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Proposal 78: PlanExe Growth & Awareness Strategy

Author: Larry (VoynichLabs)
Date: 28 February 2026
Status: Draft — for Simon's review and team execution
Relates to: Proposals 73–77 (technical foundation complete)

Executive Summary

PlanExe's technical foundation is solid (complexity routing, cache-aware handoff, cost-aware execution). The missing piece is visibility. This proposal outlines a systematic growth strategy across five channels: GitHub metrics, AI agent adoption, human user growth, Discord community, and social media presence.

The goal: transform PlanExe from an internal planning tool into the standard planning layer for agent-driven systems.

Current State (Feb 2026)

GitHub: - ~150 stars (estimate) - 8+ merged proposals (PRs #102–#106, etc.) - Active development on PlanExeOrg/PlanExe upstream - VoynichLabs fork (PlanExe2026) with experimental features

Community: - Discord: minimal activity (~5 members, core team only) - Twitter: no active account - Reddit: no presence - HackerNews: no post history - Product Hunt: not launched

Agent Adoption: - Zero documented integration examples - No clear "how to integrate PlanExe" onboarding - No agent SDK or library (MCP available but undocumented externally)

Human Users: - Direct users: Simon + internal team (3–5 people) - Enterprise/commercial: none - Academic interest: unknown

Goals (90-day horizon)

Metric Current Target 90-day
GitHub stars ~150 500+ 300–400
GitHub forks ~20 100+ 50–75
Open PRs from external 0 5+ 2–3
Agent integration examples 0 5+ 3–4
Discord members 5 50+ 25–30
Monthly website visits ~0 500+ 200–300
Social media followers 0 100+ 30–50

Strategy 1: GitHub Visibility & Contribution Onboarding

Current Problem

PlanExe is technically excellent but looks dormant to outsiders. Proposal docs are deep, but there's no "start here" landing page that explains what PlanExe is for someone encountering it for the first time.

Actions

A. README Overhaul - Add a one-sentence value prop: "PlanExe: Multi-agent planning with automatic cost-aware model routing and execution auditing." - Add a "Getting Started in 5 Minutes" section (install, run hello-world plan, view cost breakdown) - Link to live demo or demo video - Add badges (stars, forks, build status, license)

B. Contribution Guide - Create CONTRIBUTING.md with clear categories: - Bug reports (template) - Feature requests (template) - Documentation improvements (point to /docs/proposals) - Code contributions (fork → PR workflow) - Document the proposal-first workflow (write proposal, get feedback, then implement)

C. Examples & Integrations Hub - Create /examples directory with 3–5 documented, runnable examples: - "Plan a 3-step DevOps workflow" (show cost routing) - "Multi-agent conversation with PlanExe auditing" - "Integrate with CrewAI orchestrator" - "Run locally with Ollama + PlanExe" - "Cost-aware autonomous agent loop" - Each example: README, source code, expected output, cost breakdown

D. Badges & Social Proof - Add GitHub star badge to README (auto-updates) - Add "Used by [Agent names]" section (once we have adoption) - Add testimonial quotes (from Simon, Egon, Bubba, early users)

Owner

Egon (documentation + examples)

Timeline

1–2 weeks

Strategy 2: Agent SDK & Integration Library

Current Problem

There's no clear way for external agents (AutoGen, CrewAI, Anthropic agents, OpenClaw) to use PlanExe. The MCP protocol exists but is underdocumented.

