🤖 AI Engineer
AI Engineer helps teams with architecture, development, and delivery.
Problem
- The work still depends on a few people and is hard to repeat.
- Context is scattered across tools, so handoffs drop details.
Solution
- Map the workflow
- Connect the data
- Produce a result
- Review with a person
Live demo
Workflow demo · Phase one is a simulation so you can check the interaction and the deliverable. It will not write to your live CRM, WeChat, or store.
AI Engineer Demo
SimulatedTry the inputs and deliverables. Outputs are demo data—no production systems or live publishing.
Auto-playing workflow steps
- 1
Map the workflow
Running
- 2
Connect the data
Waiting
- 3
Produce a result
Waiting
- 4
Review with a person
Waiting
- 5
Deliver
Waiting
Workflow
- 01Take the input
- 02Understand the goal
- 03Call tools
- 04Produce a result
Architecture
Input
Business goal, Existing material, Constraints
Agent
AI Engineer
Tools
Business API, CI
Output
Findings
Implementation: LLM + Tool Calling
Input
- Business goal
- Existing material
- Constraints
Output
- Findings
- Next steps
- A draft a person can edit
Stack
- LLM
- Prompt
- Tool Calling
- Codebase
- CI
API
- Business API
- CI
GitHub
https://github.com/jnMetaCode/agency-agents-zh/blob/main/engineering/engineering-ai-engineer.mdEstimate
Reference range ¥8,000 - ¥25,000. This estimate follows the current scope and changes with how deep the integrations go. It is not a market list price.
FAQ
Who is AI Engineer for?
Teams that need help with architecture, development, and delivery.
How long does it take?
A reference timeline is 3-7 days. It changes with how many systems you connect.
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