Who It's For
Open to all enrolled students, regardless of major. We welcome students from technology, product design, business communication, foreign languages, and industry research to form teams that understand business and can deliver quickly.
AI Agents are becoming the new bridge connecting technology, business, and commercial delivery. FDE (AI Field Delivery Engineer) is not just about writing code, nor is it only pre-sales or product work; it is about going deep into real enterprise sites to complete requirement interviews, workflow breakdown, Agent / RAG / automation solution design, MVP delivery, and commercial validation. Led by Professor Zhang Shengli’s team at the College of Electronic and Information Engineering, this bootcamp has completed two cohorts and continues to connect enterprise problem statements, industry mentors, and project incubation resources.
The bootcamp is not just about teaching AI tools; it turns the FDE methodology distilled from meeting minutes into project-based training: starting from fuzzy requirements, going through requirement clarification, workflow modeling, solution design, MVP development, Demo presentation, and enterprise feedback.
This cohort will focus on introducing FDE case studies and real industry problem statements. Through the "University + Enterprise + FDE" collaboration model, students will transform AI capabilities into deliverable, verifiable, and reviewable project outcomes.
Open to all enrolled students, regardless of major. We welcome students from technology, product design, business communication, foreign languages, and industry research to form teams that understand business and can deliver quickly.
Two FDE exchanges have formed a core consensus: the barrier to AI delivery is not any single tool, but industry understanding, workflow breakdown, client communication, delivery stability, and commercial judgment.
The bootcamp helps students learn how to turn fragmented expressions from bosses, business staff, and engineers into developable and verifiable requirements; while understanding enterprise-level constraints such as permissions, logs, exception handling, data privacy, and on-premise deployment.
Every project must think about how much time, risk, and revenue it saves for the client, and form templates for requirements, workflow, cost, ROI, acceptance, and review to avoid staying at one-off demos.
Enterprises provide small and clear real needs; FDE / industry partners help clarify; instructors lead student teams to complete 1-2 week Demo / MVP; then enterprises evaluate whether to continue projectization, internships, or incubation.
Around enterable enterprise scenarios, quickly complete industry understanding, business process mapping, AI transformation entry-point design, and a small Demo, using real feedback to train FDE judgment and delivery capability.
Cohort 3 focuses on large language model (LLM) application deployment in real industry scenarios, prioritizing 9 directions including cross-border e-commerce, supply chain, industry, HR, ad optimization, knowledge management, and smart office.
For enterprise problem statements, mentor collaboration, project pipeline, or course co-design, please reach out through the contact channel below.
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