Real work, real results
No invented case studies, no placeholder logos. What follows is a look at the kind of work this becomes when the systems finally support the person running them.
Client builds
Global E-commerce Marketplace
What was built
Full infrastructure review, a custom analytics dashboard (Google Analytics + Shopify integration), user access management, and a checkout redesign. Embedded with the client's engineering team (Kanban, JIRA) to scope the IT roadmap — network upgrades, firmware rollouts, and feature launches that stuck.
Before
Client inquiries flooded in as unstructured emails — no triage, no tracking, no resolution path.
After
A custom support ticket process built from scratch. Analysis showed most inbound contact was education-seeking, not issue-reporting, so a targeted resource library was built around that.
Dozens of unstructured emails a week became 3–4 structured, resolved support tickets.
Reference: real project materials
Physician & Wellness Practice Owner
What was built
Started with education — demystifying VPNs and showing how AI automates instead of adding chaos. Built single-creator systems for batch content creation, secure templates for IP protection and legal compliance, and a router-level VPN deployment protecting every device on the network automatically.
Before
2–3 hours of patient file reconciliation every Friday afternoon, and a network she couldn't trust with client data.
After
Reconciliation takes minutes per week. A secure, private network that actively supports business development — what was a liability became infrastructure she can grow on.
2–3 hours of weekly manual reconciliation reduced to minutes.
Auto Rims & Detailing Shop
What was built
Migrated legacy hardware to cloud infrastructure, reformatted and optimized drives, set up secure user profiles and enterprise-grade security protocols, and rebuilt the workflow stack from scratch with documented processes and steps.
Before
The business couldn't execute basic operations without a former leader's access. Manual processes ate the team's time daily.
After
100% security access reclaimed, restructured, and secured. The team runs the business without daily troubleshooting fires.
100% security access reclaimed. 1–3 hours saved daily through workflow automation and documentation.
Reference: real project materials
Additional experience
A broader look at the scale and range of the work.
Live builds to explore
A case study tells you what happened. These you can check. Each one is live, and each one names the skill it took to build.
Accountability record
A trigger term I run across every AI tool I touch. It turns a bad session into a plain, itemized account: what the tool was marketed to do, what it had the capability to do, and what it did instead. Three real briefs are on the page for you to open.
What it shows
Working checklist
A real migration, written down as a routine. One domain moved off Squarespace, with DNS on DigitalOcean, hosting on Netlify, and email on Proton Mail. The site and the inbox both stayed live the whole way through. Five steps, in the order that keeps it calm.
What it shows
Searchable database
22 clothing brands made from natural fiber, with no polyester, nylon, or other synthetics. Every entry is verified against the brand's own materials page plus an independent source.
What it shows
Publishing system
The blog on this site runs on a weighted rotation across its pillars, with a drafts inbox for review and a scheduled date on every post. It started from 25 original drafts of my own writing, from my LinkedIn newsletter, which trained it to understand my voice. After more than a dozen rounds of voice edits, it has generated more than 50 posts that are live right now. They are built from my writing, resume, experiences and credentials, to create a consistent brand voice of credibility.
What it shows
My own infrastructure
Everything below is infrastructure designed, built, and run for The Baddie Stack itself — not a client engagement, my own operations. The fastest way to see how someone runs a program is to watch what they built when no one was billing them for it.
How these were built
I direct the model the way I would direct an engineering team. It gets a written job description, a knowledge base to work from, a line it cannot cross, and a review before anything ships. What comes out is a working system with files, logs, and results you can check. It is not a conversation with a model, and it is not a summary pulled out of one.
The skills underneath
File System Rescue
What was built
Discovered that the folder connected to the AI workflow for months was actually the desktop app's own internal data directory, not a project folder. Extracted, verified, and rehomed every file, then wrote the operating rules that prevent recurrence and synced them into four separate project files.
Before
Every new work session risked starting from zero, with no visibility into what had already been built or decided.
After
Every file recovered and verified, session recaps written so past work resumes instead of restarting, and one canonical rules document any project can now inherit.
2,250 files recovered across 19 sessions, every one MD5-verified byte-identical. Zero data loss.
Job-Search Operating System
What was built
A browser-driven application agent with its own job description and knowledge base, an ATS-style scoring script weighing keyword coverage and formatting, a resume generator, and a pipeline log recording every company pursued, every score, every gap, and every outcome.
Before
Job-search tracking that lived in memory and scattered browser tabs, with no consistent way to know what had been tried or why.
After
Every application scored before it goes out, every honest skill gap logged rather than smoothed over, and one file that answers what happened with any given company at a glance.
14 tailored resumes generated and scored, with honest fit scores ranging from 50 to 98 out of 100, logged even on the low ones.
Grant-Seeking Operating System
What was built
A grant-seeking system with a full knowledge base, a hard-filter eligibility matrix, a fit-scoring method, an explicit three-tier autonomy line for what the system can do alone versus what needs a human signature, and a documented discard list for every rejected opportunity.
Before
Funding opportunities found ad hoc, with no consistent way to screen fit before investing hours in an application.
After
Every opportunity screened against a fixed eligibility bar before any drafting starts, with reasons on record for every one discarded.
1 grant submitted (~$4,000 in credits), 1 drafted ($10,000), 1 staged ($10,000), from a discovery sweep of 14 opportunities.
Cross-Project Chief of Staff
What was built
A chief-of-staff system that reads across every other project: a priority framework, a live register of every project in motion, standing routines mirrored from a canonical operating-rules document, and an explicit sensitive-data boundary so it can report across projects without carrying clinical or legal detail out of them.
Before
Status and priority lived in whichever project was most recently top of mind, with no single place that saw across all of them at once.
After
One live task register and one set of standing routines applied consistently across every project, with a data-boundary rule designed in rather than bolted on after.
