Founder Coach 🎯
Your AI-powered founder accountability system.
A structured coaching framework for AI-era founders. Daily check-ins, decision journaling, weekly strategy reviews, and accountability tracking — all stored in your agent's memory.
Quick Start
CODEBLOCK0
🌅 Morning Brief Template
Use this every morning to set your day:
1. Yesterday Recap
- - What did I commit to yesterday?
- What actually got done? (completion rate)
- What carried over and why?
2. Today's Top 3 Priorities
| # | Priority | Why it matters | Time block |
|---|
| 1 | | | |
| 2 |
| | |
| 3 | | | |
Rule: If you can only do ONE thing today, which is it? That's #1.
3. AI Founder Question of the Day
Pick one to reflect on:
- - "What manual process am I doing that AI could handle?"
- "Where is my moat — data, workflow, distribution, or brand?"
- "What's my cost-per-serve and how do I halve it?"
- "Am I building a product or a feature that GPT will add next quarter?"
- "What would a 10-person AI-native company do differently?"
🌙 Evening Reflection Template
Wins
- - What went well today?
- What am I proud of?
Losses
- - What didn't happen? Why?
- What would I do differently?
Tomorrow
- - Top 3 priorities for tomorrow
- One thing to stop doing
- One thing to start doing
Energy Check
Rate 1-5: Energy [ ] Focus [ ] Motivation [ ]
📊 Weekly Strategy Review
Run every Sunday or Monday. Takes 30-60 minutes.
Performance
- - Commitments made this week:
- Commitments kept: (_%)
- Trend vs last week: ↑ / → / ↓
Key Metrics
| Metric | Last Week | This Week | Target |
|---|
| Revenue | | | |
| Users/Customers |
| | |
| Key Feature Progress | | | |
| Cost-per-serve | | | |
Strategic Questions
Moat Analysis
- - Data moat: Are we accumulating proprietary data? What data do we have that others don't?
- Workflow moat: Are we embedded in customer workflows? Switching cost?
- Distribution moat: Do we own a channel? Community? Brand?
- Speed moat: Are we shipping faster than anyone else?
Commoditization Risk
- - Which parts of our stack are becoming commoditized?
- What happens when GPT-5 / Claude 4 / Gemini 3 drops?
- Are we building on top of APIs that could become competitors?
AI-Era Economics
- - Cost-per-serve: What does it cost to serve one customer?
- Outcome-based pricing: Can we charge for outcomes, not seats?
- Marginal cost: Does our 1000th customer cost the same as the 1st?
- AI leverage: Where does AI give us 10x leverage vs humans?
Decisions Made This Week
| Decision | Context | Options Considered | Chosen | Reversible? |
|---|
| | | | |
Next Week
- - #1 priority (must happen):
- #2 priority (should happen):
- #3 priority (nice to have):
- One bet/experiment to run:
📓 Decision Journal Format
For important decisions, use this format:
CODEBLOCK1
📈 Accountability System
How It Works
- 1. Morning: Set 3 commitments
- Evening: Mark complete/incomplete with notes
- Weekly: Review completion rate and patterns
- Monthly: Identify systemic issues
Scoring
- - 90-100% completion: You're either crushing it or setting easy goals
- 70-89%: Healthy stretch zone
- 50-69%: Overcommitting or execution issues
- Below 50%: Stop. Fewer commitments. Execute on 1-2 things.
Patterns to Watch
- - Always incomplete #3: You're overcommitting — do 2 things well
- Same item carrying over: It's either not important (cut it) or you're avoiding it (why?)
- High completion but no progress: You're busy, not productive — wrong priorities
- Energy always low: Burnout risk — take a break before it takes you
🤖 AI-Era Founder Questions Bank
Rotate through these in morning briefs:
Product & Moat
- 1. What would this business look like if AI could do 80% of the work?
- Are we a thin wrapper around an API? How do we add defensible value?
- What proprietary data or feedback loops do we create?
- If OpenAI built our feature tomorrow, what would still be ours?
Economics
- 5. What's our cost-per-serve and trajectory?
- Can we charge for outcomes instead of access?
- Where do margins come from when AI costs drop 10x yearly?
- What's our unit economics at 10x scale?
Competition
- 9. What can a 3-person AI-native startup build in 3 months that competes with us?
- Where do we have distribution that new entrants don't?
- What switching costs have we built?
Personal
- 12. Am I building a company or a project?
- What am I uniquely positioned to build that AI can't easily replicate?
- Am I spending time on $10/hr tasks or $1000/hr tasks?
- What would I do if I had 10x the resources? What about 1/10th?
Storage
All entries are stored in memory/founder-journal/:
CODEBLOCK2
Credits
Built by
M. Abidi |
agxntsix.ai
YouTube |
GitHub
Part of the
AgxntSix Skill Suite for OpenClaw agents.
📅 Need help setting up OpenClaw for your business? Book a free consultation
创始人教练 🎯
你的AI驱动创始人问责系统。
为AI时代创始人打造的结构化教练框架。每日签到、决策日志、每周战略回顾和问责追踪——全部存储在你的智能体记忆中。
快速开始
bash
晨间签到
python3 {baseDir}/scripts/founder_checkin.py morning
晚间反思
python3 {baseDir}/scripts/founder_checkin.py evening
每周回顾
python3 {baseDir}/scripts/founder_checkin.py weekly
查看统计
python3 {baseDir}/scripts/founder_checkin.py stats
查看近期记录
python3 {baseDir}/scripts/founder_checkin.py history --days 7
🌅 晨间简报模板
每天早晨使用此模板规划你的一天:
1. 昨日回顾
- - 我昨天承诺了什么?
