Solo founders wear every hat โ 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?
This use case sets up multiple OpenClaw agents as a coordinated team, each specialized in a domain, communicating through shared memory and controlled via Telegram.
Pain Point
- 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 โ 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 It Does
- 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 โ 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 โ tag the agent you need
- Scheduled daily tasks: Agents proactively work without being asked โ 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 โ 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 (responds to @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 โ 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 (responds to @josh)
Daily tasks:
- 9:00 AM: Pull and summarize key metrics
- Track competitor pricing changes weekly
Agent 3: Marketing Agent
## SOUL.md โ 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 (responds to @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 โ 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 (responds to @dev)
Daily tasks:
- Check CI/CD pipeline health
- Review open PRs
- Flag technical debt items
Skills You Need
telegramskill for the shared control interfacesessions_spawn/sessions_sendfor 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/
โโโ GOALS.md # Current OKRs and priorities (all agents read)
โโโ DECISIONS.md # Key decisions log (append-only)
โโโ PROJECT_STATUS.md # Current project state (updated by all)
โโโ agents/
โ โโโ milo/ # Milo's private context and notes
โ โโโ josh/ # Josh's private context
โ โโโ marketing/ # Marketing agent's research
โ โโโ 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 โ Telegram Routing
Telegram group: "Team"
Routing:
- @milo โ Strategy agent (spawns/resumes milo session)
- @josh โ Business agent (spawns/resumes josh session)
- @marketing โ Marketing agent (spawns/resumes marketing session)
- @dev โ Dev agent (spawns/resumes dev session)
- @all โ Broadcast to all agents
- No tag โ 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 โ Team Schedule
Daily:
- 8:00 AM: Milo posts morning standup (aggregates overnight agent activity)
- 9:00 AM: Josh pulls key metrics
- 10:00 AM: Marketing surfaces content ideas from trending topics
- 6:00 PM: Milo posts end-of-day recap
Ongoing:
- Dev: Monitor CI/CD health, 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 (input from all agents)
- 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" rather than wrestle with a generic AI
- Shared memory + private context: The combination is critical โ 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 โ Milo (strategy lead), Josh (business), a marketing agent, and a dev agent โ all controlled through a single Telegram chat on a VPS. Each agent has its own personality, model, and scheduled tasks, while sharing project memory. 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 โ IT built most of this, just by chatting," and @nateliason described a multi-model pipeline (prototype โ summarize โ optimize โ implement โ repeat) using different models at each stage. Another user, @danpeguine, runs two different OpenClaw instances collaborating in the same WhatsApp group.