AI automation & marketing that pays for itself.

Practical AI training that helps teams actually use these tools in their day-to-day work.

The workshops focus less on theory and more on doing: using tools like ChatGPT, Claude, Gemini, Make, Zapier, n8n and others to improve real workflows, automate repetitive tasks and work more efficiently.

AI is quickly becoming a normal part of how we work. The teams that learn how to use it well now will be better equipped to move faster, experiment more and get more done.

Typical duration: 1-3 day intensive workshops, plus optional ongoing consultation. Perfect for marketing teams, operations departments, or entire organizations looking to build internal AI capabilities.

I build automation systems that take repetitive work off your team’s plate and connect the tools you already use.

That can mean automating data entry, moving information between systems, triggering follow-ups, or building more complex workflows across your CRM, project management tools, analytics platforms and internal apps.

Depending on the setup, I use tools like Make, n8n, Zapier and Python to build something that fits the way your team already works.

The reality is that most businesses waste 20-30% of employee time on manual, repetitive tasks that could be automated. Modern no-code and low-code platforms have made enterprise-grade automation accessible to businesses of all sizes. Implementations typically take 2-6 weeks depending on complexity, with measurable time savings visible within the first month.

See it in action:

This is one of my production builds: an SDR fills in a three-field form — industry, geography, how many targets — and a research agent finds, screens, and dedupes real companies before handing them off for enrichment. The animation below is the actual logic.

Waiting for an SDR to ask for a list…

See how this workflow is built →

I help build marketing strategies around what the data is actually telling us.

That means looking at the full customer journey, finding where people drop off, identifying the channels and activities with the most potential, and improving them over time.

I combine traditional marketing thinking with AI and analytics to make better decisions, test faster, and build acquisition systems that can scale.

In an era where customer acquisition costs are rising across all channels, strategic precision matters more than ever. The difference between good and great marketing is often about making better decisions with better data, not just spending more money. Engagements typically span 4-8 weeks for initial strategy development, with optional ongoing advisory roles.

I build AI agents that can do more than just follow a fixed set of rules.

Instead of simply responding to prompts, these systems can understand context, make decisions, work through multiple steps, and take actions across different tools.

I use models like Claude and GPT alongside frameworks such as LangChain and custom setups to build agents around real business processes. They’re useful when a workflow is too complex or unpredictable for a traditional “if this, then that” automation.

The technology here is rapidly maturing. What seemed like science fiction 18 months ago is now production-ready. Organizations implementing AI agents early are seeing 40-60% reductions in response times and significant improvements in output quality. Implementation timelines range from 3-10 weeks depending on complexity and integration requirements.

I build content systems that make it easier to create and publish consistently without handing everything over to AI.

That can include everything from finding ideas and drafting content to reviewing it, publishing across channels, and tracking what performs.

AI handles the repetitive parts and speeds up production, while human input stays where it matters most: judgment, quality, tone, and originality.

The ideal content engine is a hybrid system where AI handles research, structure, and first drafts, while humans provide strategic direction, creative refinement, and quality assurance. Organizations implementing content engines typically see 3-5x increases in output volume while maintaining or improving quality. Setup takes 3-6 weeks, with continuous optimization based on performance data.

See it in action:

My AI SEO content agent: twice a week it runs a Semrush gap analysis, dedupes against the content calendar, picks ten keywords, and has Claude draft each article against a strict brief — staged in Notion for human review. Nothing publishes itself.

Waiting for the Monday batch…

See how this workflow is built →