Chris Fornesa

Technical Forward

As we move deeper into the era of Generative AI, the value of a technologist has shifted from the manual labor of writing syntax to the Systems Thinking required to govern logic. My approach to development is rooted in the belief that an AI is only as effective as the architectural guardrails surrounding it.

My work focuses on the GAIL (Governed Artificial Intelligence Logic) protocol. This framework treats AI as a "Collaborative Engine" that requires three specific architectural pillars:

1. Deterministic Guardrails: Using staccato-phonetic constraints, 3-syllable word-ceilings, and low-temperature inference (T=0.1) to ensure structural veracity. This minimizes "tokenization hallucinations" common in complex linguistic tasks.

2. Sovereign Systems & Scaffolding: Implementing localized PII redaction to ensure data sovereignty, while architecting agents as "Thinking Partners." In alignment with current pedagogical research, these tools prioritize "productive struggle" and active learning over simple automation.

3. Cross-Disciplinary Integration: Bridging the gap between complex cultural traditions—like the Tagalog Tanaga—and the mathematical limitations of modern tokenization.

I do not simply "use" AI; I architect the environments in which AI can function with institutional-grade integrity. By combining my background in Data Architecture at Chevron with current graduate research in Political Behavior and Linguistics, I build systems that prioritize meaning over mechanics and privacy over convenience.

The Dual-Tier Framework

Thinking Partner vs. Productivity Accelerator

In alignment with recent research from the Harvard Gazette regarding the pedagogical shift in AI, my work distinguishes between two distinct categories of synthetic interaction. I do not architect "one-size-fits-all" bots; I design specialized systems based on the intended cognitive or operational outcome.

• Tier I: Productivity Accelerators Focus: Efficiency, Administrative Accuracy, and Data Hygiene. These agents—such as the Resume Editor and Sentiment Preprocessing Pipeline—are designed for high-concurrency tasks that aim to remove "friction." By automating clerical labor and data cleaning, they free the human user to focus on high-level strategy and interpretation.

• Tier II: Cognitive Scaffolding (The "Thinking Partner") Focus: Inquiry, Active Learning, and "Productive Struggle." Agents like the Poetic Agent and Political Behavior Analyst act as "Tutorial Bots." They do not merely provide a finished product; they provide a structural framework (such as Prosodic Meter or Moral Foundations Theory) that requires the user’s active participation. These systems facilitate more profound meaning-making, ensuring that AI serves as a "scaffolding" for human intelligence rather than a replacement for it.

My Philosophy: Algorithmic Advocacy

My work is centered on the concept of Algorithmic Advocacy. In an era of probabilistic AI, I believe agents should be more than just "chatbots"—they should be reliable frameworks that uphold the user's research integrity and data sovereignty.

Whether I am engineering a Search-Path Protocol to prevent link hallucinations or applying Moral Foundations Theory to neutralize political bias, my goal is to build systems where human expertise and machine intelligence are in a state of verified "handshake."

The Multi-Purpose Stack

UX & Product Design | Prioritizing user sovereignty through dynamic search paths and responsive, intent-driven interfaces.

AI Systems Engineering | Orchestrating multi-agent systems and API lifecycles (FastAPI) with a focus on asynchronous performance.

Data Science & Security | Implementing rigorous methodology (MFT, NLP Valence) and local PII sanitization to ensure output reliability.

Intellectual Lineage

My approach is the product of three distinct yet intersecting professional and academic paths. I leverage the technical rigor of Data Science, the behavioral frameworks of Political Psychology, and the enterprise scale of Global IT.

1. My Ethical Perspective

The rise of AI has posed several existential questions surrounding the value of our human existence and what we're willing to sacrifice for technological and societal progress. As the debate over AI ethics evolves, I stand by my belief that AI can be used ethically with proper safeguards in place. Thus, my AI projects revolve around AI as a form of human empowerment, rather than as a dangerous threat to humanity. Similarly, my data science projects aim to ask how we, as humans, can come together to fight back against encroaching algorithmic polarization.

2. Ethical AI Usage

Societal, economic, and environmental concerns have plagued American AI companies. Thus, I have opted to prioritize using non-American AI companies, such as Mistral AI, in performing the logic of these agents. This decision is not only more cost-effective but also underscores the need for more thoughtful prompt engineering and the handling of user data. However, I know I cannot expect myself to fully divest from American AI companies or big tech as a whole (especially given my use of Google Gemini to create these projects). Still, I want to take this step to raise awareness that American AI companies can, in fact, advance the field without high costs to American workers, the environment, and the economy. Big tech does not need to displace the American worker or engage in (and support) human rights abuses in Palestine, Sudan, and the Democratic Republic of the Congo.

3. The Enterprise Foundation

During my tenure at Chevron, I specialized in translating complex technical telemetry into actionable executive insights. Managing enterprise mobility data at scale taught me that Systems Integrity and IT Governance are the true backbones of any successful system. This mindset is why my portfolio utilizes a "Sovereign Stack"—ensuring every agent operates with secure API lifecycles and local PII redaction.

4. The Behavioral Framework

My upcoming graduate research at Arizona State University will focus on how deep-seated psychological drivers influence modern conflict. I don't treat AI as a "black box" that magically solves problems. Instead, I treat it as a tool for Algorithmic Auditing to empower human creativity. My agents use frameworks such as Moral Foundations Theory (MFT) to move beyond surface-level rhetoric and identify the deep-seated psychological drivers of intergroup friction.

5. The Computational & Creative Core

With an MS in Data Science from Boston University and a background in Studio Art, I bring technical rigor to linguistic and creative problems. This bimodal lens allows me to engineer strict constraints, such as Language-Logic Anchoring for poetry and Valence-Arousal NLP for sentiment tracking. This ensures that AI remains grounded in technical accuracy while prioritizing creativity and cultural authenticity.

My AI System Standards

Every AI project in this portfolio adheres to a strict Production Standard:

1. Redaction First: All inputs are scrubbed of PII via local Regex before reaching any LLM.

2. Theoretical Grounding: No agent is "raw"; every output is filtered through a proven framework (STAR, MFT, or Prosody).

3. Search Sovereignty: I never provide static links. I provide the tools for the user to verify the source themselves via the Search-Path Protocol.

This is to ensure that user information is not unethically used by the LLM in any project, which is central to my mission to offer ethical, helpful AI solutions that empower humans, not replace them.

Technical Proficiencies & Tooling

A comprehensive look at the technologies and frameworks powering my multidisciplinary suite.

• Data Science & Analytics | Python (Pandas, NumPy, Scikit-learn)

• AI & Systems Engineering | FastAPI

• Natural Language Processing | NLTK

• Research & Methodology | Quantitative Research Design

• Web & Product Design | HTML5, CSS, and JavaScript

My technical stack is not a static list of tools; it is a dynamic ecosystem designed to support Ethical AI Development. I specialize in selecting the most cost-effective, environmentally conscious, and logically sound models to solve complex social and creative problems.

Call To Action

Open for Collaboration - I am seeking opportunities where multidisciplinary thinking meets high-level AI implementation.

Resume | LinkedIn | GitHub

Copyright & AI

Note on Authorship: These agents are designed as collaborative scaffolding. Per global IP standards (U.S., UK, China), I advocate a "Human-in-the-Loop" approach in which AI provides the structure, while the user provides transformative authorship.