I trained to control air traffic. Now I control
AI automations.
From air transport management through years in B2B sales to an AI specialist role at a marketing company. Different industries, the same principle: watch the system, catch the deviation before it becomes a problem, and bring things safely to their destination.
Where I come from and what I bring to AI
I studied air transport management — a field where one thing gets drilled into you: watch several systems at once, spot the deviation before it becomes a problem, and never improvise where a procedure already exists. I then spent more than seven years in logistics and B2B sales, carrying that same discipline into client care, negotiation and team coordination.
Since February 2026 I have been an AI specialist at a marketing company, applying that same way of thinking — system, precision, a repeatable process — directly to building AI agents and automated workflows. This isn't course theory: I solve the company's real operational problems with the approach I learned studying air transport management and later proved in practice in logistics and B2B sales — except now the system does part of the work for me.
Technical background
- 01n8nWorkflow automation, connecting tools and APIs
- 02LLM APIOpenAI, Anthropic, OpenRouter — prompting and integrations
- 03MCPConnecting AI agents to tools and data sources
- 04REST API / FTPData flows between systems
Brought from my previous career
- →B2B negotiation7+ years of direct client contact
- →Systems thinkingFrom an environment where error is not an option
- →Team coordinationNearly 2 years leading a team as a sales manager
What it looks like in practice
A look at how these internal tools work — running on sample data.
Sales enquiry log with AI-drafted replies
Incoming sales emails are logged into an internal app — you can open them, check attachments and have the AI draft a reply. Click an email in the list.
Client database with AI-suggested outreach
For each client the AI reviews their profile and last interaction, then suggests how to approach them next — kept as a notepad. Click a client tab.
GA4 campaign labeller
Automatically pulls data from GA4, assigns readable labels to campaigns by channel and writes them into an internal database for the dashboard. Click to run a sample pass.
The dashboard where I watch this chat
The chatbot on this page has its own admin dashboard with notifications to my phone — and this is its live view of your conversation. Write something to Mini-Angelika and watch what I see: messages in real time, the conversation status, and the alert that fires when you ask for a real person. For privacy reasons you can't see anyone else's conversations here.
Ask me something to start the demo.
