AI advisory, engineering, and company-wide implementation

Advice that can carry into the build

Some engagements start with a business decision: where AI belongs, what to build, or how a product should change. Others start with software that needs to ship or teams that need help adopting it. I work across those problems as an AI implementation specialist, product engineer, and advisor.

Bring me in to own a product build, implement AI across teams, or advise your leadership as the work moves into delivery. My forward-deployed engineering practice means working directly with your team to understand requirements, build and integrate the system, deploy it, and support adoption. We agree on scope, decision ownership, and acceptance criteria before the build. I work with teams worldwide.

How an engagement can work

A briefing, a build, and an embedded implementation need different levels of involvement. We can start with a bounded problem, define a useful deliverable, and agree who owns the next decision. Workshops are one format; full-stack delivery and ongoing implementation support are others.

• Advisory: executive briefings and working sessions that turn business priorities, product and model gaps, or operating constraints into a practical implementation scope.
• Build and implementation: a defined product or agent-system scope, with engineering, integrations, evaluation, and deployment planned together.
• Team enablement: lunch-and-learns and hands-on working sessions around the software and workflows people need to use.

Define the work and what success requires

Before the work begins, we define the business need, access and integration requirements, review responsibilities, and what a useful result would look like. The scope makes clear which decisions stay with your team and which parts I take on.

An advisory engagement can produce an implementation brief or prioritized roadmap. A build can cover requirements, engineering, evaluation, and deployment. Company-wide work can include operating documentation, handoffs, and an adoption plan. We agree on the deliverables for your engagement rather than promise the same package to every company.

For AI startups and founders

I help AI startups examine where a model or product falls short in real customer work. We look at the task, the failure cases, and the surrounding system before deciding whether the gap calls for better context, a different workflow, an integration, an evaluation, or a change in product scope.

For founders building a new company, I also advise on using AI inside the business: product development, research, engineering, growth, and operations. The aim is to choose a workable operating model early, with clear ownership and an honest view of the limits.

• Model-to-workflow fit: identify capability gaps, failure cases, and the conditions under which the product is useful.
• Customer implementation: connect the AI product to a company's data, tools, review requirements, and daily work.
• Founder operating systems: decide where agent teams can support delivery across functions and where human judgment must stay.

Advisory through implementation

I work across the technical and operating sides of implementation. That can mean owning a product build, advising a leadership team, or staying involved as teams put the system to work. These are the areas we can scope together.

• 01AI strategy & advisory:

  assess business priorities, model and product gaps, customer needs, and what is worth building. Define success criteria and an implementation roadmap.

• 02AI product & agent engineering:

  build customer-facing software, application backends, AI integrations, and agent systems. Scope evaluation and deployment as part of the engineering work.

• 03Forward-deployed engineering & implementation:

  work directly with your team on requirements, working software, integrations, and deployment. Prepare documentation, operational handoffs, and adoption support across functions.

• 04Growth engineering & enterprise adoption:

  connect product research with content systems, onboarding, customer education, and product feedback.

• 05Private enablement & embedded support:

  executive briefings, lunch-and-learns, hands-on team sessions, implementation guidance, and ongoing delivery support.