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03 / Real QQ business use · Local simulated WeChat prototype

AI Community Support Assistant

From repetitive answers to a support process others can take over

RAGContext designBusiness support
My roleRequirements analysis · Product proposal · AI prototype implementation
Project timelineTo be added
Evidence of deliveryQQ · Real business use for answering inquiries
AI Community Support Assistant / 03↳
01Group questions
02Knowledge lookup
03Human escalation for complex issues
Workflow diagram · Not a product screenshot
01 / CONTEXT

The problem

Groups repeatedly received questions about product use, redemption steps, and account issues. Standard questions needed support, while complex issues needed accurate handoffs to a human.

02 / MY CONTRIBUTION

What I did

  1. Broke down QQ business inquiries into multi-turn follow-up questions, initial troubleshooting, business knowledge lookup, and human handoff prompts.
  2. Used competitor research and conversations with practitioners to clarify requirements such as message deduplication, @mention/quoted-message triggers, and context completion.
  3. With AI-assisted coding, built a local simulated WeChat MVP using webhooks, a task queue, and workers, completing message intake, model processing, simulated sending, and logging.
03 / OUTPUT

Deliverables & results

The QQ group AI support assistant was used to answer standard questions in actual business operations.

Completed the WeChat product proposal and local simulated workflow.

04 / VALIDATION BOUNDARY

What has been validated

Real QQ business use and the simulated WeChat prototype are presented separately. Sending and receiving messages in real WeChat groups, third-party callbacks, extended operations features, and long-term operating metrics still need validation.

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