50%
faster delivery for new design components through AI-assisted development and tighter standards
AI Adoption Leadership
I lead AI adoption inside companies by turning manual work into operational systems teams actually use.
My focus is not AI as a demo layer. I build the workflows, tooling, standards, and team habits that make AI useful across the business and strong enough to change how work gets done, especially in B2B SaaS environments where marketing, sales, and product execution need to stay aligned.
700+
hours saved in the first three months through operational AI and workflow redesign
n8n
introduced as an operational layer for web systems, APIs, and automation
5-10m
outline creation time after AI, down from a 3-4 hour manual process
Current Signal
From content operations to engineering workflows, I build AI systems that reduce manual work, tighten quality, and give B2B SaaS teams a practical way to adopt AI at scale.
About
A builder who now focuses on leading AI adoption.
I come from senior software engineering, but my strongest work now sits at the point where operational change, tooling, and team behavior meet. I help companies introduce AI in a way that becomes part of how the business runs, from workflow design and automation to quality standards and day-to-day adoption. A lot of that strength comes from B2B SaaS, where marketing, sales, and development all need to stay aligned.
Lead AI adoption across the company
I build the rollout approach, operating model, and practical workflows that make AI relevant across teams instead of leaving it trapped in isolated experiments.
Turn manual processes into AI systems
From Notion-to-publishing flows to API and n8n automation, I design systems that remove repetitive work and make execution faster, cleaner, and more reliable.
Set standards teams can actually use
I help teams adopt AI with clear standards, practical tooling, and workflows that support both operators and engineers instead of overwhelming them.
Focus
What I lead teams to do with AI.
The hard part is rarely access to tools. It is designing the systems, standards, and rollout approach that make AI useful across real functions inside the company.
Operational Automation
Manual publishing work connected to web systems and APIs through n8n, turning repetitive steps into a reliable operational system.
Publishing Flow
Article outlines dropped from hours of manual effort to minutes with AI, giving the team a much faster editorial workflow.
Component Velocity
New components started shipping in roughly half the previous time through AI-assisted development and stronger implementation standards.
Cross-Team Delivery
Marketing, design, and web moved into a tighter execution loop, reducing handoffs and speeding up delivery together.
Proof
Recent proof from real operating systems.
The clearest signal I can offer is work already running inside a company: less manual process, faster publishing, stronger engineering standards, and measurable time saved.
Measured result
10,000s
of hours that can be saved per year
The first operational wins proved the model. The larger goal is building AI systems and internal agents that can save tens of thousands of hours per year across company workflows.
n8n became a real operational backbone
The goal was not to test automation in isolation. It was to wire manual work into systems the company could rely on, using n8n, web platforms, and APIs as part of daily operations.
Publishing moved from manual coordination to direct flow
Content publishing now moves directly from Notion into the publishing pipeline, which removes unnecessary handoffs and makes the process easier to scale.
Cross-team delivery got much tighter
AI-backed workflows helped connect marketing, design, and web execution into a much faster delivery loop, while new components started shipping in roughly half the previous time.
How I Work
Leadership, systems, and adoption have to move together.
The role I want is not to sit next to AI adoption. It is to lead it, shape the operating model around it, and make sure the systems are strong enough that teams can rely on them.
Lead with outcomes, not hype
AI work needs to make sense to leadership, operators, copywriters, and engineers at the same time or it will not stick.
Build the operating layer
I care about workflow ownership, automation, standards, and rollout, not just strategy decks or isolated pilots.
Design adoption into the system
If teams cannot use the tools confidently and repeatedly, the implementation is not done no matter how advanced the stack looks.
Connect
Open to leading AI adoption inside the right company, and to selected consulting conversations.
If you need someone who can lead AI rollout across workflows, standards, and teams, or you want focused help moving from AI interest to real operational use in a B2B SaaS context, reach out.