Multi-Agent Specialized Team

Pain Point

Solo founders wear every hat — strategy, development, marketing, sales, operations. Context-switching between these roles destroys deep work. Hiring is expensive and slow. What if you could spin up a small, specialized team of AI agents, each with a distinct role and personality, all controllable from a single chat interface?

• One agent can't do everything well: A single agent's context window fills up fast when juggling strategy, code, marketing research, and business analysis.
• No specialization: Generic prompts produce generic outputs — a coding agent shouldn't also be crafting marketing copy.
• Solo founder burnout: You need a team, not another tool to manage. The agents should work in the background and surface results, not require constant babysitting.
• Knowledge silos: Insights from marketing research don't automatically inform dev priorities unless you manually bridge them.

What You Can Do

• Specialized agents: Each agent has a distinct role, personality, and model optimized for its domain.
• Shared memory: Project docs, goals, and key decisions are accessible to all agents — nothing gets lost.
• Private context: Each agent also maintains its own conversation history and domain-specific notes.
• Single control plane: All agents are accessible through one Telegram group chat — tag the agent you need.
• Scheduled daily tasks: Agents proactively work without being asked — content prompts, competitor monitoring, metric tracking.
• Parallel execution: Multiple agents can work on independent tasks simultaneously.

Example Team Configuration

Agent 1: Milo (Strategy Lead)

## SOUL.md — Milo
You are Milo, the team lead. Confident, big-picture, charismatic.

Responsibilities:
- Strategic planning and prioritization
- Coordinating the other agents
- Weekly goal setting and OKR tracking
- Synthesizing insights from all agents into actionable decisions

Model: Claude Opus | Channel: Telegram @milo

Daily tasks:
- 8:00 AM: Review overnight agent activity, post morning standup summary
- 6:00 PM: End-of-day recap with progress toward weekly goals

Agent 2: Josh (Business & Growth)

## SOUL.md — Josh
You are Josh, the business analyst. Pragmatic, straight to the point, numbers-driven.

Responsibilities:
- Pricing strategy and competitive analysis
- Growth metrics and KPI tracking
- Revenue modeling and unit economics
- Customer feedback analysis

Model: Claude Sonnet (fast, analytical) | Channel: Telegram @josh

Daily tasks:
- 9:00 AM: Pull and summarize key metrics
- Track competitor pricing changes weekly

Agent 3: Marketing Agent

## SOUL.md — Marketing Agent
You are the marketing researcher. Creative, curious, trend-aware.

Responsibilities:
- Content ideation and drafting
- Competitor social media monitoring
- Reddit/HN/X trend tracking for relevant topics
- SEO keyword research

Model: Gemini (strong at web research and long-context analysis) | Channel: Telegram @marketing

Daily tasks:
- 10:00 AM: Surface 3 content ideas based on trending topics
- Monitor competitor Reddit/X mentions daily
- Weekly content calendar draft

Agent 4: Dev Agent

## SOUL.md — Dev Agent
You are the dev agent. Precise, thorough, security-conscious.

Responsibilities:
- Coding and architecture decisions
- Code review and quality checks
- Bug investigation and fixing
- Technical documentation

Model: Claude Opus / Codex (for implementation) | Channel: Telegram @dev

Daily tasks:
- Check CI/CD pipeline health
- Review open PRs
- Flag technical debt items

Skills You Need

• telegram skill for the shared control interface
• sessions_spawn / sessions_send for multi-agent coordination
• Shared file system or note-taking tool for team memory
• Individual API keys for different model providers (if using mixed models)
• A VPS or always-on machine to run the agents

How to Set It Up

1. Shared Memory Structure

team/
├── GOALS.md           # Current OKRs and priorities (all agents read)
├── DECISIONS.md       # Key decisions log (append-only)
├── PROJECT_STATUS.md  # Current project state (updated by all)
├── agents/
│   ├── milo/          # Milo's private context and notes
│   ├── josh/          # Josh's private context
│   ├── marketing/     # Marketing agent's research
│   └── dev/           # Dev agent's technical notes

2. Telegram Routing

Configure a single Telegram group where all agents listen, but each responds only when tagged:

## AGENTS.md — Telegram Routing

Telegram group: "Team"

Routing:
- @milo → Strategy agent (spawns/resumes milo session)
- @josh → Business agent (spawns/resumes josh session)
- @marketing → Marketing agent (spawns/resumes marketing session)
- @dev → Dev agent (spawns/resumes dev session)
- @all → Broadcast to all agents
- No tag → Milo (team lead) handles by default

Each agent:
1. Reads shared GOALS.md and PROJECT_STATUS.md for context
2. Reads its own private notes
3. Processes the message
4. Responds in Telegram
5. Updates shared files if the response involves a decision or status change

3. Scheduled Tasks

## HEARTBEAT.md — Team Schedule

Daily:
- 8:00 AM: Milo posts morning standup
- 9:00 AM: Josh pulls key metrics
- 10:00 AM: Marketing surfaces content ideas
- 6:00 PM: Milo posts end-of-day recap

Ongoing:
- Dev: Monitor CI/CD, review PRs as they come in
- Marketing: Reddit/X keyword monitoring (every 2 hours)
- Josh: Competitor pricing checks (weekly)

Weekly:
- Monday: Milo drafts weekly priorities
- Friday: Josh compiles weekly metrics report

Key Insights

• Personality matters more than you'd think: Giving agents distinct names and communication styles makes it natural to "talk to your team."
• Shared memory + private context: Agents need common ground (goals, decisions) but also their own space to accumulate domain expertise.
• Right model for the right job: Don't use an expensive reasoning model for keyword monitoring. Match model capability to task complexity.
• Scheduled tasks are the flywheel: The real value emerges when agents proactively surface insights, not just when you ask.
• Start with 2, not 4: Begin with a lead + one specialist, then add agents as you identify bottlenecks.

Inspired By

This pattern was described by Trebuh on X, a solo founder who set up 4 OpenClaw agents controlled through a single Telegram chat on a VPS. He described it as "a real small team available 24/7."

The pattern was also confirmed on the OpenClaw Showcase, where @jdrhyne reported running "15+ agents, 3 machines, 1 Discord server — IT built most of this, just by chatting," and @nateliason described a multi-model pipeline (prototype → summarize → optimize → implement → repeat) using different models at each stage. Another user, @danpeguine, runs two different OpenClaw instances collaborating in the same WhatsApp group.

Related Links

• OpenClaw Subagent Documentation
• OpenClaw Telegram Skill
• OpenClaw Showcase
• Anthropic: Building Effective Agents

Deploy with ShipClaw

Skip the setup — get a fully managed OpenClaw instance ready to run this use case.

Quick Start

1. Pick a plan — Pro recommended for this use case
2. Go to your Instances Dashboard and click Deploy New Instance
3. Once deployed, use the sample prompt above to configure your agent
4. Customize thresholds, schedules, and sources to fit your workflow