Ads are the business. Signal is the constraint.
Our partnership roadmap with Meta, published rather than pitched. Worked backwards from Meta's own numbers: ads are effectively all of Meta's revenue, ad growth now comes from price per ad, price per ad is relevance, and relevance is signal. Signal is the input getting harder to source. That is the whole argument, and everything below follows from it.
Our proposal, in the open. Meta is not currently a partner, investor, or customer of ours, and nothing here is agreed with anyone at Meta.
Start with the P&L, not with our product.
Up 28% year over year.
Up 27%. Effectively the whole company.
The growth engine. Relevance, priced.
Inventory growth, and it cannot compound forever.
Quarterly operating loss, on $431M of revenue.
$31.1B in Q2 alone.
The growth is coming from relevance, and relevance is signal.
Ad revenue is $59.4B of $60.8B. Every other thing Meta does, the glasses, the models, the $130 billion of capex, is funded by that line. So the honest question for any partner is not what we would like to build together. It is what moves that line.
And the line is moving in a specific way. Impressions grew 14 percent and price per ad grew 12 percent. Impressions are inventory, and inventory growth has a ceiling: there are only so many surfaces and so many hours. Price per ad is relevance, and relevance is a function of signal. It is the half of the growth that can keep compounding, and it is also the half whose input is getting harder to source every year.
There are two ways to answer a signal shortage. Infer harder, which is what the whole industry is doing and which regulators, operating systems and people are all pushing back on at once. Or be given the signal. A declared intent from somebody who chose to publish it is more accurate than any inference, current rather than modelled, and it is the only kind of signal that gets easier to obtain as privacy law tightens instead of harder.
That is the layer we build, and it is the reason this is a partnership rather than a pitch. Meta has the demand, the auction, the ranking and the reach. What it cannot manufacture is a person's willingness to say what they actually want, to a company they are wary of. That has to be earned by somebody standing on the person's side of the line.
What Meta says it is building.
You cannot propose a partnership to a company you have not bothered to understand. This is the public record as of August 2026, taken from Meta's own earnings call and announcements, and every line is checkable.
Personal superintelligence, for billions
Not a lab AGI. An AI that knows a person's own history, interests, relationships and goals. Stated as the company's north star, with 2026 called a big year for delivering it.
Agents that run continuously, not chatbots that wait
Within five years, billions of people relying on autonomous agents working in the background on their behalf, rather than assistants that answer when spoken to.
The four things those agents will handle
Personal finances. Health. Household logistics. Interpersonal relationships. Meta named these, and they are, in order, the four most sensitive data sets a person has.
WhatsApp as the primary interface
The agent lives where the conversations already are. Family of Apps Other revenue, which is largely business messaging, grew 73 percent this quarter.
The ads stack is now AI end to end
Andromeda retrieves roughly a thousand candidates out of millions. Lattice ranks. GEM sits above both, trained at LLM scale, teaching the rest by distillation, and predicting the whole sequence of actions a person takes before and after seeing an ad.
Glasses as the surface
A target of ten million pairs of AI glasses in 2026, a display line arriving through the autumn and December, and Muse Spark described as running on device.
One dependency Meta cannot buy.
Read those six lines together and a single requirement runs under all of them. An agent that manages somebody's finances, health, household and relationships needs that person to hand over the four most sensitive data sets they have. An ads model that predicts the whole sequence of actions around a purchase gets dramatically better with declared context than with inferred context. Glasses that see what the wearer sees need permission from the wearer and social licence from everyone else in the room.
Every one of those is the same requirement, and it is the one thing capex cannot buy. Compute can be bought, models can be trained, distribution already exists. A person's willingness to say what is actually going on in their life, to a company they are wary of, has to be earned, and it has to be earned by somebody standing on their side of the line.
There is a real tension here and it is better said out loud. Meta's personal agent will run on Meta's infrastructure under Meta's incentives. Ours runs on the person's. Those are different products and we are not pretending otherwise. But they are not competitors for the same person, because a large number of Americans will never hand that data to a platform, at any level of capability, and no amount of model quality changes their mind. Serving them requires somebody whose entire business is being on their side. That is the segment we open, and it is a segment Meta structurally cannot reach alone.
Which is why the honest framing is not a vendor pitch. It is: you are building the agent, and we are building the reason a cautious person lets one near their life.
The roadmap
Five workstreams. One of them starts this week.
Each carries what we would ask for and the number that would tell us it worked, including the numbers that could tell us it did not. Only the first is ready today, and the page says which.
Design partner on Muse Spark 1.1
Ready nowThis quarter. Startable this week.
