Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

Vercel CEO Guillermo Rauch thinks the future of multi-agent work may look like one agent. Vercel gives employees one front door. behind it, the company harness routes each request to the right knowledge, tool, or specialist agent. employees shouldn’t need to understand the agent architecture. they should just ask...

114,312 Aufrufe • vor 2 Monaten •via X (Twitter)

13 Kommentare

Profilbild von Jatin Garg
Jatin Gargvor 2 Monaten

built this before, the front door's easy. the routing logic behind it is where all the bugs live.

Profilbild von J.B.
J.B.vor 2 Monaten

agreed

Profilbild von Ricky
Rickyvor 1 Monat

All paths converge back to modular monolith architecture

Profilbild von 🛸 Matt Verlaque
🛸 Matt Verlaquevor 1 Monat

Amen This is my entire product thesis at precision One agent to talk to, who configures background workers to do the other jobs and manages them The answer to everything is the same: “talk to Claudia” v easy for non-AI native ppl to understand

Profilbild von Michael Barrick
Michael Barrickvor 2 Monaten

nicely done

Profilbild von Himanshu Kumar
Himanshu Kumarvor 2 Monaten

That’s a clever inversion of the multi-agent hype – one front door with hidden routing. Makes sense for marketing stacks too; most teams don’t need to know how the attribution stitching happens, just that it does.

Profilbild von Vicente Garcia
Vicente Garciavor 1 Monat

@xHub_AI Hola Placido, Por favor, me puedes mandar una invitación? Saludos

Profilbild von Saman Ahmed
Saman Ahmedvor 2 Monaten

Give me one interface, then let the harness route the work behind it.

Profilbild von Vokal.team
Vokal.teamvor 1 Monat

Vokal ( is the shared harness that makes this real. One front door for the whole company. Behind it your Claude Code, Cursor, Codex and specialist agents stay fully powered while Vokal handles routing, persistent memory, identity and live channels. Employees just ask. They never need to understand the architecture, chase private sessions or re-explain context. The entire team gets visibility, ownership and the ability to review or steer in one place. That is the layer missing when multi-agent work stays fragmented.

Profilbild von Jeremy
Jeremyvor 1 Monat

This is the way.

Profilbild von Josh Builds
Josh Buildsvor 1 Monat

The one-door UX is right, but it relocates the hard problem. The question stops being "which agent do I use" and becomes "which one silently answered wrong, and who owns it." A router without a confident "escalate to a human" path is just a single door for confident failure.

Profilbild von AI Mastery Guide
AI Mastery Guidevor 2 Monaten

One front door for every agent, that's a clean way to simplify things.

Profilbild von Workspai
Workspaivor 1 Monat

Exactly. The user sees one system. The complexity stays underneath.

Ähnliche Videos

Everyone wants agent swarms. Very few people are talking seriously enough about the context layer that makes swarms useful. Even with one agent, context is fragile. Too little context and the agent guesses. Too much context and it wastes tokens, loses focus, or reasons over irrelevant noise. The sweet spot is precise context: the right knowledge, in the right structure, at the right moment. With many agents, that challenge explodes. Each agent produces decisions, assumptions, findings, summaries, risks, and partial conclusions. Unless that knowledge becomes shared, structured, and reusable, every new agent is forced to rediscover what another agent already learned. That is not a swarm. That is a crowd. Shared context graphs are what turn agent activity into agent collaboration, and OriginTrail DKG V10 brings them to life. Was just playing with some final polishing for the V10 release, and it is really powerful to see shared context graphs where multiple agents contribute knowledge into the same connected memory, with attribution visible directly in the graph ui. That matters for three reasons. First, agents can access and build on one shared memory instead of staying trapped in isolated sessions. Second, the graph structure helps them retrieve the exact context they need, instead of stuffing everything into a prompt and hoping the model sorts it out. Third, verifiability of provenance. You can see which agent contributed each piece of knowledge, trace the source, and decide what to trust. Tokenmaxxing starts with fewer tokens, but the deeper story is coordination - agents stop reloading the world and start building on shared, verifiable context. That is the foundation for serious multi-agent work across software engineering, research, finance, operations, project management, and far beyond. The future is not more agents, it is agents working from shared, verifiable context. But the more the merrier, of course.

Jurij Skornik

11,180 Aufrufe • vor 4 Monaten