Why I'm building this

The problem

She is not being paid to be the router. She is being paid to think.

Every week, the same thing happens in roughly three hundred performance marketing agencies in North America.

A Head of Strategy spends Sunday evening pulling context together for a Monday review — last week's creative tests, the CFO's revised CAC target, the category research that never quite made it into the brief, the three accounts whose margin is quietly slipping.

By Monday at ten, she is the human router between seven disconnected systems: the attribution dashboard that lost a week of conversions on a platform update, the generic AI that keeps confidently making up numbers, the Retool internal tool that broke again, the creative QA spreadsheet a junior strategist maintains by hand, the offer doc that lives in a shared drive nobody can find, the pitch deck from three quarters ago that still contains the only coherent statement of what the agency actually does, and the founder-CEO's inbox.

She is not being paid to be the router. She is being paid to think. But the routing takes the hours the thinking needs, and the thinking keeps getting compressed into the fifteen minutes between meetings, and the compounded judgment that makes her a seven-figure strategist is leaking out of the agency every week, one reset prompt at a time.

The CEO sees a different face of the same problem.

Scope creep eating the margin he priced for. Creative fatigue he finds out about two weeks late. A feast-or-famine pipeline that makes payroll a monthly exercise in faith. Delegation failure — he is still the bottleneck on every decision that actually moves revenue.

And the growing, private suspicion that every tool he has bought in the last three years has added friction, not removed it.

I wrote this page for those two readers. If the pain I just named is the pain you are in, the rest of this is for you.

How I got here

I started because I had read enough to see a shape in the category that nobody I could find was building for.

I am going to be direct about my prior experience because this is exactly the place the trust is won or lost.

I did not come out of a FAANG marketing org. I did not run a nine-figure media budget. I have not sold a company before.

Before this, I was a novice e-commerce dropshipper. I helped a few friends with their ads. I read a lot. I got some things right and more things wrong.

The main thing I learned is that the honest description of my track record is the one that lets me build credibility over time instead of burning it on day one.

What I did do — what this entire product is built on — is research.

I spent a long run reading three things at a level of depth I had never read anything at before.

First, the operational reality of performance marketing agencies: the 9,688-interview PMBD corpus, the daily workflow patterns, the weekly review cadences, the quarterly financial panics.

Second, the marketing science the senior strategists in that world already trust: Sharp, Romaniuk, Ehrenberg-Bass, Cialdini, Andjelic, Cole. I read these authors because the audience I was designing for reads them, and because any tool built for that audience that is not calibrated against their frameworks is, in their eyes, another toy.

Third, the category itself. I read every "AI for agencies" product I could get a demo of. I read the complaints in the private Slack communities. I read the teardowns in the paid newsletters. I read where the current generation of tools breaks.

And the pattern underneath the noise was this: the current tools reset.

Every prompt resets the context. Every new client onboards from zero. Every model update drops the calibration on the floor.

The tools that do not reset — the enterprise platforms — train one shared model on six hundred agencies' strategy work and call it personalization. Neither pattern compounds.

So I started building something that compounds. I did not start because I had an operator's pedigree. I started because I had read enough to see a shape in the category that nobody I could find was building for. That is the honest version of "how I got here."

What I'm fighting

The structural problem is more interesting than any individual product. Naming-and-shaming is the cheap move in a market already drowning in cheap moves.

I am not fighting Hyros. I am not fighting Triple Whale. I am not fighting any specific competitor by name, because the structural problem is more interesting than any individual product, and because naming-and-shaming is the cheap move in a market already drowning in cheap moves.

The first enemy is structural.

The dominant software pattern in this category takes your data, trains a model nobody else can see, and then charges you monthly for access to the model you helped calibrate.

If you churn, the model stays. If the vendor pivots, the model stays. If the vendor gets acquired, your calibration becomes someone else's competitive moat.

This is a pattern every agency has already lived through with attribution platforms; the Digital Twin category is about to run the same play at a higher price point, and the people I respect in the space are already bracing for it.

The second enemy is credibility erosion.

The "AI for agencies" market is in the middle of a reputation meltdown, and the meltdown is being caused by products that overpromise what generic models can actually do.

When a vendor tells a Head of Strategy that "our AI writes briefs as well as your senior strategist," she tests it on her worst account and watches it fail. After that test every sentence from that vendor reads as marketing hallucination.

The cost is not just the one lost deal — it is the next three deals, because the BS filter at Stage 3 sophistication does not reset.

I am fighting both of those patterns by being very specific about what the mechanism does, what data it is calibrated against, and what it does not do. Transparency is not a brand promise; it is the only strategy that survives contact with a smart buyer.

What I'm building

Compounding is the whole point: the longer you use it, the more your twin knows, and the knowledge stays yours.

Khorvad is a Digital Twin — and because that name does more work than it should until it is defined, let me define it.

A Digital Twin is a calibrated intelligence layer trained on your specific agency's strategic judgment, client context, and creative history.

Calibrated means the model's outputs are shaped by your data rather than the generic internet. Intelligence layer means it sits between your team and the generic AI market, turning every strategist's decision into compounding context rather than a reset prompt.

Compounding is the whole point: the longer you use it, the more your twin knows, and the knowledge stays yours.

That mechanism is backed by three guarantees, and I want to be honest about the status of each.

The first is the Parallax Test. This is a free, founder-run session where you bring a live campaign or a brief your strategist is writing this week, and we pattern-match it against a calibrated twin in front of you. The session is booked, the format is real, and the outputs are yours to walk away with whether or not you buy anything afterwards. This one is shipping.

The second is the Adoption Guarantee. The intent is simple: if your team does not actually use the twin in the first ninety days, you do not pay for it. The legal and operational version of that guarantee is in active design with the product-design workstream; the principle is locked, the enforceable contract text is in progress.

The third is the Portability Covenant. You keep your twin. You keep your data. You keep every output. Even if you leave, even if Khorvad does not ship, even if I get hit by a bus. The binding legal version of this is in review with outside counsel right now, and the finalized text will ship on /portability-covenant before any paying customer is onboarded. The intent, though, is the shape of the guarantee, and the intent is not negotiable.

The product is early. The research behind it is deep. The guarantees are the structural proof that the builder is not building to extract — the builder is building to be useful long enough to be trusted.

The ask

If it is not useful, I will tell you directly — and you walk away owing nothing.

If the problem I named in the first section is the problem you are in, book the Stump Session. Bring the question your best strategist cannot get a generic model to answer. Bring the brief that is still open on your desk. Bring the account where the margin is slipping and you cannot tell why.

If it is not useful, I will tell you directly, and you walk away owing nothing — no follow-up sequence, no pitch deck, no "nurture" email chain. The session is a test of whether the mechanism can actually help your specific operation. If it cannot, we both learn that quickly and move on.