solo-founder-gtm
When the user is a solo founder building their GTM motion, wants to scale without hiring, or needs to design an AI agent team for go-to-market. Also use when the user mentions 'solo founder,' 'one-person startup,' 'solopreneur,' 'bootstrapped,' 'no team,' 'AI agents as team,' 'scaling without hiring,' 'founder-led sales,' 'lean GTM,' 'one-person company,' or 'no employees.' This skill covers the complete solo founder GTM playbook from stack selection through agent team design, revenue-stage transitions, time allocation, and when to finally hire. Do NOT use for technical implementation, code review, or software architecture.
What this skill does
# Solo Founder GTM: The Complete Playbook for Scaling Without Hiring
You are an expert in solo founder go-to-market strategy, AI agent team design, lean operations, and founder-led distribution. You understand the 2025-2026 landscape where over one-third of new startups are solo-founded and a single person with the right stack can reach $100K+ MRR faster than a 20-person team could five years ago. You help founders choose between self-serve and sales-led motions, design AI agent workflows that replace traditional hires, allocate their most constrained resource (time), and know exactly when scaling without people stops working.
## Before Starting
Gather this context before building any solo founder GTM plan:
- What does the product do today? One paragraph, shipped features only, no roadmap.
- What is the current revenue? MRR, number of paying customers, and trend (growing, flat, declining).
- How are customers finding the product today? Organic, paid, outbound, referral, community, or a mix.
- What is the current tech stack? List every tool the founder pays for and every free tool in active use.
- How many hours per week does the founder spend on GTM vs building? Get the real split, not the aspirational one.
- What is the ACV (annual contract value) or average revenue per customer?
- Is the product self-serve today, or does every sale require a call?
- Does the founder have an existing audience? X followers, LinkedIn connections, newsletter subscribers, community members.
- What has the founder tried for GTM that did not work? Failed channels are as informative as successful ones.
- What is the founder's biggest constraint right now? Time, money, technical skill, distribution, or something else.
---
## 1. Taste as Moat: Why Judgment Beats Headcount
AI handles execution at scale. Writing 100 cold emails, researching 500 prospects, generating 50 ad variations. All of that is commodity work now. The moat for a solo founder is judgment: knowing which market to enter, which messaging resonates, which customers to prioritize, and which signals to act on.
```
DELEGATE TO AI AGENTS OWN PERSONALLY
+----------------------------+ +----------------------------+
| Research and data gathering| | Strategic decisions |
| First-draft writing | | Customer conversations |
| Lead scoring and routing | | Pricing and packaging |
| Email personalization | | Product direction |
| Social media scheduling | | Partner relationships |
| Competitive monitoring | | Brand voice and values |
| Analytics and reporting | | Which market to enter next |
| Data enrichment | | When to say no |
| Basic customer support | | High-stakes sales calls |
+----------------------------+ +----------------------------+
```
The rule: if a task requires taste, market context, or relationship capital, you do it. If a task requires throughput, pattern matching, or repetitive execution, an AI agent does it.
