Zhu Hao from Lide AI: Bridging the Talent Gap in AI Implementation with Underlying Technologies
Introduction
Under the wave of AI, two long-standing contradictions have persisted: brick-and-mortar merchants invest budgets in AI transformation, but most of them only get access to tools, and can hardly convert these into stable customer leads.
The market is clamoring for a shortage of AI talents, but a large number of practitioners who have studied AI lack the ability to implement commercial applications, and cannot match the actual needs of enterprises.
Targeting the pain points of difficult AI implementation and mismatch between talent supply and demand, Lide AI, led by Zhu Hao, former UI engineer of Baidu R&D Center in Shanghai, has launched practical AI talent incubation and enterprise accompanying operation services in Wuhu.
Relying on the technical accumulation of leading tech companies, the team avoids the templated routines of most AI training and agency operation services on the market, and tries to build a closed-loop service system connecting universities, individual learners and brick-and-mortar enterprises.
I. Targeting the Supply-Demand Mismatch: Starting from Wuhu to Build a Regional Demonstration Model
Lide AI takes Wuhu as its core test base, and has established school-enterprise cooperation with Anhui Normal University, Anhui Polytechnic University, local industrial parks, communities and relevant government and public institutions, opening up the whole chain of AI talent incubation, practical training and talent delivery.
Considering the awareness level and payment rhythm of brick-and-mortar merchants in third- and fourth-tier cities for AI services, the team did not choose the extensive full-domain promotion, but cooperated with partners in other cities such as Foshan and Nanning, relied on the local matrix of WeChat Channels to accumulate content, took Wuhu as a demonstration sample, and replicated the mature operation model to other regions.
Different from players that focus purely on tool sales and short-term AI courses, Lide AI does not start from teaching users to use AI tools, but designs the entire training and accompanying operation process centered on "commercial monetization".
II. Building Differentiated Barriers: Self-Developed System, Rejecting Conceptual AI Services
In an industry environment where most players pile up tools and create gimmicks, the core barriers of Lide AI come from its self-developed system and implementation-oriented orientation: the 3322 Customer Acquisition System for Xiaohongshu Blue V B-end independently developed by team leader Zhu Hao has obtained national copyright protection. This system is not a single AI prompt skill, but a full-domain customer acquisition SOP adapted for local brick-and-mortar merchants. At the same time, the team independently develops lightweight AI applications, which under the same output effect, consume less Tokens than general large model solutions, and are suitable for small and medium-sized enterprises for long-term use at low cost. Zhu Hao, the head of the team, has 15 years of full-link practical experience in the Internet industry, is proficient in UI design and front-end development, and is responsible for the company's traffic operation and customized development of AI agents. The other two co-founders: Teacher Yanyang, a 20-year veteran in the brick-and-mortar business sector, is deeply involved in entrepreneur circles, government-enterprise and university resource integration, and is responsible for converting hard-core technologies into commercial implementation results. Teacher Zhao Rongbo, former founder of Shanghai Xuanmei Hardware Factory, has 15 years of front-line operation experience in the manufacturing industry and 10 years of experience in education and training, has a deep understanding of the pain points of brick-and-mortar businesses, and is responsible for converting AI technology into productivity. This is the foundation for the team to deeply participate in accompanying enterprises to operate projects, rather than only outputting courseware.
III. C+B+G Collaborative Closed Loop: Two-way Mutual Empowerment Between Talent Incubation and Enterprise Accompanying Operation
On the business side, Lide AI has formed a mutually guiding model for three types of businesses:
For individual professionals at the C-end, it offers AI practical training camps and one-on-one diagnosis, to train students to have AI implementation capabilities that can take orders, with the goal of outputting practical talents who can directly undertake the needs of merchants;
For brick-and-mortar enterprises at the B-end, it provides AI customer acquisition accompanying operation and full project planning, builds exclusive AI agents and local traffic matrix for enterprises, implements content production and lead conversion, and takes actual customer lead results as the delivery standard;
For the G-end and universities, as an intermediate docking channel, it undertakes school-enterprise practical training, and delivers AI talents with commercial practical training to enterprises in a targeted manner.
At present, the project has completed the minimum closed loop: trainees of the training camps have successively realized monetization by taking orders, and cooperative enterprises have also obtained effective local leads, which verifies the feasibility of this model.
Conclusion
The industry continues to be optimistic about the AI enterprise service track, but many projects only stay at the tool layer.
In Zhu Hao's view, AI is only a carrier to improve efficiency, and what is truly scarce is AI execution talents who understand business and can deliver practical results.
Lide AI's short-term goal is to consolidate its local brand in Wuhu, and polish the standardized incubation and accompanying operation process; in the medium and long term, it plans to expand to surrounding cities, gradually set up service stations in first-tier cities, and deliver the market-verified AI implementation system to enterprises and practitioners with real business operation needs.