AI Strategy & Product Development

Generative AI & LLMs (NLP)

I leverage the full ecosystem of Large Language Models to accelerate product discovery and development. I am proficient in prompt engineering and model evaluation across:

  • Gemini, ChatGPT, and Claude: Utilizing these models for automated content generation, complex reasoning, and synthetic user research.

  • LLM Implementation: Understanding the nuances of model selection, context window management, and the trade-offs between proprietary and open-source models for enterprise scaling.

Hand holding a phone with ai application icons.
Hand holding a phone with ai application icons.
Multimodal & Agentic AI

I am actively exploring the transition from "Chat" to "Action" through:

  • Multimodal Integration: Building experiences that synthesize text, image, and data inputs to create more intuitive and human-centric interfaces.

  • Agentic AI (OpenClaw): Experimenting with autonomous agent frameworks like OpenClaw to build self-correcting workflows that can navigate complex tasks with minimal human intervention.

A person typing on a laptop on a table
A person typing on a laptop on a table
The "Vibe-Coding" Methodology

I built a full-on production SaaS application, Family Chores (www.chores.family). This project serves as my primary sandbox for "vibe-coding"—a development philosophy where I use AI as a collaborative partner to:

  • Move from a high-level concept to a functional MVP in weeks, not months.

  • Bridge the gap between Figma designs and production-ready code using AI-prompted logic.

  • Iterate on features in real-time based on user feedback, treating the AI as an infinitely scalable engineering team.

Computer Vision & Edge AI

My background includes involvement in Vision AI, where I have managed products that translate visual data into actionable insights across diverse industries:

  • Object Identification: Developing systems to identify specific objects and anomalies in the medical field (diagnostic assistance), agriculture (crop health and livestock monitoring), and sports (player tracking and performance analytics).

  • Edge AI: Implementing lightweight vision models on Edge devices to ensure low-latency, real-time processing in environments where cloud connectivity is limited or data privacy is paramount.

a computer processor with the letter a on top of it
a computer processor with the letter a on top of it
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