENGINEERING RIGOR

Why Prompt Engineering Is Not Architecture

Relying on a 5,000-token prompt to enforce business rules inevitably produces hallucinations, inconsistent formatting, and security vulnerabilities. Robust AI architecture decomposes workflows into stateful Directed Acyclic Graphs (DAGs) where each node executes a bounded micro-decision with verified schema outputs.

Architectural Pillars for Production AI

Schema-Validated I/O:Every tool call and LLM output is strictly validated against Pydantic / JSON schemas before execution.

Deterministic Fallback States:When confidence scores drop below calibrated thresholds, calls and tasks safely fall back to pre-defined rules or human reps.

Direct Native Integration:Avoid detached third-party dashboards. Systems read from and write directly to your core operational stack (HubSpot, PostgreSQL, Slack).

REPRESENTATIVE BLUEPRINTSView Case Studies

STATEFUL MULTI-AGENT DAG

LangGraph Research & Scoring Engine

Coordinated asynchronous research, web scraping, and ICP qualification agents. Outputs pass through strict Pydantic parsers before triggering automated CRM sequence updates.

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REALTIME SPEECH PIPELINE

Sub-2s Latency Voice Telephony

Engineered WebSocket streaming voice pipelines combining speech-to-text, LLM intent recognition, conversational voice synthesis, and dynamic calendar booking with sub-2s conversational turn latency.

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