One system tracking priority and status across every other system in the account, with a written data-boundary rule protecting sensitive material.
Also running
AI-native & assisted
I have spent almost three years running AI tools, first on the enterprise side and now as a founder. The work was never the conversation with the model. It is what exists when the conversation ends: an agent in use, a system that got fixed, a page you can visit.
Skill 01
I write instructions the way I would write an operating document. Each one names the role, the scope, the source of truth, and what must never be touched. The test is simple: the tenth run has to come back as good as the first.
In practice
See it
Skill 02
An agent is not finished when it answers well once. It is finished when it has a job description, a knowledge base, and a written line between what it may do alone and what needs a human signature. Then it goes to work.
In practice
See it
Skill 03
When a build fails, I find the cause, fix it, and write the fix down as a standing rule so the same failure cannot come back. The record states what happened and what it cost. It does not argue about what the tool meant to do.
In practice
See it
Skill 04
The output is the thing itself. A page you can visit, a pipeline that runs on a schedule, a database you can search, a checklist you can follow. If all that exists at the end is a good chat, the work is not done.
In practice
See it
109 builds across 14 weeks, logged as they happened. The blocked and stopped work is left in.
Oct 22–28
7 builds this week, across Infrastructure.
What got built
Oct 15–21
7 builds this week, across Brand Content, Infrastructure, Offers.
What got built
Oct 8–14
13 builds this week, across Brand Content, Offers, Infrastructure.
What got built
In their words
For most of a decade I was the person people came to when a system was a mess, a room had gone quiet, or nobody wanted to say the obvious thing out loud. It was never in a job description. Clients and colleagues at Pluralsight, MURAL, GitHub and Shyft wrote it down anyway.
“I was supposed to be the manager of our system, and I was being locked out by another user. It really was above my head as far as what I could understand, but CO was really patient with me. She was able to create a workflow and independently resolve the complete migration, including giving us all access to the right files with the right permissions.”
Barbara W.
Operations Manager, LV Wheels · Auto Rims & Detailing — The Baddie Stack client · 2026
“Helpful, a clear communicator and committed to making sure that the goals we envisioned when we started made progress to reality.”
Michael R.
Solutions Architect & Technical Trainer · Slalom — client at Pluralsight · 2021
“Extremely customer focused, energetic, and a fantastic collaborator. A true problem solver.”
Kristen C.
Strategic Projects Leader, Enterprise Learning & Enablement · Old Navy — client at Shyft · 2021
And the people beside me
“She was the director of customer success acting as a window between the engineering team and customers. She is always there to help whenever engineering teams need her, and usually tries to do extra to make our work easier.”
Bin L.
Software Engineering Director · Shyft Tech · 2021
“Her ability to dig into a situation, learn the environment, ask provocative questions and create solutions helped create a bridge between my team and the burgeoning success team she helped build.”
Deepak B.
Senior Android Engineer · Shyft · 2021
“An amazing leader and trusted advisor to our team and her customers. She is phenomenal at representing her customer's point of view and works in a collaborative way to enhance the overall customer experience.”
Cameron P.
Revenue Strategy & Operations · Pluralsight · 2021
“She's been super supportive in situations where her expertise was invaluable to helping a customer move forward. She has been a phenomenal SME.”
Amid Z.
Principal Solutions Delivery Consultant · MURAL · 2023
“When she speaks, everyone listens. She has a powerful grace I rarely see in an individual. It doesn't matter if she's at the helm, or in the trenches — she consistently leads by example.”
Logan L.
Customer Success, Technical Workforce Transformation · Pluralsight · 2021
“She communicated well with the customer, owned the Services engagement, and kept key stakeholders in the loop. CO is a thought leader in GitHub Services.”
Karl A.
Tech Leader, Ecommerce & Higher Ed Consultant · GitHub · 2025
The Baddie Stack is that same role, with a process and a price attached.
What I bring to it
Layer 01
“The problem is rarely what it looks like on the surface.”
Reviewing scattered tools and workflows to find what's actually creating friction — before anything gets rebuilt.
Ties to: Digital Systems Scan
Layer 02
“Systems should hold you, not the other way around.”
Automations, integrations, and no-code architecture that let founders execute without carrying it all manually.
Ties to: Done-For-You Founder Builds
Layer 03
“Competence you feel, not just perform.”
Closing the gap between what you already know and what you feel confident doing out loud — in the room, at the keyboard, in the ask.
Ties to: Systems Support for Professional Women
Layer 04
“Collaboration that actually finishes.”
Hands-on structure for teams and founders who need a partner in the build, not just a consultant with opinions.
Ties to: Done-With-You Implementation
Layer 05
“The right next step, not just any next step.”
A short, focused intake that surfaces goals and friction points before anything gets built or sold.
Ties to: Discovery
Global perspective
Cities, countries, colonies, tribes — New York to Panama City, Roatán to Chicago, and everywhere in between. A global eye sharpens local analysis.
Common questions
Pricing weighs formal education and certifications, 9+ years of direct engagement and immersive experience, and a unique skill set that combines holistic vision with an empathetic approach.
From the Services page, choose a session type, then decide between a Live Session or an Asynchronous engagement via the Training Portal. Booking means choosing a day and time, sharing context, and submitting payment to confirm.
A Live Session is timed (25/50/60 minutes), reviews the context shared at booking, and includes a live discovery conversation that ends in a custom, prescriptive walkthrough. An Asynchronous engagement runs through the Training Portal — an initial response to the booking context, discovery questions, and the client's answers — resulting in the same custom, prescriptive walkthrough, completed on the client's own time.
Your turn
Share what is going on, what feels heavier than it should, and what kind of support would actually help. From there, the best next paid step can be recommended.