The Meta Model API is OpenAI-compatible, and bring-your-own-API is already a first-class capability in 🤫 Private Agent One: the person's key, their quota, their hardware. So an American can point their own agent at Muse Spark 1.1 today with nothing signed between us. We would rather do it properly, as a named design partner, with the feedback loop pointed back at Meta.
What we would ask for
Design-partner access and a channel to the model team.
How we would know it worked
Agent One shipping Muse Spark as a selectable provider, with real usage from real people on their own keys.
Consented signal for Ads
ProposalPilot in one surface, one quarter.
A person publishes a declared intent, not an inferred profile. Advertisers bid for permission to reach that intent. Matching happens on the person's device and no identity is transferred. This is signal Meta was never going to get, given rather than taken, and it gets better as privacy law tightens rather than worse.
What we would ask for
One surface, one market, and an agreed measurement of lift against the existing baseline.
How we would know it worked
Price per ad on the pilot cohort versus control. If it does not move, the idea is wrong and we should both know quickly.
Agent One on Ray-Ban Display
ProposalAfter 00 and a hardware conversation.
Glasses are the surface where the trust question is sharpest, because they see what the person sees. An agent that holds context locally and discloses per field, with a receipt, is the difference between a device somebody wears among other people and one they do not.
What we would ask for
Developer access to the glasses platform.
How we would know it worked
A working on-device agent loop with consent and receipts, demonstrated on hardware.
Business messaging that respects the person
ProposalFollows 01.
Meta has named WhatsApp as the primary interface for personal AI agents, and Family of Apps Other revenue, largely business messaging, grew 73% this quarter. Every one of those conversations is a business asking a person for something. The consent handshake, the scope and the receipt belong there natively, and a business that can prove it only ever received what it was granted is a business people answer.
What we would ask for
A pilot with a small set of business-messaging customers.
How we would know it worked
Reply rate and complaint rate against the existing baseline.
Compute at the edge
ProposalLong horizon, and only if it is real.
Meta guided to $130-145B of capex for 2026. A distributed grid of owner-operated supercomputers is not a replacement for a data centre and we will not pretend otherwise. It is a different cost curve for a specific class of workload: inference close to the person, on hardware somebody else already paid for.
What we would ask for
A technical conversation about which workloads, if any, actually fit.
How we would know it worked
Cost per inference at the edge versus in the data centre, measured honestly, including the cases where we lose.
Muse Spark 1.1, with the person holding the key.
Muse Spark 1.1 plans, calls tools, drives interfaces and delegates to subagents. That is not an assistant. That is an agent acting on somebody's behalf, and an agent acting on somebody's behalf needs their real context: their calendar, their money, their health, their family. The announcement is a model release and says nothing about where that context lives, what is retained, or what a person can take back. We are not reading anything into the silence. We are pointing out that the question is still open, and that it is the question that decides whether anyone hands the context over at all.
🤫 Private Agent One already answers it, and answers it in a way that costs Meta nothing to try. Bring your own API and bring your own compute are native capabilities, not integrations we would have to build: the person supplies the key, the quota is theirs, and the agent runs on hardware they own. The context never has to leave. The model gets called, not fed.
Meta gets
Usage, and a feedback loop from an agent doing real work for real people on their own keys. Plus a demonstration that the model is good enough to be trusted with a life, which is a different claim from a benchmark.
The person gets
Frontier capability without surrendering the substrate. Their key, their hardware, their receipts, and the ability to switch model the day a better one exists.
We get
To be judged on whether people actually trust it, which is the only test of a consent layer that means anything.
What we are not asking for.
- Not asking Meta to change its business model. Ads pay for everything Meta does and we think that is fine.
- Not asking for exclusivity, in either direction.
- Not asking Meta to adopt our protocol. If a better consent standard exists, we would rather use it.
- Not asking for an announcement. We would rather ship something small that works than sign something large that does not.
Nothing here is agreed. One thing is buildable today.
Meta is not a partner, an investor, or a customer, and no one at Meta has seen this before it was published. Workstream 00 needs nothing from Meta beyond an API that is already in public preview, which is why it is the one marked ready. Workstreams 01 through 04 are proposals and are marked as proposals. The consented signal layer they depend on is partly built: the consent protocol, the per-field grants and the receipts are real; the auction, the advertisers and the payouts are not.
Sources.
- Meta Q2 2026 results and earnings call transcript
- Introducing Muse Spark 1.1 and the Meta Model API
- Meta AI: GEM, the generative ads recommendation model
- Meta and EssilorLuxottica, AI glasses
Written from public information by people who admire the company and hold its stock. Mark Zuckerberg and Meta have not reviewed, endorsed, or agreed to any of it.