Onboarding

Hi, I’m Taylor Waldon.

// package
name: Taylor-waldon
version: vNext
type: product-leader
status: production_ready
pipeline: awaiting_next_build → 2025.1 (deployed_to_team)
seeking_env: stable_repo_with_growth_mindset

 Quick Start Guide

Welcome to Taylor vNext — this website is development deployment (or employment) documentation for me, Taylor Waldon, as a living software system.

The metaphor’s meant to make you think — but don’t worry if it feels like too much at first. Here’s the fastest way to get your bearings:

Read the Docs	Everything you need to get oriented with this website is in the user documentation section.
Understand the README	My README is the foundational guide to how I work. It’s my values, principles, work style, and company fit information.
Explore the Branches	There are two main showcase pages that house a collection of projects (called “artifacts”). Each has a unique central theme. Legacy = LearnDash Product Owner Role Experimental = AI Workflow Optimizations
Check the Human API	If you want to know more about me and my skills in depth, the API page is the place to do it.
Book a Demo	Contact me to get to know more about how I might fit into your organization.

Version History

vGiveWP → vStellarWP → vLearnDash → (vNext)

Roadmap

 What is the roadmap in this context?

What you’re seeing here is my personal version-history: where I’ve been, what I’ve shipped, and the next build in progress. Think of this as the “changelog” for Taylor my work history.

April 2024 – Nov 2025
vLearnDash.legacy
Product Owner — led strategy built from customer voices and collaboration.

// release
name: vLearnDash.legacy
role: product_owner
period: 2024-04 → 2025-11
focus: team_alignment, platform_stability, internal_ai_enablement
commits:
  - reporting_refactor: 93% faster; 87.5% less_memory
  - customer_signals_alignment: refunds -42%; support_volume -30% YoY
  - ai_ops_workflows: ~+50% personal_efficiency
  - cross_functional_ai_adoption: training + custom_gpt_tools
status: archived

 LearnDash Product Owner Highlights

This chapter was about transformation through constraint.

• I stabilized the product’s core systems and rebuilt the reporting engine, cutting query times by 93 % and memory use by 87.5 %.
• I reconnected the roadmap to real customer needs, which drove refunds down 42 % and reduced support volume by 30 % year-over-year.
• I designed AI-assisted workflows that automated triage and communication, reclaiming half my workweek for higher-impact thinking.
• I trained cross-functional teams on new AI tools and workflows, building confidence and alignment across departments.

Summary: this was where I learned to rebuild from the inside out — turning technical debt, team fatigue, and scattered priorities into momentum and clarity.

Public Release
vNext.2025.0
Product Leader — ready for a new challenge.

// release
name: vNext.2025.x
role: technical_product_manager
state: public_release
focus: clarity_context, scalable_systems
outcome: platform_ready_for_deployment

 What makes me a great hire?

This version marks a turning point — the moment I stopped describing what I do and started showing it.

• I built the Human API, my framework for how I work: connecting empathy with execution, people with process.
• I rebuilt my portfolio as a living product — a transparent, documented record of how I build, lead, and ship.
• I laid the foundation for agentic systems, exploring how AI can amplify human creativity instead of replacing it.
• I refined how I scale collaboration — through clarity, trust, and communication that actually works.

Summary: this phase isn’t just about readiness — it’s proof of evolution, and an open invitation to build what’s next together.

In Development
vNext.deployment
Current build — exploring new product ecosystem.

// release
name: vNext.deployment
state: in_development
goal: deployed_to_team (full_time_role)
focus: new_product_ecosystems, ai_enablement_at_scale
pipeline: candidate_environments → interview → merge_to_main
result: new version TBD

 How will I onboard in my next full time role?

This next build is all about deployment — finding the right environment where everything I’ve built can run at full capacity.

• I’m refining systems for AI-enabled product strategy and building playbooks that help teams move faster with context, not chaos.
• I’m developing Human API documentation for how I onboard, lead, and collaborate — so my process scales as soon as I join.
• I’m exploring ways to make AI-assisted product work transparent, trustworthy, and genuinely helpful for every contributor.

Summary: the next release will ship when the right team is ready — one that values curiosity, clarity, and the kind of progress that stays human.

Commit Messages

Here’s what teammates committed to the branch had to say:

Explore Repositories

Two repositories — legacy deployment and experimental branch.

• Legacy Branch: How I guided LearnDash through one of its most transformative years.
• Experimental Branch: Experiments and systems that make AI more practical—and more human-in-the-loop.

// summary
feat: built human-in-the-loop AI operations framework in Cursor  

// functionality
- triages support tickets → checks completeness + dev readiness  
- synchronizes multi-tool workflows → (Jira, GitHub, Help Scout)  
- converts AI insights → real-time, human-verified actions  

// outcome
result: ~50% time-savings  
focus: judgement, empathy, innovation  

// summary
release: LearnDash 5.0  

feat: REST API refactor + Model Context Protocol (MCP) integration  

// purpose
creates: foundation for Agentic AI in LMS software  

impact: transformed technical debt → forward momentum  

// outcome
framework: enabled smarter releases with every iteration  

Environment