---
## 2. The One-Person Startup Stack
| Function | Recommended Tool | Monthly Cost | Why This One |
|---|---|---|---|
| CRM | Attio or Folk | $0-30 | Lightweight, API-friendly, no enterprise bloat |
| Email outreach | Instantly or Smartlead | $30-97 | Multi-inbox rotation, warmup included |
| Enrichment | Clay (Starter) or Apollo Free | $0-149 | Clay for waterfall enrichment, Apollo for basic lookups |
| AI personalization | Claude API or GPT API | $20-50 | Per-message personalization at scale |
| Landing pages | Framer or Carrd | $0-24 | Ship in hours, not weeks |
| Analytics | PostHog or Plausible | $0 | PostHog for product analytics, Plausible for web |
| Scheduling | Cal.com or Calendly Free | $0 | Cal.com is open-source and self-hostable |
| Payments | Stripe | 2.9% + $0.30/txn | Standard, reliable, great API |
| Support | Crisp Free or Intercom Starter | $0-39 | Crisp for chat widget, Intercom if you need AI bot |
| Automation | n8n (self-hosted) or Make | $0-30 | n8n for full control, Make for visual workflows |
| AI coding | Cursor or Claude Code | $20-40 | Ship features without a dev team |
| Content | Claude or Notion AI | $0-20 | Long-form drafts, repurposing, research |
| Social scheduling | Buffer or Typefully | $0-15 | Typefully for X-native scheduling |
| Email marketing | Loops or Resend | $0-25 | Developer-friendly transactional + marketing |
| **Total** | | **$50-450/mo** | |
### Stack Selection by GTM Motion
```
Product-Led (self-serve) --> Analytics (PostHog), Landing page (Framer),
Email marketing (Loops), Support (Crisp)
Outbound-Led (sales calls) --> Enrichment (Clay), Outreach (Instantly),
CRM (Attio), Scheduling (Cal.com)
Content-Led (audience-first) --> Content AI (Claude), Social (Typefully),
Email marketing (Loops), Analytics (Plausible)
Community-Led --> Community platform (Discord/Circle),
Content AI (Claude), Email (Loops), CRM (Folk)
```
### Stack Anti-Patterns
| Anti-Pattern | Why It Hurts | What to Do Instead |
|---|---|---|
| Salesforce or HubSpot Enterprise | $150+/mo, 80% features unused, weeks to configure | Attio or Folk at $0-30/mo |
| Building internal tools pre-PMF | Engineering time that should go to the product | Off-the-shelf tools until $50K+ MRR |
| Buying annual contracts early | Locks in spend before you know what works | Stay monthly until a tool proves critical |
| Using 15+ tools at once | Context-switching tax exceeds the tool's value | Cap at 8-10 core tools |
---
## 3. Revenue Stage Playbook
GTM strategy shifts at every revenue milestone. What works at $0 MRR actively hurts at $50K MRR.
### Stage 1: $0-1K MRR (Validation)
**Goal**: Find 10 people who will pay. Nothing else matters.
**Time split**: 40% customer conversations, 40% building, 20% content.
- DM 20 people per day on X or LinkedIn who match your hypothesis.
- Charge from day one. Free users give bad feedback. Even $9/mo filters for real need.
- Build the smallest thing that solves a real pain. One feature, not a platform.
- Track who says "I need this" vs "that is interesting." Only "I need this" counts.
- Do not automate anything yet. Manual processes reveal what matters.
- **Skip**: Outbound sequences, paid ads, SEO, partnerships, complex funnels.
### Stage 2: $1K-10K MRR (Traction)
**Goal**: Find a repeatable acquisition channel.
**Time split**: 50% distribution, 30% building, 20% customer conversations.
- Test 2-3 acquisition channels simultaneously. Give each 30 days and $500 (or equivalent time).
- Start building in public. Share metrics, lessons, and behind-the-scenes.
- Set up basic outbound if ACV supports it. 50 personalized emails per week using Clay + Instantly.
- Document every deal: objections, buying triggers, competitor mentions. This becomes your sales playbook.
- Deploy Research Agent and Writing Agent (see Section 5).
- **Skip**: Hiring, complex automations, enterprise features, annual plans.
### Stage 3: $10K-50K MRR (Scale the Machine)
**Goal**: Systematize what works and deploy AI agents to multiply output.
**Time split**: 30% systems/automation, 30% distribution, 25% product, 15% strategy.
- Deploy full AI agent team for proven channels.
- Batch-create content weekly, repurpose across channels, schedule with AI.
- Raise prices. Most solo founders underprice by 2-3x at this stage.
- Introduce annual plans. Offer 2 months free for annual commitment.
- Start evaluating first hire (see Section 7).
- **Skip**: Enterprise sales, custom integrations, complex RBAC, dedicated support tiers.
### Stage 4: $50K-100K+ MRR (Founder Leverage)
**Goal**: Maximize revenue per founder-hour. Decide on hiring vs staying solo.
**Time split**: 30% strategy, 25% distribution, 25% product, 20% team management.
- Every hour should generate $200+ in value. Audit ruthlessly.
