What I'm working on outside of my day job — professional websites, AI workflow systems, and other experiments worth showing.
✦ Side Project
Professional Resume and Custom SMB Websites
Outside of my day job, I build professional resume and portfolio websites for clients using the same AI-coordinated workflow behind this site. It started as an experiment to see how far I could push the agentic workflow — and it turns out it produces a genuinely polished result faster than most agencies would.
Content researched and written from resume and LinkedIn
Custom design, color scheme, and branding
Deployed to client's own domain or delivered as a standalone package
I built a simple AI assistant system to help with the kind of work that tends to pile up: research, writing, coordination, and follow-through.
Starting from scratch
At first, I used AI the same way most people do: as a chatbot. I'd ask a question, get an answer, and move on. That was useful, but it still kept me in the loop for every next step.
What changed for me was realizing AI could be set up to handle parts of the workflow itself. Not just answering questions, but actually doing scoped tasks: researching something, drafting a summary, reviewing output, or updating a page.
That shifted AI from something I consulted to something I could actually work with.
Chatbot vs. assistant workflow
Chatbot: "How should I update my website?"
Assistant workflow: "Update this page with the new content, check for obvious issues, and tell me what changed."
The difference wasn't just better answers. It was moving from conversation to execution.
How I use it
One assistant handles research and source gathering
One helps with website updates and content changes
One reviews work before anything goes live
Giving each assistant a defined role keeps the process clearer and more reliable
What changed over time
At first, I mostly used AI for prompting and quick answers
Then I started experimenting with systems that could take action, not just respond
Over time, those experiments turned into workflows that could complete real tasks end to end
Eventually, I was coordinating multiple assistants with different roles — more like managing a process than using a single tool
What actually changed
The biggest shift was that AI stopped being something I used only for ideas and started becoming part of the actual workflow.
That meant some tasks could keep moving without constant hand-holding. Research got gathered before I sat down to review it. Drafts got written before I faced a blank page. Routine tasks became easier to hand off without losing visibility.
Work could keep moving while I focused on something else
Repetitive tasks took less time and less attention
Reviews became more consistent because each assistant had a defined role
I could take on more without trying to do every step myself
What came out of it
Better consistency across research, writing, and review
Faster turnaround on projects with lots of moving parts
Less time spent on repetitive coordination work
A setup that could grow as the work became more complex
This website itself was designed, written, and deployed through that assistant workflow
Team Organization Model
AI assistant structure with specialized roles and clear accountability
Nate Burgess
CEO & Principal
Iggy
Chief Operating Officer
Thoth
Research Director
Iris
Content Strategy
Anansi
Digital Operations
George
Business Analyst
Janus
Site Reliability
Argus
QA & Risk
Reporting line
Collaboration
In practice
This approach is already proving its value. It enables unusually fast execution and has been used to support real client engagements, including resume-website builds delivered through an AI-coordinated production process.