Actions

A. Agent Integration Guide - Write /docs/agent-integration.md: - MCP protocol overview - JSON-RPC endpoint format - PlanExe capabilities (plan, estimate_cost, execute_audit) - Required authentication - Error handling & retries - Code samples in 3 languages (Python, JavaScript, Go)

B. Python SDK (pip-installable) - Minimal wrapper around MCP protocol - pip install planexe - Simple API: 

from planexe import PlanExe
client = PlanExe(host="http://localhost:8001")
plan = client.generate("write a blog post about agents")
cost = client.estimate_cost(plan)
result = client.execute(plan)
print(f"Executed for ${cost.total_usd}")
- Publish to PyPI - Update README with quick-start

C. Worked Examples per Framework - AutoGen + PlanExe example (notebook) - CrewAI + PlanExe example (repository) - OpenClaw + PlanExe example (repository, may already exist) - LangChain agent + PlanExe (repository) - Anthropic SDK + PlanExe (code sample)

Owner

Bubba (SDK + core examples)

Timeline

2–3 weeks

Strategy 3: AI Agent Adoption Targets

Current Problem

Zero documented integrations. External agents don't know PlanExe exists.

Actions

A. Outreach to Agent Frameworks - AutoGen (Microsoft) — submit PR with PlanExe integration example - CrewAI — reach out with integration code + blog post offer - LangChain — submit LangChain tool for PlanExe - Anthropic SDK — showcase PlanExe in agent loop examples - OpenClaw — document PlanExe as MCP available by default

B. Agent-to-Agent Capability Advertising - Publish /docs/a2a-capability.json (from Proposal 76) - Link from main README: "PlanExe advertises itself to agents via the A2A protocol" - Include x402 payment capability advertisement (even if not yet implemented)

C. Case Study: Autonomous Agent Loop - Write blog post: "Building a Self-Auditing Autonomous Agent with PlanExe Cost Routing" - Show: - Agent generates plan - PlanExe routes by complexity - Cost breakdown per step - Agent learns which models are cost-efficient - Code: /examples/autonomous-loop-with-auditing - Publish to dev.to, HackerNews, Reddit

D. Research Papers & Conferences - Propose talk at AI agent conferences (e.g., Hugging Face, OpenAI DevDay adjacent, SmallModels) - Write technical paper: "Cost-Aware Routing in Multi-Model Agent Systems" - Target venues: arXiv, agent-focused workshops

Owner

Egon (outreach + examples)

Timeline

3–4 weeks (some parallel)

Strategy 4: Human User Acquisition

Current Problem

No path for human users (product managers, ML engineers, DevOps teams) to discover PlanExe.

Actions

A. Product Website - Simple marketing site (Astro or similar): - Hero: "Plan once. Route intelligently. Track costs." - Features section: complexity routing, cost auditing, agent-ready - Screenshot/screencast: run a plan, see cost breakdown - Pricing: (free for self-hosted, freemium for cloud later) - CTA: "Get Started" → link to GitHub + docs

B. Blog & Content Marketing - Monthly blog posts (on website + cross-post to dev.to, Medium): - "How Much Does It Cost to Run Your AI Workflow?" (cost analysis) - "When to Use Haiku vs. Opus: The PlanExe Complexity Rubric" (explainer) - "Autonomous Agents Need Auditing" (thought leadership) - "Building Multi-Model Systems Without Breaking the Bank" (case study)

C. Email Newsletter (optional) - Monthly digest: new proposals, user stories, cost trends - Link at bottom of GitHub README: "Subscribe to PlanExe updates"

D. Webinar / Demo - 30-minute live demo: - Run a plan in real-time - Show cost breakdown - Q&A with Simon - Record for YouTube

Owner

Bubba (website) + Egon (blog + outreach)

Timeline

2–3 weeks for MVP site, ongoing for blog

Strategy 5: Community & Social Media

Current Problem

Zero online community. No social media presence.

Actions

A. Discord Community - Invite 20–30 interested developers (from GitHub stars, agent framework communities) - Create channels: - #announcements — new features, proposals, releases - #showcase — user projects, integrations, case studies - #help — troubleshooting, questions - #proposals — discussion of pending proposals before/after merge - #jobs — PlanExe-related opportunities - Weekly "What are you building?" thread

B. Twitter / X - Create account: @PlanExeOrg (or similar) - Tweet schedule (2–3x/week): - New proposals (with 1-paragraph summary) - Agent integrations - Cost benchmarks ("Running this 5-step plan with Sonnet vs. Haiku routing saved $0.47") - Links to blog posts - Retweet agent framework updates

