Marketing & growth executive

Michael Preuss

I lead growth for AI infrastructure and technical B2B companies, with positioning and brand as core drivers of demand. I get the programs working, hands-on or with the existing team, then hire people to run and scale what we’ve proven.

Explore by lens

Selected writing and work

Work

Blaxel / AI Marketing Systems

Joined June 2026 · Head of Growth & Marketing · 2 min

The marketing tools I built at Blaxel: paid media review, market research, answer-engine citation analysis and a shared go-to-market knowledge grap…

Daily marketing reviews

Writing link

Signal

  • S1

    I connected ad delivery, product activity and payment outcomes in a daily review. Proposed campaign changes still required human approval.

  • S2

    A shared go-to-market knowledge graph kept the tools working from evidence and review rules.

Proof points

  • P1

    At Blaxel, paid media review moved from monthly to daily.

Writing

You Don’t Need Better Prompts. You Need a Knowledge Graph.

2026-03-09 · 23 min

A practical guide to why prompting is a tactic, context is infrastructure, and a knowledge graph is how you stop GTM drift.

Context infrastructure

Signal

  • S1

    When company context is missing, the model guesses. A shared source of truth gives each session the same positioning, evidence and constraints.

  • S2

    Versioning that context lets the team review a correction once and reuse it across future work.

Work

Blaxel / Paid Growth & Measurement

Joined June 2026 · Head of Growth & Marketing · 2 min

How I ran paid acquisition at Blaxel, connecting campaign decisions to product activity and payment outcomes.

Acquisition efficiency

Signal

  • S1

    The review connected Google Ads delivery with PostHog product activity and Stripe payment outcomes.

  • S2

    I reported overall product activity separately from paid-attributed results.

Proof points

  • P1

    At Blaxel, paid-ad conversions rose 46%, spend fell 36% and cost per paid-ad conversion fell 56%, versus the prior 30 days.

Work

Blaxel / Customer Stories & Cookbooks

Joined June 2026 · Head of Growth & Marketing · 2 min

How I turned Blaxel customer architecture into technical stories and companion GitHub cookbooks that developers could inspect, run and adapt.

Technical customer proof

Signal

  • S1

    Each story explained the customer's architecture and what Blaxel operated. Selected companion cookbooks isolated a mechanism developers could reuse.

  • S2

    I prepared customer and company distribution copy, approvals and release waves alongside the technical drafts.

Proof points

  • P1

    The companion examples demonstrate files surviving sandbox deletion and code being built, checked and repaired in a retained environment.

Writing

The Lock-In Is Moving

2026-05-11 · 3 min

AI tools can hold the reasoning behind your team's decisions. What happens when you switch, and what does that mean for customer retention?

decentralized-ai · context-engineering

Signal

  • S1

    You can take the campaign reports and budget plan to another AI tool and still leave behind much of what the team learned making those decisions.

  • S2

    For tasks several models can handle, I think more of AI's lock-in will come from having to put that knowledge back together before another tool can do useful work.