AI Builder Portfolio

Public proof package for Ross Stretch's AI Builder work.

This repository exists as a professional portfolio hub for practical AI systems, agentic workflow design, evaluation planning, crawler/search intelligence, brand-audit tooling, and human-in-the-loop product thinking.

Live prototype portfolio: https://dev.ross-stretch.com/prototype-portfolio GitHub profile: https://github.com/ross-stretch

Portfolio Thesis

I build AI-assisted systems around real workflows, not novelty demos.

The work represented here focuses on:

• turning messy business processes into structured inputs and outputs;
• using AI as leverage inside reviewable systems;
• separating evidence gathering from recommendation generation;
• designing human approval boundaries before adding autonomy;
• evaluating outputs before trusting them in production workflows;
• documenting assumptions, risks, and next steps.

Public Proof Repositories

Repository	Purpose
agency-ops-agent	Agentic intake and operations workflow prototype
stretchbas-lite	AI-assisted brand audit and business-positioning prototype
stretchsearch-lite	Crawler/search/SEO intelligence and evidence-extraction prototype
ai-evaluation-harness	AI output scoring, rubric, review, and governance prototype
ai-builder-portfolio	Portfolio hub tying the public proof layer together

What This Demonstrates

This portfolio is designed to show how I think and build with AI:

1. Problem framing — define the business workflow before choosing the model.
2. Structured inputs — collect usable context, constraints, and evidence.
3. System architecture — separate intake, analysis, generation, review, and delivery.
4. Human review — keep approvals explicit where business risk exists.
5. Evaluation — compare AI outputs against rubrics and regression checks.
6. Documentation — leave enough context for another builder or reviewer to understand the system.

Current Status

This is an early public proof layer. The repositories are intentionally lightweight and documentation-first while the deeper implementation work remains in private/product lanes.

The public layer communicates direction, architecture, product judgment, and build discipline without exposing private infrastructure, client material, credentials, or proprietary internal code.

Primary Build Areas

• Agentic workflows
• Business process automation
• AI-assisted analysis
• Evaluation and governance
• Crawler/search intelligence
• Brand and SEO intelligence
• Human-in-the-loop systems
• Internal tool and dashboard concepts
• Prototype-to-production planning

Technical Direction

Expected implementation stack across the proof layer:

• Python for crawlers, extraction, scoring, and evaluation utilities
• TypeScript / Next.js for review interfaces and product surfaces
• Structured JSON outputs and schemas for repeatability
• Dockerized runtime patterns for reproducible deployment
• GitHub-based documentation, review, and version control

Review Boundary

These projects are not presented as finished SaaS products. They are public proof artifacts showing product architecture, workflow design, AI-system thinking, and the path toward implementation.

Related Links

• Prototype Portfolio: https://dev.ross-stretch.com/prototype-portfolio
• GitHub Profile: https://github.com/ross-stretch
• Main portfolio site: https://dev.ross-stretch.com