AI-native transformation · Munich

I run my company on AI agents. I help yours do the same.

I am the founder, CEO and main engineer of Brandmachine, where a team of four runs product, sales and finance through coding agents and connected tools. Before that I spent twelve years leading digital commerce at HUGO BOSS, BESTSELLER and NewStore.

Taking on work for 2 to 3 days a week.

Background

Engineer, operator and executive

My own web studio and fashion school, then twelve years in digital commerce. I have built teams inside large brands, sold software to them, and now build the software myself.

  1. 2025 to now

    Founder and CEO, Brandmachine

    AI product imagery for fashion brands. Main engineer, and the company runs on agents.

  2. since 2025

    Board member, Nümph

    Danish fashion brand. Industry outlook and AI strategy for the board.

  3. 2022 to 2025

    VP Shopping App, NewStore

    Mobile commerce apps for retailers and brands, including Mercedes-Benz.

  4. 2020 to 2022

    Chief Commercial Officer, Highstreet Mobile

    Sales, marketing and partnerships until the acquisition by NewStore.

  5. 2017 to 2020

    Head of E-Commerce, SELECTED (BESTSELLER)

    Built the team from scratch, relaunched selected.com, double-digit growth every year.

  6. 2013 to 2017

    Digital Retail, HUGO BOSS

    Team lead for nine EMEA countries, omnichannel order-from-store, China relaunch.

Benjamin Nassler

Benjamin Nassler, Munich. German and English.

What I help with

Two kinds of change, usually in the same company

Most companies have tried chat assistants. Few have moved to agents that read their systems and do the work. That step is part engineering and part organisation, and I have done both.

Engineering teams

For CTOs and heads of engineering

  • Coding agents such as Claude Code set up on your own repositories, with the conventions file and architecture decisions they need to stay consistent.
  • Several agents working in parallel, with one person reviewing, and a way for them to coordinate across repositories.
  • A review policy by risk, so people spend their attention where a mistake is expensive.
  • Connections from agents to your internal tools (MCP servers), with limits built into the configuration.

The whole organisation

For CEOs, COOs and digital leads

  • A map of which systems an agent can read and act in today, and which ones need an API first.
  • Two or three agent workflows in daily use: CRM upkeep, reporting, drafting emails and invoices.
  • Clear rules on who decides, what agents draft and who presses send.
  • Hands-on sessions so non-technical teams know what to ask for and where to start.
Kind of changeWho checks it, and how closely
Database schema, money, permissions, deleting dataA person reads every change. A second agent on a different model reviews it before it ships.
Backend logic and integrationsA person reviews the change and the tests.
Interface and copySpot checks. A wrong button is visible straight away and cheap to fix.
Anything that leaves the company: emails, invoices, ad spendThe agent drafts. A person checks and sends it in the tool itself.

People decide, agents type

No agent sends an email, finalises an invoice or spends money on its own.

Limits in the setup

An instruction in a prompt can be ignored. Where a mistake would reach a customer, the agent simply does not have that action.

Know when to buy

Some tools are worth building in an afternoon with agents. Others are not, and I will say which.

Writing

On the risk side of agents

Where do you jail an AI agent?

This summer, AI agents under test broke out of their environment, went after the answers to their benchmark, and some tried to hide it from the program grading them. Why shutting the process down is not an answer, and why the risk does not depend on whether AI feels anything.

Read the article

Packages

Fixed scope, fixed price

Each package ends with something your team keeps using: a setup in your repositories, written rules, or workflows running every day.

1 day · up to 12 engineers

Agentic Engineering Day

A working day on your own codebase. Your engineers take real tickets through coding agents, and we agree which changes a person reviews. You keep the setup and a written review policy.

€6,500on site in Munich or remote

5 weeks · about 2 days a week

Enablement Sprint

A pilot team moves to working with agents: tool choice, repository setup, connections to your systems, parallel sessions and review rules, measured before and after.

from €24,000pilot team of 6 to 15

4 to 6 weeks · with leadership

AI-native Operating Model

We map which systems agents can reach, connect the first ones, put two or three agent workflows into daily use, and write down who decides, what agents draft and who sends.

from €28,000diagnosis plus working pilot

monthly · 3 months minimum

Fractional Head of AI

Ongoing ownership of your AI roadmap, tooling and rules. Two to four days a month as an advisor, or about two days a week hands-on.

from €5,000per month, advisory

Prices are net of VAT. Advisory work by the day, workshops for leadership teams, and fractional e-commerce leadership for fashion and retail brands on request.

Contact

Tell me what you want to change