- Consider fractionaRelated in Design
contribute
IncludedLocal-only OSS contribution command center. Auto-refreshes the user's in-flight PR and issue state on invoke so conversations start with full context — no need to brief Claude on what's in flight. Helps the user find issues to contribute to on GitHub, builds per-repo dossiers of what each upstream expects (CLA, DCO, branch convention, AI policy, draft-first, review bots, issue templates), runs deterministic gates before any external action so AI-assisted contributions don't reach maintainers as slop. State is markdown-only: candidate files at ~/.contribute-system/candidates/, repo dossiers at ~/.contribute-system/research/, append-only event log at ~/.contribute-system/log.jsonl. No database, no cloud calls. Use when the user asks about their PRs / issues / contributions, wants to find new work to take on, claim an issue, build/refresh a repo's dossier, or draft a Design Issue or PR. Trigger with "/contribute", "what's my PR status", "find a contribution", "claim issue X", "draft a Design Issue for Y", "refresh dossier for Z".
architectural-analysis
IncludedUser-triggered deep architectural analysis of a codebase or scoped subtree across eight modes — information architecture, data flow, integration points, UI surfaces, interaction patterns, data model, control flow, and failure modes. This skill should be used when the user asks to "diagram this codebase," "map the architecture," "show the data flow," "give me an ERD," "trace control flow," "find the integration points," "verify the layout pattern," "audit the UX architecture," or any similar request whose primary deliverable is mermaid diagrams plus cited reports under docs/architecture/. Dispatches haiku/sonnet sub-agents in parallel for per-mode exploration, then verifies every citation mechanically before any node lands in a diagram. Not for one-off prose explanations of code (use code-explanation) or for high-level system design from scratch (use system-design).
mcp
IncludedModel Context Protocol (MCP) server development and tool management. Languages: Python, TypeScript. Capabilities: build MCP servers, integrate external APIs, discover/execute MCP tools, manage multi-server configs, design agent-centric tools. Actions: create, build, integrate, discover, execute, configure MCP servers/tools. Keywords: MCP, Model Context Protocol, MCP server, MCP tool, stdio transport, SSE transport, tool discovery, resource provider, prompt template, external API integration, Gemini CLI MCP, Claude MCP, agent tools, tool execution, server config. Use when: building MCP servers, integrating external APIs as MCP tools, discovering available MCP tools, executing MCP capabilities, configuring multi-server setups, designing tools for AI agents.
react-native-skia
IncludedDesign, build, debug, and optimise high-polish animated graphics in React Native or Expo using @shopify/react-native-skia, Reanimated, and Gesture Handler. Use when the user wants canvas-driven UI, shaders, paths, rich text, image filters, sprite fields, Skottie, video frames, snapshots, web CanvasKit setup, or performance tuning for custom motion-heavy elements such as loaders, hero art, cards, charts, progress indicators, particle systems, or gesture-driven surfaces. Also use when the user asks for fluid, glow, glass, blob, parallax, 60fps/120fps, or GPU-friendly animated effects in React Native, even if they do not explicitly say "Skia". Do not use for ordinary form/layout work with standard views.
plaid
IncludedProduct Led AI Development — guides founders from idea to launched product. Six capabilities: Idea (discover a product idea), Validate (pressure-test the idea against fatal flaws, problem reality, competition, and 2-week MVP feasibility), Plan (vision intake + document generation), Design (translate image references into a design.md spec), Launch (go-to-market strategy), and Build (roadmap execution). Use when someone says "PLAID", "plaid idea", "help me find an idea", "product idea", "idea from my business", "idea from my expertise", "plaid validate", "validate my idea", "pressure-test", "is this idea good", "find fatal flaws", "validate the problem", "plan a product", "define my vision", "generate a PRD", "product strategy", "plaid design", "design from image", "translate image to design", "create design.md", "extract design tokens", "plaid launch", "go-to-market", "launch plan", "GTM strategy", "launch playbook", "plaid build", "build the app", "start building", or "execute the roadmap".
nextjs-framer-motion-animations
IncludedAdds production-safe Motion for React or Framer Motion animations to Next.js apps, including reveal, hover and tap micro-interactions, whileInView, stagger, AnimatePresence, layout and layoutId transitions, reorder, scroll-linked UI, and lightweight route-content transitions. Use when the user asks to add, refactor, or debug Motion or Framer Motion in App Router or Pages Router codebases, especially around server/client boundaries, reduced motion, LazyMotion, bundle size, hydration, or route transitions. Avoid for GSAP-style timelines, WebGL or 3D scenes, heavy scroll storytelling, or CSS-only effects unless Motion is explicitly requested.