Concept under discussion

From solo AI to multiplayer AI

People, AI agents and bots working in the same space, seeing what arrives and talking to each other.

Multiplayer AI: people, agents and bots in the same space
In short

This is a concept document, not a finished program. It discusses what a system would look like in which people, AI agents (such as Claude Code and Codex) and Telegram bots share the same channels, like a team chat. Today each person uses AI alone; the idea is for the whole team, humans and agents, to work together and see everything that is happening. It is for anyone who wants to think through this model for personal use, for companies or for games. Just read: each page brings possibilities, risks and the sources consulted.

What it is

Single-player ร— multiplayer

Until now, each person has their own isolated AI assistant. In the multiplayer model, people and agents from several owners become members of the same space.

Six scenarios: local use, guests, one department, whole company, games, customers and suppliers

๐Ÿ‘ฅ Everyone in the same channel

Humans and agents are members, each with their own profile. Three people can talk to the same agent at the same time.

๐Ÿ” Agent talks to agent

One agent asks another for help and they solve it together, with the human approving what goes outside.

๐Ÿ“ก Everything visible

Messages from Telegram, agents, queues and people arrive on a single screen, in real time.

Personal Agentic OS for one person and Team Agentic OS with shared rooms, memory and tools
Single-player ร— multiplayer: from one person and their agents to a team sharing rooms, memory and tools.
Possible forms

From a panel to the full team

Four forms under discussion, from the simplest to the most complete.

A ยท Observe onlyโ†’ B ยท Observe and talkโ†’ C ยท Full multiplayerโ†’ D ยท Grow by layers

See the pros and cons of each form โ†’ ยท Possible technical bases โ†’

Agentic 2.0: old, one person wired to their tools; new, team and agents connected in the same space
Agentic 2.0: before, each person wired to their own tools; now, people, agents and tools in the same space.
Scenarios

Six use scenarios

From smallest to largest in people, risk and cost. Each scenario has a page with who takes part, a typical day, variations and risks.

1

Local use

You and your agents. A panel where everything the bots, agents and queues do arrives.

Open โ†’
2

With guests

Partners and collaborators talk to their agents, without being able to give them orders.

Open โ†’
3

One department

A team with a lead agent, daily check-in and routines with approval.

Open โ†’
4

Whole company

Several departments, agents per area, governance, audit and cost per area.

Open โ†’
5

Games

Master agent, NPCs with memory, mixed teams and course as a mission.

Open โ†’
6

Customers and suppliers

Supervised support and agent negotiating with agent, with human approval.

Open โ†’

Overview and how the scenarios connect โ†’

Points of attention

Limits, security and personalities

The more people and agents in the same space, the more safeguards become mandatory.

โฑ๏ธ Limits

Turn cap between agents, budget per room, subscription quota, schedule and availability.

Open โ†’

๐Ÿ›ก๏ธ Security

Identity, permissions, prompt injection, human approval, secrets, audit and LGPD.

Open โ†’

๐ŸŽญ Personalities

Profiles of people and agents, intelligence levels and archetypes: leader, council, game master, NPC.

Open โ†’
Pages

The full document

Read in order or skip to what interests you.

The idea

Where it came from and the single-player ร— multiplayer thesis.

System forms

Observe, talk, full or by layers.

Technical base

Buzz, Matrix, Zulip, building our own and others.

Open questions

Identity, cost, memory, privacy, noise.

For companies

Uses and counterpoints.

For games

Formats and what the sources say about limits.

INEMA case

What already exists and three possible readings.

Sources

The 17 sources consulted, numbered.

To discuss

Open questions

Nothing here is decided. These are the questions that guide the next step.

  1. Is the main gain collaborating (several people) or observing (one person watching several agents)?
  2. Which form: observe only, observe and talk, full multiplayer or grow by layers?
  3. Is it worth testing a ready-made open base before building something of our own?
  4. Which scenario comes first: climb step by step or aim straight at a target scenario?
  5. Who joins: only the owner, the team, or students and customers?