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Fang Chen

Positioning: Java backend engineer with 10 years of experience, specializing in system-level debugging and payment/e-commerce business logic fixes. I don't write code from scratch — I fix the problems that AI-generated code runs into when it hits real business scenarios. Technical Background: 10 years of Java backend development. Experienced with the Spring ecosystem, database design, API integration, and concurrency handling. Deep involvement in HIS (Hospital Information Systems), e-commerce platforms, and payment systems. I understand transaction flows, risk control logic, and data consistency. Strong debugging methodology: I work backward from symptoms to root cause, instead of repeatedly trying fixes in the wrong place. Why I Can Fix AI Code: AI-generated code usually works on the "happy path." The real problems show up in places like: Payment integration: webhook verification, callback idempotency, amount precision, state machine transitions. Database & concurrency: N+1 queries, missing indexes, unclear transaction boundaries. Business logic: AI tends to write logic that "looks right" but completely ignores real-world edge cases. I have hands-on experience with payment and e-commerce systems, so I can spot these issues at a glance. This is the hardest part for developers with pure frontend backgrounds or those new to vibe coding. Task Types I'm Best Suited For: Payment/order/transaction bug fixes (Stripe integration, payment callbacks, order state issues). Code review focused on security vulnerabilities, database performance, and error handling. Debugging AI-generated backend logic, especially vague problems like "the app runs but the data is wrong." Delivery Style: I write reports in language non-technical founders can understand. Not just "changed function X" — I explain what the problem was, why it happened, what I changed, and what the user needs to do next (e.g., "go update the webhook URL in your Stripe dashboard").