For the latest episode of My Data Guest, I sat down with Antonio Malia, a dear friend since our Pisa days, now founder of Seltz, a startup rethinking web search from the ground up. Not for humans this time. For machines.

The core problem

Google, Bing, and every search engine we grew up with were built around a simple human loop: type a query, scan snippets, click a link, read the page. Antonio’s insight is that this entire interface breaks down for an LLM. A snippet is, in his words, a movie trailer. It hints at the answer but doesn’t give it. So the model either guesses or burns tokens and seconds fetching the full page. Multiply that by every agentic loop, and you get slow, expensive, unreliable agents.

Seltz’s bet: build the crawler, index, retrieval, and ranking stack from scratch, optimized for a completely different reward function: one where the “user” is a language model, not a person.

Why it matters: latency and trust

Two things stood out from the conversation:

* Latency compounds. If an agent can get a search result back in 100ms instead of a second, it can run ten iterations in the time a traditional engine takes for one. That’s the difference between a shallow answer and genuinely complex task completion.

* Trust is the real target. Antonio framed it sharply: AGI, to him, is the point where we trust a machine’s completed process more than we’d trust another person’s. Web search is just the first, most obvious place models need reliable, constantly-updated access to the world. No more “airplane mode” after training cutoff.

Full stack, small team, Rust

Seltz owns everything: crawler, data connectors, knowledge pipeline, ranking. Building in Rust was a pragmatic call: efficiency, memory safety, and (notably) a much larger, more excited talent pool than C++ offers today. The team, partly ex-Amazon, partly IR-research veterans, is explicitly modeled on the “flat, high-trust, senior-heavy” structure Antonio admired at places like Netflix.

On coding agents

Antonio’s take on AI coding tools was refreshingly unfussy: they’re a boost only if you already know exactly what needs to be done. Used to offload thinking, they slow you down. Used to execute a decision you’ve already made, and to be challenged when they propose something better, they’re a genuine multiplier. Design decisions stay human.

What’s next

The next six months are about making Seltz’s product the main driver of value for customers who integrate it, validating the underlying research day by day rather than chasing a big splashy release. If you want to try it yourself: sign up in the console and connect via API/MCP, or just book a call with the team.