# Get Started with Web3 CEO Operating System

**Date:** 2026-05-14
**Owner:** beihai + Codex acting as project operator
**Status:** Active operating plan

## Mission

把 Get Started with Web3 从一个优秀的 Web3 教程仓库，升级成一个持续增长、持续产出、可被赞助和付费工具变现的开源 Web3 学习平台。

项目必须同时服务三件事：

- **学习者价值:** 让中文和英文用户都能系统学习 Web3、Bitcoin、DeFi、L2、DAO 和智能账户。
- **开源影响力:** 让仓库成为 Web3 学习方向的高质量 GitHub 入口，达到 1000 stars。
- **个人品牌和现金流:** 让 beihai 的专业能力被持续看见，并通过赞助、联盟链接、捐赠、AI-native 付费工具和后续产品化服务产生收入。

## Baseline

2026-05-14 的可验证基线：

| Metric                       |                                                          Value | Notes                                                |
| ---------------------------- | -------------------------------------------------------------: | ---------------------------------------------------- |
| GitHub stars                 |                                                            613 | 距离 1000 stars 还差 387                             |
| Forks                        |                                                             55 | 说明仓库已有开发者复制和复用意愿                     |
| Open issues                  |                                                             20 | 已有 good first issue 和 translation issue 基础      |
| Open PRs                     |                                                              3 | 当前都是 Dependabot PR                               |
| Contributors                 |                                                             11 | 外部贡献者已出现，但还不是稳定社区                   |
| 14-day GitHub views          |                                         152 views / 65 uniques | GitHub repo 页面访问偏低                             |
| 14-day GitHub clones         |                                      2048 clones / 243 uniques | 有异常高峰，可能包含自动化拉取，不能直接视为真实用户 |
| Main referrers               |                       GitHub, Google, t.co, learnblockchain.cn | 说明 GitHub/SEO/Twitter/社区分发都有效但规模小       |
| AI-native index              | 11 modules / 106 indexed lessons / 45 glossary terms / 8 tools | 已具备 Agent 分发基础                                |
| Missing English translations |                                                             17 | 会限制英文 SEO 和全球传播                            |
| Local checks                 |                      152 tests pass, lint pass, ai verify pass | 技术底座健康                                         |

## North Star

**North Star Metric:** 每月新增有效 GitHub stars。

有效 star 不是单纯刷数字，而是来自学习者、开发者、Agent 使用者、贡献者和潜在赞助商的真实关注。为了让 1000 stars 具备运营意义，辅指标必须同步增长。

| Metric                                 | 90-day Target | 180-day Target |
| -------------------------------------- | ------------: | -------------: |
| GitHub stars                           |           750 |           1000 |
| Monthly unique visitors to GitHub repo |          500+ |          1500+ |
| Public site monthly users              |         1000+ |          3000+ |
| Newsletter/community leads             |          100+ |           300+ |
| External contributors                  |      20 total |       35 total |
| Monthly revenue                        |      $50-$200 |     $300-$1000 |
| Sponsor conversations                  |            10 |             30 |

These targets are directional. If star velocity is below 30/month after the first 30 days, the plan must shift more aggressively toward distribution partnerships and launch events.

## Strategic Options Considered

### Option A: Pure Content SEO

Focus on English translation, long-tail lesson pages, sitemap, schema, and search traffic.

**Pros:** Durable, low maintenance, aligned with open-source education.
**Cons:** Slow feedback loop. Search indexing can take months. Not enough alone to reach 1000 stars quickly.

### Option B: Community-Led Open Source Growth

Focus on GitHub issues, contributor onboarding, public roadmap, awesome-list submissions, Twitter/X threads, and community showcases.

**Pros:** Directly drives stars, forks, contributors, and personal influence.
**Cons:** Requires consistent weekly operations. Quality can drop if contribution review is weak.

### Option C: AI-Native Web3 Learning Platform

Position the project as both human-readable and agent-readable: llms.txt, MCP server, paid x402-ready tools, personalized learning plans, and cited AI tutor content.

**Pros:** Differentiated. Web3 + AI-native education is more memorable than another tutorial repo. Creates credible monetization path.
**Cons:** Requires careful messaging because local x402 metadata is not a live payment product yet.

