Introduction
Marketing is under constant pressure to improve, and for good reason. Consumers expect personalized experiences delivered instantly, brand elevation and differentiation are more important than ever, and for retail and consumer brands, recent market pressure only adds to the need to move fast and with distinction.
Legacy marketing operations are siloed and slow, and struggle to keep up. Tools are disconnected, data is disjointed, and marketing leaders make trade-offs just to keep up. Manual approvals, spreadsheets, repetition of routine tasks drain creative energy from teams. At the same time, marketing leaders have a deep desire for their teams to focus more on creative output than mundane tasks and recurring fire drills.
The brands that win will be the ones that reboot how they run their marketing operations. That is why I decided to build ANI (Agentic Native Integration) for the marketing function. ANI is part transformation consultancy, part suite of agents and products that automate marketing workflows, built on real use cases with real clients.
I believe if you've chosen marketing, you deeply value strategy, creativity, and storytelling. I am not here to rewrite your competitive advantage. I am here to help you gain speed and clarity, and amplify what you are uniquely good at. Transforming your ways of working only strengthens your moat.
Why ANI
ANI is human-centered transformation applied to AI, built for teams who want to move fast (or even faster).
There is tremendous opportunity in AI integration right now. Unfortunately, companies spending on AI are not seeing real change. I recognized this opportunity, and I have proof that as a marketing operator I can do this integration work better and faster than my competition.
I spent a decade as a Chief of Staff to CMOs, CEOs, and enterprise leaders (Meta, Instagram, Nike, Lululemon) focusing on strategy and operations, transformation, and growth.
Services
Five services. They can be engaged separately, but they work best in order: understand how the work actually runs, bring the leaders with you, build, then teach the team to keep building without me.
Transformation planning
An objective assessment of how your operations run today — workflows, data, decision rights, systems, incentives, and habits — and an end-to-end map of the work that matters. You get a prioritized roadmap with an owner and a date against each item, not a wish list.
Leadership coaching
One-to-one work with the executives who own the function, on their real material, in private — so senior leaders can be beginners without an audience. You leave able to tell a good result from a confident one, and able to sponsor the work publicly so the organization sees the mandate is real.
Strategy support
A leader's right hand through the decisions that come after the plan is signed: build versus buy, vendor and platform choices, governance people can actually follow, and the agent <> human operating model. Measurement that survives a board meeting, including honest reporting on what has not worked.
Workflow automation
Prioritize honestly, prototype quickly, and put the human where judgment belongs. Build the context layer first — the docs, permissions, data, and feedback loops agents need — then deploy on a schedule. Your team owns what we build, and the reasoning is written down so they can change it.
Team bootcamp
Hands on keyboards, on your own live work, never generic exercises. Every session ends with an asset the team keeps: a prompt, a context doc, a working skill. You also get a written internal playbook, so the practice survives the people who attended.
Working principles
- 1
People routinely overestimate what AI can change in the short-term
Models improve faster than companies. Real change inside companies requires two steps: first, an objective assessment of your existing operations and improvement to your workflows, data, decision rights, processes, systems, incentives, habits, and culture. Second, the automation.
- 2
Agents can replace tasks, not jobs
Agents can automate tasks but not yet replace jobs. Jobs are composed of thousands of tasks layered with nuance, decisions, relationships, judgement, and most critically friction. I am interested in finding the right balance between agentic and human responsibilities.
- 3
Early failure in automation is inevitable
Agentic work has a high upfront investment in human capital: setup, testing, patience. Most give up after the first shipped agent delivers slop or makes an error. Training is more critical than shipping.
- 4
Humans have agency
Agency as a word is peculiar in the context of AI, but leaders and teams should and must have ownership over the orchestration of their work. They define and refine the strategic direction, set and track goals, manage agents, decide the level of automation that is appropriate for their organization, decide when to intervene, and ultimately are accountable for outcomes.
- 5
Specificity matters
As intelligence gets cheaper, specificity gets more valuable. Differentiation comes from an organization's context, its leaders' point of view, niche expertise, distinctive quality standards, and real understanding of their customer.
- 6
Reinvention matters for both people and companies
I have rebuilt my career repeatedly. Being a beginner on purpose has led me to learn and grow in a way that is rewarding to me. Learning new skills and a new way of working can seem daunting, but today it's required, at every level. Same goes for companies. What will make companies successful in the long-term is their ability to reinvent themselves. Today, that has to do with agentic transformation.
Contact
My background includes working at companies such as Nike, Meta, and Instagram, and I'd welcome the opportunity to bring that expertise to your organization. If you are ready to transform your marketing organization and claim AI-native marketing operations, or if you are curious to learn more, I'd love to hear from you.