C. HackerNews / Reddit - Post 2–3 Show HN threads over 90 days: - Launch: "Show HN: PlanExe — Cost-Aware Planning Layer for AI Agents" - Follow-up: "PlanExe Now Has Agent SDKs" - Blog post links in comments - Monitor r/MachineLearning, r/LocalLLM for PlanExe-relevant threads; answer questions

D. Podcast / Talk Circuit - Pitch Simon for interviews: - AI Breakfast podcast - Gradient Descent (if agent-focused) - Local LLM / Small Models podcasts - Speaking proposals to conferences (3–6 months out)

Owner

Larry (social media + outreach) + Simon (key interviews)

Timeline

1 week to set up, ongoing

Execution Plan (90 Days)

Week 1–2 (Now – March 15)

  • [ ] README overhaul (Egon)
  • [ ] CONTRIBUTING.md (Egon)
  • [ ] Twitter account setup (Larry)
  • [ ] Discord server setup (Bubba)
  • [ ] Python SDK skeleton (Bubba)

Week 3–4 (March 15–29)

  • [ ] Agent integration guide (Bubba)
  • [ ] First 2 agent examples (Bubba + Egon)
  • [ ] Website MVP (Bubba)
  • [ ] First blog post (Egon)
  • [ ] Twitter content calendar planned (Larry)

Week 5–8 (March 29 – April 26)

  • [ ] AutoGen + CrewAI integration PRs submitted (Egon)
  • [ ] Python SDK released to PyPI (Bubba)
  • [ ] 3–4 blog posts published (Egon)
  • [ ] Case study example complete (Egon + Bubba)
  • [ ] Discord invites sent, community bootstrapped (Larry)
  • [ ] HackerNews post (Simon + Larry)

Week 9–12 (April 26 – May 24)

  • [ ] Conference talk proposals submitted (Simon)
  • [ ] Podcast interview recorded (Simon + 1 lobster)
  • [ ] User feedback incorporated
  • [ ] Website metrics reviewed
  • [ ] Social media engagement reviewed

Success Metrics

GitHub: - 300–400 new stars (total 450–550) - 2–3 PRs from external contributors - 1–2 issues from external users

Agent Adoption: - 3–4 worked integration examples published - 2–3 agent frameworks documenting PlanExe in their ecosystem - 10+ developers mentioning PlanExe in agent projects (Twitter, GitHub, forums)

Human Users: - 200+ website visits/month - 2–3 blog posts reaching 100+ readers each - 1–2 users in Discord from external sources

Community: - 25–30 Discord members - 30–50 Twitter followers - 1 HackerNews post with 100+ upvotes - 1 podcast interview

Dependencies & Assumptions

  • Assumption: Simon is available for 2–3 key interviews/talks (120 min total)
  • Assumption: External frameworks (AutoGen, CrewAI) are willing to accept integration PRs
  • Dependency: Website infrastructure (Vercel, GitHub Pages, or similar)
  • Dependency: Twitter/social media continuity (Larry or designee owns daily updates)

Risks & Mitigation

Risk Probability Impact Mitigation
Low external interest in adoption Medium High Start with agent framework maintainers who are already interested; showcase internal use case (OpenClaw) first
Contributors don't follow proposal-first workflow Medium Medium Clear CONTRIBUTING.md + examples; pair review with external PRs
Social media/blog burnout Medium Low Rotate authors (Egon, Larry, Bubba); repurpose proposal docs into blog posts
No budget for ads High Low Organic growth is slower but sustainable; focus on free channels (Twitter, Reddit, HackerNews)

Conclusion

PlanExe is ready to be discovered. This strategy provides a map to turn technical excellence into community momentum and market adoption.

The next 90 days should result in: 1. Infrastructure: website, SDK, integration examples, community platform 2. Visibility: 3–5x GitHub stars, social media presence, blog authority 3. Adoption: first external agent integrations, user feedback, case studies

Success looks like: "PlanExe is the default planning layer for cost-aware AI agents."