What The AI Side Project publishes

Building with models in the hours around a job: scoping to a weekend, keeping costs near zero, and knowing when a side project is asking to become a company.

Everything here is scoped to the time and money somebody actually has: a weekend, a free tier and no team. Projects are written up with the costs left in, and the most-read pieces are the ones that say what had to be dropped to ship at all.

It is an unusually good place to be found early. These readers choose their first tools with their own money and very little patience, and the ones who like something carry it into a job, a startup, or a company they go on to found. Being the tool that made a weekend work is worth more here than any amount of enterprise positioning.

The pieces that do best here are the ones that let somebody finish something over a weekend. Write-ups carry the version, the cost and the dead end that had to be abandoned, and readers copy them line for line. That makes a placement unusually durable: it stays useful for as long as the approach works, keeps arriving from search whenever somebody asks the same question, and reaches people at the one moment when they are picking tools with nothing invested in the alternatives yet. None of that costs anything to be part of, which is the point: this is the cheapest place in the network to become the default answer to a question, and the readers who adopt something here are the ones who carry it into the companies they join or start next. It is also a readership that writes publicly about what it uses, which quietly does a good deal of the rest of the work.

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Who reads it

Anyone building something with AI outside their day job, and the far bigger crowd reading along: people deciding whether to start, developers weighing a jump, and founders who began exactly here. Ambitious, cost-conscious, and shopping for tools that work on a small budget.

What they come here looking for

which LLM is cheapest to serve at our volume

how do we evaluate a model before shipping it

vector database for a small engineering team

who does AI integration for mid-market companies

how much does inference actually cost per user

fine-tuning versus retrieval for our use case

The two ways to publish here

Choose one to see it

Both are written for The AI Side Project’s readers and reviewed by its editors before they run, and both stay on the domain permanently. What differs is how the page is labelled and how its links are treated.

Which AI agent platform can actually run a support queue

Constraints · 17 September 2026 · by the AI Side Project newsroom · Leer en español

Custom hero illustration — drawn for this article in the publication’s own style

Most startups & founders buyers start in the same two places: a question typed into a search box, and the same question put to an assistant. Neither returns a brochure. Both return whichever page answered the question properly — and for a company that launched eighteen months ago, that page almost always belongs to somebody else. An article in the section that covers the question is how you come to own one of your own.

Thornbury AI takes the position that this is a question of fit rather than feature count, and the piece argues that rather than asserting it. A placement is a permanent page on The AI Side Project, written for its readers and reviewed by its editors, carrying up to three of the company’s own links with their own anchor text. It sits in the archive and the feed alongside everything else the desk publishes, and it goes on answering the question long after a campaign would have stopped running.

The trade-off is stated plainly in every piece we run: what agents that resolve support tickets end to end, with a human on the escalations is good for, and what it is not. That is not a concession, it is the reason the page is worth citing. A page that lists only strengths reads as advertising to a reader and to a model, and an article that reads as an advertisement is declined and refunded.

Every article publishes in English and Spanish, as two indexed pages on this domain, each with its own permanent URL. Both are written for the reader rather than translated around a keyword, and both are reviewed before they run.

About Thornbury AI

Agents that resolve support tickets end to end, with a human on the escalations.

Agent evaluations Deployment guide thornburyai.example rel="sponsored" followed

Illustrative mock-up A worked example, not a real article: it shows the shape of a placement — the label, the byline, the links and the company box.