Who ever had a good idea about the request, only to face this reality fear of developmentwhich may take weeks, or even months. The journey between an idea and a working product can be exhausting. Think you could fit that whole process into the time you spend with a cup of coffee? It is not a dream out there in the future.
This article describes the process of building a fully-fledged personal productivity agent, with a single input to a fully functional application, in five minutes using the GLM-5 AI model on the Z.human platform. Journey represents a new wave of AI development, as the speed of creating an MVP program is very low.
What is the GLM-5 AI model?
The GLM-5, the flagship base model of Zhipu AI, is at the center of this rapid development. It’s a big step forward for traditional AI assistants with coding skills. GLM-5 is intended for so-called Agentic Engineering. This means that it is a self-driving business that can understand high-level goals, design multi-faceted actions, write code, and solve problems on its own.
GLM-5 is designed to manage the software development life cycle. Trained with extensive coding and engineering knowledge, he can create project architectures, manage databases, and build APIs and user interfaces. Its ability to think through problems makes it a powerful partner for developers who want to move quickly. On the Z.ai platform, it runs within an integrated environment with access to the file system, terminal, and editor, allowing it to perform tasks seamlessly on its own.
Constructing a production agent using GLM 5
We will build a fully implemented application with Vibe Coding using only the Z.ai platform. With that, we head over and select the GLM 5 model from above. Also enable “Agent” mode to be able to create files using Terminal in the Cloud.
First step: Thinking about the App
This project started with a simple, high-level command: “Start with thoughts about a Human Productivity Agent. Then build an MVP version of that.”
This was the beginning of the process. The GLM-5 AI model did not start coding. The first thing he was able to produce was a structured plan. Based on this plan, the main idea was expressed, the most important aspects were discussed, and the scope of the MVP plan was established. GLM 5 can also be asked to be discussed and in the second iteration the MVP is developed. However, we tried to test the agent functions of GLM 5. So we threw two composite functions into one.
The result of AI created features in logical categories. These were task management, time management and analysis. After that he chose the reduced set as the basis of the working product. This is one of the planning stages of agent AI development. Ensures that the final product matches the original idea and any code is written.
Construction Process and Unexpected Obstacles
GLM-5 started the development phase with the approved system. It started with creating the project architecture and defining the database schema. It is done transparently where all files are created and edited in the integrated editor. The model was intended to use a backend followed by a user interface.
But progress is never a straight line. An error occurred in the process. There was a final Prisma database schema drift error message detected. The disk database failed to match the migration history of the model. This is an everyday problem in real world development. It was a true test of AI’s problem-solving prowess.
Smart Returns
The build process is stopped. Given a simple command to follow:
“What happened please continue building”
A GLM-5 artificial intelligence model analyzed the error message. It rightly recognized the need to recalculate the database and delegated this action. It then moved forward without human intervention.
This scene shows a major advance in the development of agent AI. The model did not fail but recognized the error condition and implemented a solution. After resetting the database, it systematically generated API routes, built the main dashboard, updated the design and even created a custom app logo.
Final Product: Declared MVP
The MVP application was completed and required approximately five minutes from the initial notification. The result was a global production agent for the individual. It featured a slick dashboard, intelligent task management with natural language communication, Pomodoro timer and AI Advisor.
The app had the advanced features mentioned in the discussion section. E.g. urgent tasks are assigned priority. It was possible to add hashtags like #work to tag jobs automatically. The entire process from an idea to a functional and fully featured web application has shown an unprecedented speed of development. The Z.human platform provides the integrated environment required for this smooth workflow.
It uses the Application
The Z.ai platform makes deployment incredibly easy. After the AI is built, no complex configuration files or shell scripts need to be maintained. The only thing you need to do to use the application is to press the “Publish” button in the upper right corner of the interface. This action alone will deal with all submissions. In a few seconds you have a hack containing a new unique URL and this adds to your app’s instant availability on the Internet.
Link:
Application Testing
The app is live, so now it was time to test the main functions. I Quick Add Function it was working again. Typing Research about AI agents immediately opened a new task and used the Urgent priority tag, which was relevant because it was tagged with the right keyword like natural language. Another task was also introduced, and it is called Complete assignments, which is shown with a fixed value of In the middle.
Focus Timer was also useful. When the 25-minute Pomodoro timer is started by clicking the button Start button, it started counting down as expected.
The best test was the “AI Assistant.” Answering the question, the assistant showed awareness of the real context when he answered, can you help me to continue my duties. It was very clear in listing the two pending tasks and their priorities. It then volunteered to help them prioritize or break it down into smaller steps that reflected the smart and useful aspect of the original plan.
The conclusion
This five-minute development cycle is not only a novelty but it is indicative of a new phase in software development. This is a practical (and, possibly, final) estimate, based on experience with GLM-5. These tools also have the advantage of automating the tedious work of coding, debugging, and implementation, allowing human developers to focus on doing what matters. The software does not aim to replace software developers, but rather to empower them with the help of unusually powerful AI.
Frequently Asked Questions
IA. GLM-5 is the most robust model of the Z.human base. It focuses on agent functions and complex code, enabling it to create applications independently.
A. The Z.ai platform is an integrated development platform. It also provides access to Z.ai models, such as GLM-5, for building, testing, and deploying AI systems.
A. It took about five minutes to make the initial idea into a used and functional system.
Harsh Mishra is an AI/ML Engineer who spends more time talking to Large Language Models than real people. I am interested in GenAI, NLP, and making machines intelligent (not to replace him yet). If he doesn’t use models well, he might be increasing his coffee intake. 🚀☕
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