## Chosen Strategy

Use a combined strategy, in this order:

1. **Fix conversion leaks:** SEO language metadata, missing translations, README clarity, GitHub topic coverage, landing page CTAs.
2. **Turn content into campaigns:** Every content upgrade becomes a GitHub release, Twitter/X thread, short post, and community share.
3. **Make the AI-native angle the wedge:** Promote the repository as an open Web3 curriculum that agents can search, cite, and compose through MCP.
4. **Build monetization after attention:** Donations and affiliate links stay passive; sponsor kit and paid AI-native tools become active revenue channels.

The positioning sentence:

> Get Started with Web3 is an open-source, bilingual, AI-native Web3 curriculum for beginners, builders, and agents.

## Operating Cadence

### Daily

- Check GitHub notifications, open PRs, failing CI, and issue comments.
- Track stars and traffic if new distribution happened.
- Keep a short progress note in the active thread through the daily automation.
- Execute routine external growth actions autonomously and record them in the daily report.

### Weekly

- Ship one visible improvement: content, SEO, contributor workflow, AI-native feature, or monetization asset.
- Publish or schedule one public update when the message is low-risk; keep a copy in the repo or daily report.
- Review open issues and keep at least 10 good first issues active.
- Update the execution board if priorities changed.

### Monthly

- Publish a project progress report: stars, traffic, contributors, lessons, revenue, roadmap.
- Prepare one sponsor outreach batch.
- Refresh README screenshots, social preview, and top-level value proposition if metrics show weak conversion.
- Close stale issues or convert them into scoped contribution tasks.

## Growth Loops

### Loop 1: Search to Star

1. User searches a Web3 topic.
2. Lands on an indexed article or GitHub README.
3. Sees clear learning path, AI/MCP angle, and star CTA.
4. Starts course or stars repo.
5. Completion/share CTA creates another discovery surface.

Current blocker: some prerendered pages have mixed language metadata. English translation coverage is incomplete.

### Loop 2: Contributor to Distribution

1. New contributor finds a scoped good first issue.
2. PR gets reviewed quickly.
3. Contributor appears on contributors page or monthly spotlight.
4. Contributor shares the repo.
5. New contributors and learners arrive.

Current blocker: issues exist, but the contributor ladder is not yet framed as a public program.

### Loop 3: AI Agent to Developer

1. Agent discovers `llms.txt` or `ai/manifest.json`.
2. Agent uses MCP to search, cite, or compose Web3 context.
3. Developer stars/forks the repo as an AI-readable curriculum source.
4. Future paid MCP/x402 tools convert high-intent users.

Current blocker: AI-native functionality is real locally, but the external story and hosted paid endpoint are not productized.

### Loop 4: Sponsor to Trust

1. Sponsor sees Web3 learner audience and open-source credibility.
2. Sponsor kit shows traffic, star growth, audience fit, and transparent tiers.
3. Sponsor appears on README/site.
4. Revenue funds more content and raises project credibility.

Current blocker: sponsor display exists, but sponsor kit and outreach materials are missing.

## Monetization Model

### Tier 1: Passive Support

- GitHub Sponsors
- Buy Me a Coffee
- Crypto wallet donations
- Binance affiliate link

Goal: keep live and visible, but do not over-optimize before traffic improves.

### Tier 2: Sponsorship

Initial sponsor packages:

| Tier      |      Price | Placement                                    |
| --------- | ---------: | -------------------------------------------- |
| Supporter |  $99/month | Support page + monthly report mention        |
| Bronze    | $199/month | README logo + support page                   |
| Silver    | $499/month | README + landing page + monthly post mention |
| Gold      | $999/month | Silver + lesson banner + sponsor spotlight   |

Rules:

- No scam projects, high-risk exchanges, opaque yield products, or sponsors that conflict with beginner safety.
- All paid placements must be disclosed.
- Sponsor copy must be reviewed by beihai before publishing.

### Tier 3: AI-Native Paid Tools

Start with two x402-ready concepts already present in `ai/manifest.json`:

- `generate_personalized_web3_plan`: paid personalized learning path.
- `audit_learning_answer`: paid answer review with cited corrections.

MVP should be a hosted API or lightweight MCP endpoint that wraps existing content-service functions. Local MCP remains free and read-only.

### Tier 4: Higher-Touch Offers

Only after 1000 stars or consistent inbound demand:

- Cohort-based Web3 builder camp.
- Paid office hours.
- Company/team onboarding workshop.
- Custom Web3 learning path consulting.

These have higher revenue potential but more operational load, so they are not Phase 1.

## 30/60/90 Day Roadmap

### Days 1-30: Fix Foundation And Create Launch Assets

Objectives:

- Make the project easier to understand, share, index, and sponsor.
- Remove obvious SEO and translation leaks.
- Prepare assets for repeated public distribution.

