Product positioning is the one-sentence answer to that question. It is the strategic frame that decides whether a buyer sees you as a feature, a product, or a category – and whether they can tell you apart from the incumbent bolting AI onto their suite or the foundation model that powers you both.
The Problem
Every competitor claims the same model capabilities
When you and every rival are building on the same foundation models, your spec sheet and theirs read identically – same accuracy claims, same latency, same benchmark wins that flip with the next release. A buyer comparing five AI products in your space sees five versions of the same paragraph, so the decision collapses to price or to whoever they already know. Positioning on capability puts you in a bake-off you cannot win because the capability is not yours alone. The position has to rest on something a competitor with the same model still cannot claim.
You are squeezed between incumbents adding AI and the model providers themselves
The incumbent platform already owns the buyer relationship and is shipping an AI feature into the suite the customer already pays for, while the foundation model provider you build on can move up the stack into your use case at any time. A position that does not account for both pincers gets crushed – you look like a feature the incumbent will absorb and a thin wrapper the model provider will replace. Most AI companies position against neither threat explicitly and get surprised when deals stall on 'why not just use what we already have.' The position must give a buyer a reason you exist that neither the incumbent nor the model provider can copy.
You have not decided whether you are a feature, a product, or a category
This is the call that determines everything downstream, and most AI teams make it by accident. Position as a feature and you are easy to buy but easy to absorb into someone else's roadmap. Position as a category and you take on the cost of educating a market that has no budget line yet. Position as a product and you have to defend a clear boundary against both. Picking the wrong frame – or never picking – leaves sales improvising the story deal by deal and leaves investors unable to size what you are.
Your position is anchored to a model spec that is about to commoditize
A position built on 'we have the best model for X' has a shelf life measured in months, because the underlying capability gets cheaper and more available with every release. When the spec advantage evaporates, the whole position evaporates with it, and you are repositioning under pressure in front of customers who already bought the old story. Anchoring to a buyer outcome the model merely enables – not to the model itself – is what lets the position survive the technology getting commoditized underneath it.
How We Help
We start by deciding what you actually are, because the feature-versus-product-versus-category call governs every other choice and most AI companies have never made it deliberately.
From there we find the wedge a competitor with the same model still cannot claim.
Then we anchor the position to a buyer outcome, not a model spec. We translate what the technology does into the result the buyer is accountable for, so the position survives the capability commoditizing underneath it.
We also position against both threats explicitly – the incumbent adding AI to the suite and the foundation model provider moving up the stack.
The Winston Francois difference is that we treat positioning as a strategic decision an operator has to live with, not a tagline a creative team hands over.
The output is a positioning statement and strategic frame the whole company can repeat – what you are, who it is for, the outcome you own, and why neither the incumbent nor the model provider is the same choice.
What we deliver
- A committed answer to whether you are a feature, a product, or a category, with the reasoning
- A positioning statement anchored to a buyer outcome the model spec commoditizing cannot erase
- The defensible wedge a competitor on the same foundation model still cannot claim
- Explicit positioning against both incumbents adding AI and the foundation model providers
- The frame written into sales and marketing language so it propagates, not a one-page deck
In AI, the capability is rented from the same model everyone else rents, so it can never be your position. The only defensible position is the buyer outcome you own and the wedge a competitor with the identical model still cannot copy – everything anchored to a spec is borrowed time.
Our Methodology
Our positioning engagement opens with the decision most AI teams skip: are you a feature, a product, or a category? We test each frame against your defensibility, sales motion, and stage, then commit, because that single call decides how you sell, what you build, and how investors size you. We do not let the position stay ambiguous and bleed into every downstream choice.
The next phase finds the wedge. Since the foundation model is shared, the position cannot rest on capability – so we locate the proprietary data, owned workflow, trust, integration depth, or specific outcome a rival cannot replicate by calling the same API. We then anchor the position to that buyer outcome rather than a model spec, which is what lets it hold when the capability commoditizes. We also build the position explicitly against the incumbent adding AI and the model provider moving up the stack, since those are the objections that kill AI deals.