- 实际完成了什么?(完成率)
- 哪些事项被推迟了?原因是什么?
2. 今日三大优先事项
| | |
| 3 | | | |
规则: 如果今天只能做一件事,那是什么?那就是#1。
3. AI创始人每日一问
选择一个问题进行反思:
- - 我正在做的哪些手动流程可以由AI处理?
- 我的护城河在哪里——数据、工作流程、分销渠道还是品牌?
- 我的单次服务成本是多少?如何将其减半?
- 我是在构建一个产品,还是GPT下个季度就会添加的功能?
- 一个10人的AI原生公司会怎么做不同的事情?
🌙 晚间反思模板
胜利
失利
- - 哪些事情没有完成?为什么?
- 我会怎么做不同的事情?
明日计划
- - 明天三大优先事项
- 一件需要停止做的事情
- 一件需要开始做的事情
能量检查
评分1-5:能量 [ ] 专注力 [ ] 动力 [ ]
📊 每周战略回顾
每周日或周一进行。耗时30-60分钟。
绩效
- - 本周承诺事项:
- 完成事项:(_%)
- 与上周趋势对比:↑ / → / ↓
关键指标
| | |
| 关键功能进展 | | | |
| 单次服务成本 | | | |
战略性问题
护城河分析
- - 数据护城河: 我们是否在积累专有数据?我们拥有哪些别人没有的数据?
- 工作流程护城河: 我们是否嵌入到客户的工作流程中?转换成本如何?
- 分销护城河: 我们是否拥有渠道?社区?品牌?
- 速度护城河: 我们的交付速度是否比任何人都快?
商品化风险
- - 我们技术栈的哪些部分正在变得商品化?
- 当GPT-5 / Claude 4 / Gemini 3发布时会发生什么?
- 我们是否在可能成为竞争对手的API之上构建?
AI时代经济学
- - 单次服务成本: 服务一个客户的成本是多少?
- 基于结果的定价: 我们能否按结果收费,而不是按席位收费?
- 边际成本: 第1000个客户的成本是否与第一个相同?
- AI杠杆: 与人类相比,AI在哪里能给我们带来10倍的杠杆?
本周决策
下周计划
- - #1优先事项(必须完成):
- #2优先事项(应该完成):
- #3优先事项(锦上添花):
- 一个可执行的赌注/实验:
📓 决策日志格式
对于重要决策,使用此格式:
决策:[标题]
日期:YYYY-MM-DD
重要性:低 / 中 / 高 / 关键
背景
当前情况如何?为什么现在需要做出这个决策?
选项
- 1. 选项A:[描述]
- 优点:...
- 缺点:...
- 成本:...
- 2. 选项B:[描述]
- 优点:...
- 缺点:...
- 成本:...
决策
选择:[选项X]
理由:[原因]
可逆:是/否
审查日期:[何时检查决策是否正确]
结果(稍后填写)
审查日期:
结果:
经验教训:
📈 问责系统
工作原理
- 1. 早晨: 设定3项承诺
- 晚间: 标记完成/未完成并附注说明
- 每周: 审查完成率和模式
- 每月: 识别系统性问题
评分标准
- - 90-100% 完成率:要么表现卓越,要么目标设定过于简单
- 70-89%:健康的挑战区间
- 50-69%:过度承诺或执行问题
- 低于50%:停下来。减少承诺。专注于1-2件事。
需关注的模式
- - #3总是未完成: 你过度承诺了——做好2件事
- 同一事项反复推迟: 要么不重要(砍掉它),要么你在逃避(为什么?)
- 完成率高但无进展: 你在忙碌而非高效——优先级错误
- 能量始终低迷: 倦怠风险——在它击垮你之前先休息
🤖 AI时代创始人问题库
在晨间简报中轮换使用这些问题:
产品与护城河
- 1. 如果AI能完成80%的工作,这个业务会是什么样子?
- 我们是否只是API的薄包装?如何增加可防御的价值?
- 我们创造了哪些专有数据或反馈循环?
- 如果OpenAI明天构建了我们的功能,我们还有什么?
经济学
- 5. 我们的单次服务成本和趋势如何?
- 我们能否按结果收费而不是按访问权限收费?
- 当AI成本每年下降10倍时,利润从何而来?
- 在10倍规模下,我们的单位经济学是什么?
竞争
- 9. 一个3人的AI原生初创公司能在3个月内构建出与我们竞争的产品吗?
- 我们在哪些方面拥有新进入者没有的分销渠道?
- 我们构建了哪些转换成本?
个人
- 12. 我是在建立公司还是项目?
- 我有什么独特优势可以构建AI不易复制的东西?
- 我是在花时间做10美元/小时的任务还是1000美元/小时的任务?
- 如果我有10倍的资源,我会做什么?如果是1/10的资源呢?
存储
所有记录存储在 memory/founder-journal/ 中:
memory/founder-journal/
├── 2026-02-15.md # 每日记录
├── 2026-02-16.md
├── weekly/
│ └── 2026-W07.md # 每周回顾
└── decisions/
└── 2026-02-15-decision-name.md
致谢
由
M. Abidi 构建 |
agxntsix.ai
YouTube |
GitHub
属于 OpenClaw 智能体的
AgxntSix 技能套件 的一部分。
📅 需要为你的业务设置 OpenClaw? 预约免费咨询