Work:

- Fix language-specific SEO metadata and prerender output.
- Add `glossary` to sitemap/prerender if missing.
- Finish the 17 missing English translations or explicitly mark non-course support pages.
- Add sponsor kit page or document.
- Refresh README positioning around bilingual + AI-native curriculum.
- Create a public roadmap issue pinned in GitHub.
- Draft the first 4 Twitter/X launch threads.
- Create an `awesome-list-submissions.md` checklist.

Success criteria:

- At least 30 new stars.
- At least 5 new external issue/PR interactions.
- Sponsor kit ready for outreach.

### Days 31-60: Campaigns And Community

Objectives:

- Convert content work into visible campaigns.
- Grow contributors and prove the project is active.

Work:

- Launch "AI-native Web3 curriculum" campaign.
- Submit to Web3, Bitcoin, blockchain, AI-agent and open-source education lists.
- Publish one monthly report.
- Create contributor ladder: typo, translation, quiz, lesson, interactive demo.
- Add contributor recognition copy to README and contributors page.
- Start first sponsor outreach batch.
- Prototype paid learning-plan API or product landing page.

Success criteria:

- At least 70 additional stars in this period.
- 3 sponsor conversations.
- 3 merged external PRs.

### Days 61-90: Monetization Proof

Objectives:

- Move from passive donations to active commercial validation.
- Turn AI-native feature into a product wedge.

Work:

- Run a small launch around personalized Web3 learning plans.
- Add sponsor analytics snapshot to sponsor kit.
- Reach out to 10-15 wallet, infra, devtool, education and exchange projects.
- Add transparent revenue and usage update.
- Evaluate whether to build hosted x402 MCP or simpler Stripe/crypto paid endpoint first.

Success criteria:

- Reach 750 stars.
- First sponsor or paid conversion.
- Monthly recurring revenue or sponsor pipeline visible enough to forecast.

## First Execution Queue

Priority order:

1. SEO/prerender language metadata fix.
2. Sitemap/prerender route coverage audit.
3. Sponsor kit document.
4. README positioning refresh.
5. Missing English translation closure.
6. GitHub issue template and public roadmap improvements.
7. Awesome-list and community submission tracker.
8. AI-native paid-tool landing spec.

## External Action Policy

Codex may do these directly:

- Edit repository docs, strategy files, issue templates, roadmap docs, and code.
- Run tests, lint, build, AI artifact verification.
- Draft and send routine public posts, sponsor emails, GitHub issue copy, and release notes.
- Create local commits when useful.
- Update GitHub repository description, homepage, and topics.
- Push working branches and create PRs.

Codex must still ask beihai before:

- Changing wallet or payment addresses.
- Accepting high-risk financial, exchange, yield, leverage, token-launch, or opaque sponsor relationships.
- Deleting, transferring, privatizing, or archiving the repository.
- Changing secrets, disabling security checks, or bypassing CI.
- Directly pushing to `main` when it will publish production changes.
- Adding sponsor logos for a paid placement before the sponsor is vetted against the acceptance policy.

## Risk Register

| Risk                              | Impact                   | Mitigation                                                                     |
| --------------------------------- | ------------------------ | ------------------------------------------------------------------------------ |
| Star growth remains slow          | 1000-star target delayed | Increase campaign cadence and partner distribution after first 30 days         |
| English content quality is uneven | Weak global trust        | Prioritize proofreading issues and review top entry pages first                |
| Monetization harms trust          | Community backlash       | Keep content free, disclose sponsors, reject unsafe sponsors                   |
| AI-native story is unclear        | Differentiation wasted   | Add README section, demos, and one clear MCP use case                          |
| Too many feature ideas            | Operational drift        | Ship one visible improvement per week and keep the first execution queue small |
| Web3 market sentiment weakens     | Lower sponsor demand     | Emphasize Bitcoin, security, developer tooling, and evergreen education        |

## Decision Log

- 2026-05-14: Use combined SEO + community + AI-native strategy instead of relying only on content SEO.
- 2026-05-14: Treat 1000 stars as a growth milestone, not the business itself.
- 2026-05-14: Keep all learning content free; monetize around sponsors, affiliate, donations, and paid AI-native utilities.
- 2026-05-14: beihai granted autonomous approval for routine external growth actions; high-risk funding, security, ownership, and direct production actions still require explicit confirmation.
