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Adept Alumni Talent Intelligence Station: Dynamic tracking of a 150-person team, earning 15,000 RMB monthly

Workflow: Automatically scrapes public information from LinkedIn, X, and GitHub daily, identifying Adept alumni title changes, new

AGENT

Key Fields

FIELD STAMPS

IndustryFintech

RegionGlobal

ScaleSME

ChannelOnline

🔧 Workflow

Automatically scrapes public information from LinkedIn, X, and GitHub daily, identifying Adept alumni title changes, new company formations, and paper publications, and uses AI to summarize them into intelligence cards. Inputs are company names or personnel lists, and outputs are email newsletters and real-time alerts. When an event is triggered, the system re-extracts from news sources, breaking the news down into three threads: people, companies, and roles, then matches them with the tracked personnel database to generate user-exclusive reminders. Every weekend, it automatically aggregates a weekly event relationship graph, highlighting which intelligence items relate to the AI Agent product line, model R&D roles, and startup financing.

🛠 Setup Requirements

Requires proficiency in Python or n8n automation, applying for Twitter API and GitHub API, and integrating large language models for summarization. Setup takes about 2 weeks; initially, you can manually maintain 10 people to validate demand. During the validation phase, the free version of n8n and self-built keyword subscriptions handle about 70% of the workload, with paid APIs used only for high-frequency monitored figures. Check the personnel status sheet every Wednesday to avoid data backlog. The overall technical barrier is not high; the key lies in converting public data into structured personnel profiles, a step that determines subsequent intelligence quality.

🧰 Toolchain

🔧 n8n
🔧 OpenAI API
🔧 GitHub API
🔧 Twitter API

💰 Revenue

Approximately 15,000 RMB per month, coming from 60 subscribing users (199 RMB each) and a small amount of project-based consulting, with actual figures fluctuating based on user scale. When trigger-type news appears, single-month consulting revenue can reach over 20,000 RMB; for example, a targeted talent flow report generated by the 150-person transfer event was priced at 5,000 RMB per instance. Subscriptions flow steadily via online payments, while consulting is quoted on a project basis, averaging between 2,000 RMB and 8,000 RMB per order.

💸 Cost

Tool subscriptions are about 500 RMB/month, mainly for API calls and cloud function fees. If integrating a higher-tier LinkedIn data proxy, the cost would rise to around 1,000 RMB/month, though it is not needed initially.

⏱ Time Investment

About 2 hours per day for data validation and content editing; on days with trigger-type news, an extra hour is added for in-depth correlation analysis. Every Sunday takes about 1 hour to compile the weekly report and the critical personnel dynamics list for the following Monday.

🚀 Getting Started

The first step for beginners is to manually organize the public dynamics of 10 Adept alumni, publish them on a free mailing list, and observe replies and subscription conversions. Once demand is confirmed, use n8n automation for scraping and distribution. The second step is to build a timestamped profile page for each tracked person, recording job changes and news correlations. The third step is to turn the two most-followed personnel threads into a paid weekly report, collecting payments via an email subscription tool. Note: run the process smoothly using free tools before upgrading to paid APIs.

🔑 Keys to Success

✅ Track key individuals rather than the entire company for higher information density
✅ Use exclusively public data to lower compliance risks
✅ Leverage event-driven push mechanisms to turn trending news into paid consulting entry points
✅ Three-tiered pricing targeting headhunters, VCs, and media, monetizing a single piece of intelligence multiple times
✅ Tag alumni for life, allowing subsequent startups and job hops by the same person to trigger recurring payments

⚠️ 风险

⚠️ LinkedIn has strict restrictions on automated access and may ban accounts, requiring simulated human pacing
⚠️ Intelligence sources rely on public info; undisclosed personnel changes cannot be covered, creating information gaps
⚠️ Topic hype around star AI Agent teams will fluctuate with industry cycles, leading to unstable renewal rates
⚠️ If major tech giants bind tracked individuals with non-compete agreements, public info may experience prolonged silence, causing product update interruptions

📌 Real Cases

📌 In July 2026, after the news 'Company A exposes worst Claude! 150 people emergency transferred' was captured by the system, the automatically generated talent flow graph was purchased by 3 venture capital firms, yielding a single consulting fee of 5,000 RMB and cumulative revenue of 15,000 RMB.
📌 On July 28, 2026, the day the report 'Amazon restructuring AI strategy on the eve of financial earnings' was published, the system automatically pushed a correlation brief on Adept and AWS strategic adjustments to subscribers, adding 12 monthly subscribers and increasing revenue by about 2,400 RMB that month.
📌 A dissected weekly report targeting the release of the 'Adept AI In-Depth Research Report' was reposted by 5 media organizations, bringing in 4 project-based intelligence analysis orders at an average price of 3,000 RMB each, totaling about 12,000 RMB.
📌 When the 2026 world model training and robotics exit topics fermented, the system compiled Adept's former team layouts in the robotics field into a standalone report, subscribed to by 2 funds at an annual unit price of 6,000 RMB, totaling about 12,000 RMB.

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