Progress update, strategic direction, and milestones for the next 12 months. 进展更新、战略方向及未来12个月里程碑。
"Learn quantitative trading. Here's a course. Here's a backtesting tool.""学量化交易。这是课程。这是回测工具。"
"Think you can trade? Prove it. Free capital. Real competition. We just keep score.""你觉得你会交易？证明给我看。免费资金。真实竞赛。我们只记分。"
The core bet: people don't learn from advice. They learn from losing. We built a place where they can figure that out themselves — and when they're ready, the tools are right there. 核心赌注：人们不会从建议中学习，而是从亏损中学习。我们建了一个让他们自己发现这一点的地方 — 当他们准备好了，工具就在手边。
Free capital, live competition, trade however you want. We don't lecture. We just record everything — entry timing, position sizing, panic sells, revenge trades.免费资金、实时竞赛、随便怎么交易。我们不说教。只是记录一切 — 入场时机、仓位大小、恐慌卖出、报复交易。
After each cycle, they get a scorecard. Not "you lost money" — more like "you panic-sold 6 times after 3% dips." Meanwhile, quant strategies running in the same competition quietly outperform.每个周期结束，他们收到评分卡。不是"你亏了" — 而是"你在3%回调后恐慌卖出了6次"。同时，在同一竞赛中的量化策略默默跑赢。
After watching themselves lose to the same mistakes three rounds in a row, the motivation is personal. That's when we open the door to the quant tools. No pitch required.看着自己连续三轮犯同样的错误，动力变成了个人的。这时我们打开量化工具的大门。不需要推销。
User loop: Competition → scorecard → quant tools → paid conversion → funded accounts. Data loop: Behavioral patterns from manual traders become a proprietary signal. Their collective mistakes are, by definition, tradeable.用户飞轮：竞赛 → 评分卡 → 量化工具 → 付费转化 → 实盘账户。数据飞轮：手动交易者的行为模式成为专有信号。他们的集体错误，本质上是可交易的。
| Education First教育优先 | Arena First (Us)竞技场优先（我们） | |
|---|---|---|
| Why users sign up用户注册原因 | "I should learn quant""我应该学量化" | "I'll prove I can trade""我来证明我能交易" |
| Early drop-off早期流失 | ~90% | Low (ego keeps them)低（自尊心留住他们） |
| Conversion trigger转化触发点 | Marketing copy营销文案 | Their own data他们自己的数据 |
| Data asset数据资产 | None无 | Behavioral alpha行为Alpha |
| Viral potential传播潜力 | Low (courses)低（课程） | High (scorecards)高（评分卡） |
| Revenue timing收入时间 | After education (slow)教育后（慢） | During competition竞赛期间 |
One is a classroom. The other is a colosseum. The colosseum fills itself.一个是教室。另一个是竞技场。竞技场会自己填满。
Benchmarked against consumer fintech & gaming apps.对标消费金融科技和游戏应用。
These are estimates. We'll know real numbers after Q2 beta. The model self-corrects — scorecards create the conversion trigger, not sales.这些是估算。Q2测试后才有真实数据。模型会自我修正 — 评分卡创造转化触发，而非销售。
22-month runway (Feb 2026 – Dec 2027). Covers team, infrastructure, and initial GTM.22个月运营资金（2026年2月-2027年12月）。覆盖团队、基础设施和初始市场推广。
Trigger: 10K+ users, first revenue, proven retention. Use: scale paid acquisition, hire, expand product.触发条件：1万+用户、首笔收入、验证留存。用途：扩大付费获客、招聘、产品扩展。
Trigger: $1M ARR, 50K+ users, B2B pipeline. Use: regional expansion (SEA/APAC), B2B team, enterprise product.触发条件：$1M ARR、5万+用户、B2B管线。用途：区域扩张（东南亚/亚太）、B2B团队、企业产品。
Small team now. That's intentional. We're proving the model before scaling the headcount. Hire after we see real retention numbers from Q2 beta.现在团队小。这是有意的。在扩大团队前先验证模式。Q2测试后看到真实留存数据再招人。
If the scorecard isn't compelling enough, people just leave. Mitigation: make the report card so good they have to share it. Ego works both ways.如果评分卡不够吸引人，人们就会离开。应对：让报告卡好到他们必须分享。自尊心是双刃剑。
We're estimating 8-12%. Could be 3-5% initially. Mitigation: tournament fees provide revenue even with low subscription conversion.我们估计8-12%。初期可能3-5%。应对：即使订阅转化低，锦标赛费用也能提供收入。
Simulated capital competitions may need licensing in some jurisdictions. Mitigation: start in Singapore (friendly), paper trading only initially, legal review ongoing.模拟资金竞赛在某些司法管辖区可能需要牌照。应对：先在新加坡（友好环境）、初期仅模拟交易、法律审查进行中。
They could add competitions. But they can't build the AI scoring, behavioral data loop, and quant agent platform. The moat is the full stack, not any single feature.他们可以加竞赛功能。但他们无法构建AI评分、行为数据闭环和量化代理平台。护城河是全栈，不是任何单一功能。
Maybe users just keep trading manually and never convert. Mitigation: the competition itself has monetization (tournament fees, premium features). Migration is upside, not the only path.也许用户只是一直手动交易不转化。应对：竞赛本身有变现（锦标赛费、高级功能）。迁移是额外收益，不是唯一路径。
Bottom line: We don't need every assumption to be right. The arena model generates revenue and data even if conversion rates are half of what we expect. That's the margin of safety.底线：我们不需要每个假设都正确。即使转化率只有预期的一半，竞技场模式仍然能产生收入和数据。这就是安全边际。
If D7 retention hits 35%+ in beta, the model works. Everything else follows.如果测试版D7留存达到35%+，模型就成立了。其他一切都会跟上。
We have the engine, the data, the team, and now the strategy. The next 90 days are about shipping the arena and getting real users in. Everything we learn from that shapes what comes next. 我们有引擎、数据、团队，现在还有策略。接下来90天的重点是上线竞技场并获得真实用户。从中学到的一切将决定下一步。