Hire an AI Product Manager

Your product needs an AI strategy. You don't need a full-time AI PM yet.

Most companies at the AI-feature stage don't have a product manager who understands AI well enough to write specs for it, evaluate vendors, or explain trade-offs to a board. We provide that function for a fixed engagement, no full-time hire, no equity, no six-month ramp-up.

Engagements are scoped to your product, typically four to eight weeks. You get a prioritized feature backlog, written specs, vendor evaluation, and stakeholder materials.

How we work

Tell us about the AI features you're trying to define.

What you get.

Four things every AI PM engagement covers. Together they give you what you need to make confident decisions and hand work to your engineering team.

AI feature scoping and spec writing

Clear product requirements for AI features written in a format your engineering team can build from, not vague ideas about what AI could do.

Vendor and tool evaluation

A structured comparison of the tools and vendors that fit your use case, with real cost estimates and honest trade-offs. No vendor kickbacks.

Build vs buy decisions with real numbers

When building custom makes sense versus buying an existing solution, with total cost of ownership estimates for both paths so the decision is based on data, not instinct.

Stakeholder communication and demo prep

Presentation materials, demo scripts, and executive summaries that explain what the AI does and why, in language that doesn't require a technical background.

Who this is for.

Founders who know they need AI but aren't sure where to start
You've seen what AI can do and you have a sense your product could use it. You don't have a product manager who understands AI well enough to define what to build first. We give you a prioritized list with the reasoning behind it.
CPOs adding AI to an existing product roadmap
You have a roadmap. You need to understand which AI features belong on it, which order makes sense, and what each one will actually cost to build before you commit your engineering team's time.
Teams that have AI engineers but no PM driving the product side
Your engineers can build. The problem is that nobody has defined what success looks like, written the specs, or made the vendor decisions. We provide the product layer so your engineers can focus on building.

Frequently asked questions.

What does an AI PM do that engineering doesn't?: Engineers decide how to build something. An AI PM decides what to build and why, in what order, and whether to build it at all. That means writing specs that define the user problem (not just the technical solution), evaluating vendors before the engineering team commits time to an integration, and communicating progress and trade-offs to stakeholders who don't read Jira tickets.
How long does a fractional AI PM engagement last?: Most engagements run four to eight weeks. The first half is scoping: understanding your product, your users, and your AI goals, then producing a prioritized feature list with specs. The second half is supporting the build: answering questions, reviewing progress, and preparing stakeholder communications. Engagements can be extended if you have ongoing PM needs.
What do I get at the end?: A prioritized AI feature backlog with written specs for each item, a vendor evaluation document covering the tools you're considering, a build vs buy analysis for the top one or two features, and a roadmap presentation you can use with your board or investors. Everything is in formats your team can work from immediately.
When should I hire a full-time AI PM instead?: When you have more than three or four AI features in active development simultaneously, a dedicated AI PM starts to pay for itself. If you're still in the “figure out what to build” phase or have one or two AI features per quarter, fractional is the right fit. We'll tell you honestly if we think you've crossed the threshold for a full-time hire.

Ready to define your AI roadmap?

Tell us about your product and the AI features you're considering. We'll reply within one business day with a rough scope and price range, no commitment required.

Your product needs an AI strategy. You don't need a full-time AI PM yet.

Engagements are scoped to your product, typically four to eight weeks. You get a prioritized feature backlog, written specs, vendor evaluation, and stakeholder materials.

What you get.

Four things every AI PM engagement covers. Together they give you what you need to make confident decisions and hand work to your engineering team.

AI feature scoping and spec writing

Clear product requirements for AI features written in a format your engineering team can build from, not vague ideas about what AI could do.

Vendor and tool evaluation

A structured comparison of the tools and vendors that fit your use case, with real cost estimates and honest trade-offs. No vendor kickbacks.

Build vs buy decisions with real numbers

When building custom makes sense versus buying an existing solution, with total cost of ownership estimates for both paths so the decision is based on data, not instinct.

Stakeholder communication and demo prep

Presentation materials, demo scripts, and executive summaries that explain what the AI does and why, in language that doesn't require a technical background.

Who this is for.

Founders who know they need AI but aren't sure where to start

You've seen what AI can do and you have a sense your product could use it. You don't have a product manager who understands AI well enough to define what to build first. We give you a prioritized list with the reasoning behind it.

CPOs adding AI to an existing product roadmap

You have a roadmap. You need to understand which AI features belong on it, which order makes sense, and what each one will actually cost to build before you commit your engineering team's time.

Teams that have AI engineers but no PM driving the product side

Your engineers can build. The problem is that nobody has defined what success looks like, written the specs, or made the vendor decisions. We provide the product layer so your engineers can focus on building.

Frequently asked questions.

What does an AI PM do that engineering doesn't?

Engineers decide how to build something. An AI PM decides what to build and why, in what order, and whether to build it at all. That means writing specs that define the user problem (not just the technical solution), evaluating vendors before the engineering team commits time to an integration, and communicating progress and trade-offs to stakeholders who don't read Jira tickets.

How long does a fractional AI PM engagement last?

Most engagements run four to eight weeks. The first half is scoping: understanding your product, your users, and your AI goals, then producing a prioritized feature list with specs. The second half is supporting the build: answering questions, reviewing progress, and preparing stakeholder communications. Engagements can be extended if you have ongoing PM needs.

What do I get at the end?

A prioritized AI feature backlog with written specs for each item, a vendor evaluation document covering the tools you're considering, a build vs buy analysis for the top one or two features, and a roadmap presentation you can use with your board or investors. Everything is in formats your team can work from immediately.

When should I hire a full-time AI PM instead?

When you have more than three or four AI features in active development simultaneously, a dedicated AI PM starts to pay for itself. If you're still in the “figure out what to build” phase or have one or two AI features per quarter, fractional is the right fit. We'll tell you honestly if we think you've crossed the threshold for a full-time hire.

Ready to define your AI roadmap?

Tell us about your product and the AI features you're considering. We'll reply within one business day with a rough scope and price range, no commitment required.