What makes this different from a generic positioning exercise is that we treat it as an operator's strategic bet, not a messaging deliverable. A standard agency polishes how you describe the same model claims everyone else makes. We change what you anchor to – from a spec that resets every release to an outcome and a wedge that survive it – and we write the position into the language sales and marketing run, so it is a frame the company lives, not a tagline on a slide.
How We Work
Initial engagements typically run 6 to 10 weeks because making the feature-product-category call, finding a defensible wedge, and anchoring the position to an outcome is real strategic work, not a one-week sprint. The first two weeks audit how the market sees you, where you blur into competitors on the same model, and which of the two threats – incumbent or model provider – is the live one. The middle weeks make the framing decision and locate the wedge. The final weeks write the positioning statement and translate it into sales and marketing language.
Our team includes a positioning strategist who owns the feature-product-category call and the statement, a writer who turns the frame into sales and marketing language, and a researcher who maps the competitive set and tests whether the outcome lands with buyers. From your side we need leadership for the strategic bet, sales for where deals stall on 'why not the incumbent or the model directly,' and a few customers to confirm the outcome we anchor to is the one they actually buy. We do not write a position in a vacuum and hope sales adopts it.
The cadence is working sessions through the build – market and competitor mapping up front, a framing-decision review where we commit to feature, product, or category, and a finalization review where we walk the full positioning statement and the sales and marketing language. Because positioning is a foundational decision, the deliverable is the committed frame and the language to run it, with the option to extend into the messaging, narrative, and go-to-market that propagate it once the position is set.
- A clear, defensible answer to whether you are a feature, a product, or a category
- A position that holds when the underlying model capability commoditizes
- A reason to choose you over both the incumbent's AI feature and the raw model
- Sales and marketing telling one consistent story instead of improvising per deal
If your ai / machine learning company needs product positioning leadership, we should talk.
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Frequently asked questions
How much does a product positioning engagement cost for an AI/ML company?
A defined positioning engagement typically runs in the $20K-$45K range depending on how crowded your competitive set is, how much buyer and competitor research it requires, and how much sales and marketing language comes out of it. That is in line with a senior strategy engagement, priced for a decision you will live with for a year rather than a tagline.
How long does it take to land a defensible position?
A defined engagement runs 6 to 10 weeks from market mapping to a finalized positioning statement and the sales and marketing language to run it. The feature-product-category decision usually takes shape in the first three to four weeks, since the rest of the work depends on it.
How does the positioning team integrate with our product and sales staff?
We work with product to make sure the position is one the roadmap can actually back, because a position the product cannot deliver is just a claim that breaks in the first demo. We work with sales to see exactly where deals stall on the incumbent or the raw model, so the position answers the objection that is really losing deals.
What makes this different from generic product marketing?
Generic product marketing polishes how you describe capabilities that, in AI, are shared by every competitor on the same foundation model – so it sharpens a message that cannot differentiate. This work is the strategic decision underneath that: whether you are a feature, a product, or a category, and what defensible wedge and buyer outcome the whole position rests on.
How do you measure whether the positioning is working?
We track whether buyers and sales repeat the frame – whether deals shift from spec comparisons to the outcome you own, and whether prospects stop asking 'why not just use the incumbent or the model directly.' The headline signal is sales telling one consistent story instead of improvising per deal, and win rates improving against the two threats the position was built to answer. We also watch whether the position survives the next model release without a scramble, since anchoring to an outcome rather than a spec is the whole point.
Is product positioning the right priority if our AI product is still early?
Companies stuck blending into competitors on the same model, or losing deals to 'why not the incumbent or the raw model,' are the strongest fit regardless of stage. So are teams that have never deliberately decided whether they are a feature, a product, or a category and are paying for it in an inconsistent sales story.
