# Multi-Agent Specialized Team (Solo Founder Setup) 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? 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 — 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 — 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) ```text ## 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 (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) ```text ## 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 (responds to @josh) Daily tasks: - 9:00 AM: Pull and summarize key metrics - Track competitor pricing changes weekly ``` ### Agent 3: Marketing Agent ```text ## 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 (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 ```text ## 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 (responds to @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 ```text 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: ```text ## 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 ```text ## HEARTBEAT.md — 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 — 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](https://x.com/iamtrebuh/status/2011260468975771862), a solo founder who set up 4 OpenClaw agents — Milo (strategy lead), Josh (business), a marketing agent, and a dev agent — 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](https://openclaw.ai/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](https://github.com/openclaw/openclaw) - [OpenClaw Telegram Skill](https://github.com/openclaw/openclaw) - [OpenClaw Showcase](https://openclaw.ai/showcase) - [Anthropic: Building Effective Agents](https://www.anthropic.com/research/building-effective-agents)