Pricing & Packaging Strategy — by an AI council
Design pricing, tiers and the value metric that scales with what you deliver. Four rival AIs debate it and hand back: A recommended pricing model, tiers, price points and what to test first.
A recommended pricing model, tiers, price points and what to test first.
Signed off by an independent Final QA audit — with a “verify before you rely on this” list, never a black box.
Why this team
Pricing sits at the intersection of value, psychology and arithmetic, and each seat covers a way it goes wrong: the Pricing Strategist designs the model, the Economist tests it against willingness-to-pay, and the Behavioural Economist checks how the tiers read to an actual buyer scanning the page. The Sales Leader reports what happens in real negotiations, the CFO does the margin arithmetic, and the Devil’s Advocate attacks the number everyone is being polite about.
Each seat runs on a different frontier model — GPT, Claude, Gemini, Grok — so it’s a genuine cross-model review, not one AI in costumes. How a run works →
What the debate sounds like
An illustrative excerpt — A B2B analytics startup charges a flat $99/month; its heaviest customer runs 40× the queries of its lightest, and the founders are debating usage-based pricing versus three seat-based tiers.
The 40× spread is the whole case: flat pricing means your best customer is subsidised by your smallest. But the value metric should be the thing that grows as they succeed — queries are a cost metric, and customers resent paying for costs. Price on seats with query allowances, so the invoice grows with adoption rather than with a meter they fear.
Whatever the metric, unpredictability is what kills the deal psychologically. A buyer who cannot forecast the invoice will not champion the purchase internally. If any usage component survives this debate it needs a hard cap or a pre-agreed band — “roughly this much, never more than that” is what gets a budget owner to sign.
From the deals I run: three tiers works only if the middle tier is where you actually want them to land, and the current draft makes the top tier the honest fit for the 40× customer at a price that triggers procurement review. Land them mid-tier, and let usage growth force the upgrade conversation next year — with the data on your side.
Questions
Can the council recommend actual price points, not just a model?
Yes — the final synthesis commits to a recommended model, tiers and concrete numbers with the rationale, plus the single value metric to price on. The numbers are grounded in what you share about customers, alternatives and costs, and the verdict flags which of them deserve a real-world test before you publish a pricing page.
Should I raise prices on existing customers too?
That is treated as its own decision inside the debate — grandfathering, migration windows and the trust cost of repricing loyal accounts get argued separately from the new-customer model, because the two calls fail differently. The recommendation states which change to make first and which to defer.
How is this better than copying a competitor’s pricing page?
A competitor’s pricing encodes their costs, their segment and their mistakes. The debate prices your value metric against your buyer’s willingness to pay — and the Devil’s Advocate exists precisely to attack comfortable anchors like “the market charges $99, so we should”.
Your material is used only to run your review — never to train public models. Encrypted in transit and at rest. Security & privacy →
Want full control — pick your own minds, set the depth? Open the full council →