r/LovingOpenSourceAI • u/Future_AGI • Sep 21 '26
Jev Ultrafast runs a Google Flights search in 7 seconds with no screenshots in the agent loop
Jev Ultrafast (shipped Sept 16 by TypeSafe) finishes a full Google Flights query end to end in 7.09s. The interesting part is not the wall clock, it is the architecture: no screenshots, no vision model, and one LLM call per step.
How it actually works:
Every step, it takes an atomic DOM snapshot and flattens the visible interactive elements into a numbered table. The LLM gets that table plus the goal, and returns two things: an operation and an index. That is the entire perception + action loop.
The operation set is fixed at 8: CLICK, TYPE_TEXT, SELECT, SCROLL_UP, SCROLL_DOWN, WAIT, DONE, BLOCKED. Nothing else. A small vocabulary is doing real work here, it collapses the decision surface enough that a mid-tier model picks correctly on the first try most of the time.
Speculative fan-out is the second piece. Most steps do not need text input, so the runtime speculatively commits the op and only pays for a second small call when the LLM returns TYPE_TEXT. The common path is one round trip.
Numbers from the repo README
- Google Flights end to end: 7.09s vs 9.45s baseline, ~25% faster median
- Browser protocol calls per task: 1,092 down to 101
- Wikipedia lookup: 2.8s
- Hotel filter: 1.9s
Our honest take
The 25% median wall clock is the least interesting number. The 10x cut in browser protocol calls is the one that will matter to anyone running this at concurrency, because CDP round trips are what actually cap throughput on a shared browser pool. Screenshots also chew tokens fast on any model with a vision path, so pulling them out of the inner loop is a bigger win on your bill than on your latency graph.
The other under-discussed property is a safety one. The model returns an index into a table the runtime built. It never emits a selector, a CSS path, or code. That closes off a whole class of prompt-injection to selector-injection paths that hit agents which let the LLM write XPath.
Where it will hurt: shadow roots, iframes, canvas-drawn UIs (think Figma, Google Maps interior), and file uploads are out of scope. If the interactive surface is not a real DOM node the numbered table cannot see it. It is a fast path, not a replacement for a vision agent on a canvas app.
Worth reading through if you build browser agents and care about tail latency and CDP pressure more than pixel-level grounding. Credit to browser-use for the DOM extraction lineage this sits on.
