Role: Principal Systems Architect
Status: Production / Legacy (2023-Present)
Focus: Agentic Skill Packs, XML-Gated Logic, and Process Compression.
Impact: Generated $5M+ in recurring value by collapsing manual operational pipelines into 60-second autonomous loops.
This repository documents the "Bulletproof Skill Packs" developed to operationalize Large Language Models (LLMs) for commercial scalability. Unlike standard "prompt engineering," which relies on stochastic luck, these architectures utilize XML-based logic gates, stateful execution, and Gold Data validation to treat natural language as executable code.
- Phase 1 (Observe): Decompose legacy "human-in-the-loop" workflows into discrete technical requirements.
- Phase 2 (Orient): Architect XML-gated agentic frameworks to eliminate hallucination and enforce business logic constraints.
- Phase 3 (Act): Deploy Self-Sufficient Systems that move operators from manual dependency to "Autopilot."
The Friction: Commercial product creation was bottlenecked by manual drafting and stochastic drift ("hallucinations"), requiring extensive human oversight.
The Architecture: A "Prompt-as-Code" framework that enforces strict brand guidelines and structural integrity.
- Mechanism: Multi-shot prompting with XML delimiters to define state boundaries.
- Validation: Outputs are rigorously tested against Gold Data sets to ensure 99% accuracy before human review.
- Result: Reduced production time from days to minutes (Process Compression), enabling single-operator scalability.
The Architecture: A "Prompt-as-Code" pipeline that encapsulates persona, tone, and strict DOM (Document Object Model) constraints within a single execution environment.
- XML Encapsulation: Utilizes
<TaskDefinition>and<ContextAndData>tags to create pseudo-namespaces, preventing logic bleed between creative and structural instructions. - Stateful Iteration: Implements a "Wait for Next" protocol, forcing the model to hold state (Outline → Draft → Review) in memory before committing to the next phase.
- Schema Enforcement: Compels the model to output raw HTML (
h1,div,li) rather than markdown, allowing for direct compilation into production-ready formats (.docx,.epub).
Commercial Artifact:
- Product: The ABCs of Raising a Puppy (Commercial Lead Magnet)
- Performance: 100% Sell-Through Rate; Reduced Time-to-Market by 95% (Weeks → Hours).
The Problem: High-volume content generation often suffers from "drift," losing brand voice or SEO intent over time. Standard chatbots lack the rigor for enterprise compliance.
The Architecture: A Human-in-the-Loop (HIL) Orchestrator designed for the NewsFLASH and SocialBLITZ commercial SaaS products.
- Chain-of-Thought (CoT) Injection: Embedded reasoning steps within the system prompt force the agent to validate keyword density and tone before generating text.
- Logic Gates: Implements strict
<CLARITY>and[WAIT FOR USER APPROVAL]checkpoints. The system pauses execution at critical failure points (Analysis, Outlining, Drafting) to ensure off-nominal behavior is caught immediately. - Context Injection: dynamically references static knowledge bases (
.txtrule sets, Hemingway Rules) to ground probabilistic outputs in deterministic best practices.
Commercial Artifact:
- Product: NewsFLASH & SocialBLITZ (SaaS Subscriptions)
- Scale: Deployed to 400+ active users; consistently maintained >4.8/5.0 satisfaction ratings over 12 months.
The Problem: Video content scaling is limited by manual rendering time. "Guru" solutions rely on expensive software, ignoring low-code integration possibilities.
The Architecture: A Self-Correcting ETL (Extract, Transform, Load) Pipeline that bridges the gap between text generation and visual rendering engines.
- Quality Assurance (QA) Loops: The generative prompt includes a recursive
<REVIEW>tag, forcing the LLM to critique and score its own output (1-10 scale) against specific criteria. Data is only serialized if it meets a "9/10" threshold. - CSV Middleware: outputs structured data compatible with Canva's Bulk Create API, automating the rendering of 100+ unique video assets in a single batch operation.
- Zero-Cost Infrastructure: Architected entirely on "Free Tier" tools (ChatGPT, Google Sheets, Canva), demonstrating enterprise-grade automation without enterprise-grade overhead.
Commercial Artifact:
- Metric: Production rate increased to 100 videos/hour (vs. 1 video/hour manual).
- Impact: Methodology published as an open-source guide, adopted by thousands of users for rapid social scaling.
This repository operates on the principle of Deterministic AI:
- Context is Code: Prompts are structured with the same rigor as software classes.
- Trust but Verify: Every automated step includes a validation gate (HIL or Self-Correction).
- Ship the Machine: The value isn't the content; it's the pipeline that produces it.
This portfolio represents a transition from "using tools" to "architecting systems." For inquiries regarding specific implementations or consulting, please contact via LinkedIn.