The Pathlit Method™
You are not looking for attention. You are looking for the right project.
The kind that is worthy of what you know. Specific enough to be meaningful. Structured enough to sustain. Connected to the contribution you have always felt you were here to make.
The Pathlit Method™ is a three-act framework for seasoned women leaders who are ready to define that project — and show up in a way that feels less like performance and more like the most natural extension of everything they have already built.
01
Act I
Framing
You have already done the work.
Most frameworks start with your audience. This one starts with you. Framing is where we get clear on the problems you are built to solve, the values that have quietly shaped every decision you have ever made, and the people whose world you most want to change.
Not as an exercise. As an excavation. Because the leaders who resonate online are not the ones who figured out the right content strategy. They are the ones who finally found the language for what they have always known.
Framing gives you that language. A playbook that is yours to keep. A source of truth to return to when the noise gets loud.
02
Act II
Placement
Now we give it a location.
You have the wisdom. You have the framework. You have decades of knowing exactly what needs to be said. What you do not have is time to figure out where to say it, how to build it, whether it is working, and who is actually on the other end.
This is where we choose the right channel for your specific contribution, build a content architecture that fits inside your actual life, and create a rhythm of showing up that is sustainable because it was designed for you.
No guesswork. No content treadmill. Just a clear, deliberate structure for getting your project into the world.
03
Act III
Continuation
Sustained presence over time.
This is where most visibility strategies fall apart. Life adds something new. A role shifts. A season gets hard. The content stops. The momentum disappears. And starting over feels worse than never having started.
Continuation is the act of staying in motion without it consuming you. Every month you get a dedicated strategy call, a private Slack channel with peers and direct access to Tess — a text, an email, a voice note with a half-formed idea that needs a second opinion.
This is not a subscription to content. It is a sustained creative partnership. Your project grows with you.
Core principles
The method is built on five beliefs.
These are not rules. They are the convictions that shape every engagement — and the reason the work feels different from a content strategy.
01
Nuanced Communication
Most leaders are more complex than their current messaging reflects. The work honors that complexity instead of flattening it.
02
EQ as Operating Logic
How you read a room determines how well your message lands. Emotional intelligence is not a soft skill — it is the whole skill.
03
Visibility as Stewardship
Your perspective has value beyond your title. Withholding it has a cost — to you and to the people who need to hear it.
04
Behavioral Change Through Modeling
The most powerful thing you can do is demonstrate the thing you are asking others to do. Lead by showing up.
05
Iteration as Evidence
Showing up imperfectly over time is more credible than waiting until it is perfect. Continuation is the proof.
Entrepreneurs, educators, & advocates driving social or cultural impact.
Change Management
Emotional Intelligence
Change-makers are the ones redefining what’s possible, redirecting the master narrative, and protecting communities.
I’m here to help you transform bold ideas into sustainable impact.
I thrive at the intersection of emotional intelligence and empathy-driven change management, helping you navigate the complexities of transformation with care and clarity.
Whatever you’re working toward, I would be honored to amplify the movement.
Artists, filmmakers, writers, & designers looking to scale their vision.
Strategy
Analytics
Marketing Yourself
…these things tend to give even the most successful creators a case of the spookies.
Let us translate your genius and back it up with data and narrative.
We’re the team you call when the creative sparks fly but the details start to weigh you down.
From capturing those behind-the-scenes moments to brainstorming bold ideas or locking in the opportunities that take you to the next level, we’ve got you covered.
Nonprofits, start-ups, mission-focused brands, & socially responsible companies.
Whether you need:
a creative partner
a strategist
an executor
all of the above
—I’m here for it.
I’ve worked with professionals at every level, from C-suites and executive directors to board members, strategists, managers, and individual contributors, making sure everyone understands their role and feels empowered to contribute to the project’s greater purpose.
Thank you for taking the time to explore my portfolio.
Every project here represents a relationship built on trust—trust from mission-driven organizations and individuals with big ideas and the courage to pursue them.
That trust is something I deeply respect.
Each campaign I’ve created, every strategy I’ve designed, and all the content I’ve crafted have been opportunities to amplify voices that matter, highlight meaningful work, and connect people through shared purpose.
For me, marketing isn’t about selling—it’s about serving. It’s about showing up with creativity, clarity, and commitment to help others bring their vision to life.
Thank you for being here. I hope my work inspires you to imagine what’s possible for your own purpose, and I look forward to the possibility of supporting your journey.
With gratitude,
Tess
What is Federated Learning?
Federated learning is an AI training approach that enhances privacy and security by keeping data localized on users’ devices instead of centralizing it in one location. This decentralized method allows models to learn from data across multiple devices or servers while only sharing insights—rather than raw data—back to a central system.
In the context of AI responsibility, federated learning minimizes data exposure, reduces the risk of breaches, and supports compliance with data protection regulations like GDPR and CCPA. It also promotes ethical AI development by preserving user control over personal information and enabling more inclusive and privacy-focused AI systems.
What is Dynamic Workload Scheduling?
Dynamic workload scheduling is an energy-efficient computing strategy that adjusts when and where AI workloads are processed based on real-time conditions, such as renewable energy availability, electricity prices, and server capacity.
In the context of sustainable AI computing, it means shifting AI training or inference tasks to times and locations where renewable energy sources (like solar and wind) are abundant to reduce carbon emissions and energy costs.
How Does Dynamic Workload Scheduling Work?
Aligning AI Training with Renewable Energy Peaks
Load Balancing Across Data Centers
Taking Advantage of Variable Electricity Pricing
AI-Optimized Scheduling Systems
Google’s Carbon-Aware Computing:
Microsoft’s Project Forge Global Scheduler:
What Is an AI Accelerator?
An AI accelerator is a specialized hardware component designed to speed up artificial intelligence (AI) and machine learning (ML) workloads more efficiently than traditional processors like CPUs (Central Processing Units) or even GPUs (Graphics Processing Units). These accelerators are optimized for parallel processing, lower energy consumption, and high-performance AI computations.
How Do AI Accelerators Work?
Unlike general-purpose CPUs, which handle a wide variety of computing tasks, AI accelerators are custom-built for specific AI operations such as:
Matrix multiplications & tensor processing (core operations in deep learning).
Neural network training & inference (faster model execution).
Optimized data flow (reducing memory bottlenecks).
These accelerators reduce the energy and time required to train AI models and process real-time AI applications, making them crucial for sustainable computing strategies.
Examples of AI Accelerators
1. Google Tensor Processing Units (TPUs)
What it is: Custom-built by Google for deep learning workloads.
Why it matters: Uses less power than GPUs while accelerating AI model training.
Example: Google’s TPUs power Google Search, Google Photos, and AI-driven healthcare research.
2. AWS Inferentia (Amazon Web Services)
What it is: A custom AI chip designed for machine learning inference (running trained AI models efficiently).
Why it matters: Uses lower power and costs less than GPUs for AI-powered applications.
Example: Powers Alexa, AWS AI services, and real-time recommendations for e-commerce.
3. NVIDIA Grace Hopper Superchip
What it is: A hybrid CPU-GPU superchip designed for high-performance AI applications.
Why it matters: Reduces energy consumption while handling massive AI models like large language models (LLMs).
Example: Used in supercomputers, autonomous vehicles, and generative AI models.
A specialized processor designed for parallel processing, originally developed for rendering graphics. GPUs have thousands of smaller cores that can process multiple tasks simultaneously, making them ideal for AI, machine learning, gaming, and high-performance computing. Unlike CPUs, GPUs are optimized for large-scale data computations, enabling faster processing of complex mathematical operations.
