An autonomous ad system, starting with Ghost Inspector
You asked about Ghost Inspector, and it made me realise where an approach I've already been working towards fits cleanly. The system would automatically create and test ads and landing pages, launch experiments, measure real customer outcomes, and choose the next test on its own. Think of Andrej Karpathy's autoresearch idea, but aimed at distribution. After setup, it runs without anyone sitting on it.
I'd like to explore how this could work for SureSwift, starting with Ghost Inspector, then reusing it across the other businesses. I'm showing you this because to me it seems worth discussing.
What the system does, in a nutshell
For Ghost Inspector, I'm proposing an autonomous distribution system. It creates/tests ad variants and landing page variants, launches experiments, measures customer and business outcomes, and picks the next experiment on its own. The idea traces back to Andrej Karpathy's autoresearch approach, applied here to distribution rather than research.
The cycle is simple: make a change, compare it against the current baseline, measure the result, keep improvements, repeat. Nobody manually manages each variation.
A complete path to a customer.
Cold email, X, Google, Meta, YouTube and TikTok are possible starting points. We would pick one based on Ghost Inspector’s current customers, acquisition data and priorities.
For this example, imagine a Meta ad leading to a Ghost Inspector landing page. The system coordinates the ad and page so the message people click on matches the experience they land on.
The AI generates variations of the creative, copy and landing page, checks them against the product, launches the test, and measures the result. Each experiment compares a specific change, or a defined combination, with the current version.
The same approach could also generate and test UGC style video ads, widening the creative formats available alongside images, messaging and landing pages.
Autonomous after launch
Before anything goes live, we agree on three things: the customer outcome we're optimizing for, the spending cap, and what the system is allowed to change on its own.
Once running, the system selects the next experiment, builds the variations, and launches them without anyone stepping in for each one. Every test keeps the current version untouched as a baseline. Improvements get applied; wins, failures and inconclusive results all get recorded so the next choice is smarter than the last.
We track trial activity, paying customers and continued product use from day one. Trials give fast signals. Paying and retained customers show whether a change actually holds up over time.
My own experience
I've personally built and set up systems with AI before launch, and they went on to run autonomously and improve over time. That's the working pattern I'm bringing to Ghost Inspector.
For my dad’s paving company, I ran Google Ads combined with landing page optimization. The system guided keyword selection and strategy as well as the page optimization itself. We observed page speed improvements, and the landing page analytics drove copy tests. Keywords were optimized toward qualified lead opportunities, not treating every click or form fill as success.
Tested on cold email as well, it picked templates and improved the prompts used by agents writing the personalized portions. That connected with the self improving landing page on the other end. The result was increased landing page traffic and more meetings booked.
My earlier Meta advertising work was manual testing, not deployment of this autonomous system. But I see strong potential for it on Meta and X specifically, because creative, copy, headlines, captions and pages together give a lot of variables to experiment on.
The proposed next application is Ghost Inspector, leading toward a reusable system across the SureSwift portfolio.
Starting with Ghost Inspector
The first step is getting a clear picture of how Ghost Inspector acquires customers today. What experiments have been run, what worked, what didn't, and what the current numbers look like. From that, we'd define one useful first experiment together: a specific desired outcome, the current baseline to beat, how we track results, a budget, and what the system is allowed to change on its own.
I'd build and run that experiment alongside the team, using the process to develop the larger system in the right direction.
Beyond Ghost Inspector, I'm keen to explore working with you and SureSwift on the broader opportunity. The exact arrangement is still open for discussion, but starting here feels like the natural way in.
Cheaper than an agency
Once it's set up, the system handles the repetitive work: making variations, running experiments, analyzing results, applying what worked. That means substantially less ongoing human production, coordination and reporting.
The performance case is that ads, copy and the landing page get improved as one connected process. The system goes straight from a result to the next test, carrying forward what earlier experiments taught it. We optimize it towards desired outcomes, not clicks or form fills.
I'm confident this beats typical agency economics, not as a guarantee but as a reasonable expectation given how the work is structured.
As a result of the operation costs being substantially lower it also means more money spent on ADs and as a result more conversions as a whole.
Then the rest of SureSwift
Once Ghost Inspector is running, the same underlying system can serve the other SureSwift businesses. Each has its own customers, objectives, economics and experiments, so nothing gets copy pasted blindly.
What does carry over is the method: how to choose the next experiment, how to create variants, how to evaluate results. That forms a shared playbook. New businesses start with those learned methods and then test and adapt them locally to their own context.
Each business that plugs in improves the reusable system for the ones that follow and those already running.
The next conversation
I'd like to get on a call and hear how you're thinking about this across SureSwift. We can talk through the idea, where it might be useful, and whether there's an opportunity to work together.
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