With the rapid development of artificial intelligence technologies, the position of ai product manager has gradually become a relic of the technology industry. A number of leading students, technical staff and senior industry-experienced product managers are planning the transition course。
But the ai product manager's track is not as good as it looks, for several reasons:
First sighting a. I. Product manager
There's a target. There's a problem
Many graduates/skillers know that the ai product manager has not been fully informed and that they have seen friends turning to ai, so they want to switch to ai product manager。
A large number of pieces of knowledge, such as ai smarts, ai+ applications, are available online, and then they learn how to enter the curriculum vitae and find jobs without receiving interviews. What's the problem
It's just that experience doesn't match job requirements。
You want to change the a. I. Product manager, what's the a. I. Product manager classified? What's the power model? What are the workflows
The individual advantage and past experience are then selected for professional upgrading in suitable areas to enhance matching。
Each individual is a product manager x starting class summarizing three types of ai product manager competency models based on market demand. Let's see what kind of ai product manager you're looking for
Category i, professional ai product manager, conducting large model product-related research in professional ai, large model company, large plant ai. Manager of background products suitable for advanced education, high technology (calculations, artificial intelligence, etc.)。
The second category of application level ai product managers, using mainly ai large models, ai technology, ai api and other ai capabilities, is a completely new ai application product, or adds ai functionality to existing products, requiring industry landscape insight, demand dismantling, commercialization and operational capability. Most of the ai product managers that are now being recruited by businesses refer to this category。
Master's degree and above, graduate in computer science/artificial intelligence, may give priority to professional ai product managers。
If you don't have a technical background, you don't have the best academic qualifications, but industry's experienced traditional product manager, who wants to seize the opportunity of ai, strongly advises you from the application level of ai product manager。
I don't know what type of ai product manager i'm looking for
Seeing here, you should know more about the a. I. Product manager, but how do you get in
Development of plans, production capacity, experience
The development of each sector has to go through the three stages of heavy technology, heavy products and re-operation, and the ai industry is now entering the second phase of product-priority, thus making the requirements for the ai product manager more stringent。
By dismantling several a. I. Product managers, j. D., we can find that these core skills are necessary to enter the business:
How does base line zero prepare? It is recommended that you quickly build your ai product capability system from these four dimensions:
Phase i: building api
1ai product capacity-building: the ability to transform bcg end-user needs/business pain points into ai product functions is the core basis for becoming ai product managers。
2 industry understanding & business insight: business logic is clear and ai is by nature a technology that serves business development. The ai product manager is familiar with business logic in order to know how to use ai enabling operations and which processes/business difficulties to optimize。
The product manager taught himself to run the field. Battalion
From basic to advanced, help your system to fill the gaps and make product capacity systematic。
Phase ii: building on the ai project landing experience
3 technical comprehensibility: without being conversant but understanding, the ai product manager needs to understand the process of technology realization and the technological boundary (know what ai can and cannot do). This will allow better integration of user needs with ai technology, optimize product design and accelerate product achievement。
There is an ai landing experience: the ai product manager serves a different client group, finance, education, government, health, etc., the project may have several hundred models, as well as a multi-sector client scenario fast-out product programme, where the quick-output solution for the industry can be produced quickly。
Special training camp for ai product manager
The system helps product students to improve their ait understanding, including mcp, rag, agent, manus, workflow, modelling fine-tuning, theoretical + practice models, rapid upgrading of technical understanding of products and insight into the ait technological boundaries to achieve ai enabling business
If you've acquired the above skills, congratulations on being a qualified ai product manager, you can try to see the ai product directly。
If you want to seize this wave of ai opportunities, but still lack the expertise to produce/ai, how do you start? Want a teacher to take his hand with him。
We can choose the new ones
Ia product manager transforms the field
Two days of high-density ai cognisance + field operations, leading to an efficient transition through the production of ai raw product projects that can be interviewed directly。
Ai, opportunities are always for people who can do it quickly and land quickly
