I co-founded Planning Period because I wanted teachers to design
curriculum that truly connects with their students. As Head of
Product, I lived between pedagogy and engineering. I led more than 70
sprints across three full versions, and turned messy, curriculum
documents and state standards into something an AI could help with
without losing the human intent behind each lesson.
On the technical side, I designed our prompting system from the
ground up and built a QA process for AI outputs in Python and Jupyter
using the OpenAI API. I spent long stretches leveraging any library
and toolset I could find to clean and map large sets of curricular
content and standards so the system could respond with precision and
consistency. I also co-designed and tested our PDF processing pipeline
using the Mistral OCR API, to pull reliable structure from the
documents teachers actually use. The point of all that engineering was
simple: give educators responses they can trust, and space to craft
lessons that feel personal and culturally grounded.
I was also the face of the business. I secured institutional
partnerships, onboarded educators, ran workshops, and folded what I
heard back into the roadmap. I carried the backlog, wrote the epics,
made the tradeoffs, and kept our small two-person team shipping.
Building Planning Period is why I committed to becoming a full stack
developer. Once the problem was meaningful enough, the learning took
care of itself.
I built my personal website as part of my Fullstack Academy Web
Developer Certification course. Though the assignment asked for a pull
request submission. I wanted it to live in the world. I bought a
domain, configured DNS, and deployed on Vercel so the site worked like
a real product from day one. Version 1 is intentionally simple. I
focused on clear structure, readable typography, and a content flow
that feels original to me and my story.
I wrote semantic HTML5 so screen readers can navigate the page, kept
the head clean with sensible meta tags, and organized sections so the
story is easy to follow. I styled with vanilla CSS, paying attention
to spacing, type scale, and responsive rules so the layout holds up on
phones and large screens. Accessibility mattered throughout. I used
descriptive alt text, labels, and keyboard-friendly navigation so the
site welcomes more people. I treated the repo like a professional
project. I created a clean structure, committed in small, descriptive
increments, and worked through the pull request workflow to satisfy
the course requirement. I then set up a Vercel project, connected it
to the main branch, and confirmed that preview builds and production
deploys were predictable. I connected the custom domain, verified DNS
and SSL, and added the little touches that make a site feel finished.
This is only version 1. In versions 2 and 3 I plan to adopt Tailwind
to establish a tighter design system and use JavaScript to make the
site interactive. I want details that respond to the reader without
getting in the way. That includes stateful components, smoother
navigation, and motion that supports meaning. The goal is to keep it
personal and honest while leveling up the craft.
Building this site taught and reinforced the skills I care about. HTML
and CSS fundamentals. Responsive design. Accessibility from the start.
Version control discipline, and bringing your project to live in the
real world after some well intentioned hard work. It is a small site,
but it reflects how I like to build: start with clarity, ship, learn,
and then raise the bar in the next version.
I am building anyChangeAi to answer a simple question. Can I make it
easy to change any document with AI while staying honest about what
the tech can and cannot do. I will start from a clean Next.js and
TypeScript base so I can move fast and still keep the code readable
and testable. The repository lives on GitHub with a project charter
and an issue board so the work stays visible and traceable from day
one.
A core learning goal for me with this project is to understand the
limits of AI driven development, especially vibe coding. I want to see
where AI helps me explore ideas and where it slips into guesswork. I
will document those edges clearly, treat AI as a collaborator, and use
tests and acceptance criteria to keep me grounded. I also want to find
the right balance between fast prototyping and disciplined
engineering. I will prototype quickly in small, reversible steps, then
dive into what works by writing it down as GitHub issues and shipping
behind clear commits. I will create and follow a self led project
charter and implement it through labeled, milestone linked issues so
anyone can see what I am doing, why it matters, and what is next.
Process matters for this project. I want to follow a proven fullstack
path using tools that are most common in the industry. Next.js with
React and TypeScript for the app. Tailwind for a consistent design
system. Vercel for hosting. GitHub for source control, issues, and CI.
If the product needs persistence, I will add a relational database
with and keep schema changes versioned.
In order to maximize my learning from this project I built a custom
GitHub Copilot agent called Bootcamp Tutor. Its job is to act like a
coach who helps me understand the technology and methods behind each
issue and then directs me on completing the work myself. It will
reference the charter, link relevant docs, ask clarifying questions,
and suggest next steps. The goal is learning through practice, not
outsourcing the solution the way agent mode often does.
When I ship the first version, the readme will show what the product
can do, the tradeoffs I made, and the places where AI accelerates me
versus the places where I need to slow down and think. The end goal is
not a perfect demo. It is a trustworthy tool that teaches me how to
build with AI without giving up my judgment.