In the second quarter of 2026, an industry news story went viral in tech circles: a warehousing and logistics company, in actual operations, deployed humanoid robots that completed the sorting and handling of more than 40,000 packages in just 33 hours. Behind this is an intelligent scheduling system driven by AI Agents—it does not require manual programming, but instead uses natural language to describe tasks, automatically breaks down execution steps, and coordinates multiple robots to work together.
At the same time, Unitree Technology's humanoid robot demonstrated calligraphy in front of the President of Myanmar, with brushstrokes so smooth that diplomats present were amazed. Although DeepSeek's image recognition capability occasionally has humorous moments of misidentifying people, its ability in code generation has already formed a de facto standard in the developer community.
These seemingly scattered events point to the same trend:AI is moving from "can chat" to "can work". What does this mean for enterprises?
In 2025-2026, AI Agents are no longer just a discussion topic in tech circles. Gartner predicts that by 2027, 40% of enterprise applications will have built-in AI Agent capabilities. And reality is arriving faster than predictions.
In the field of enterprise software development, AI Agents can already independently complete requirements analysis, code generation, test automation, and deployment and operations. This is not a lab demo. In Shenzhen, several technology companies have already embedded AI Agents into their daily development processes.
In the traditional software development cycle, AI Agents can compress requirements communication and coding by more than 60% of the time. This means that a project that would require a 3-person team to spend a month completing can now be delivered faster.
Low-code platforms themselves have already lowered the development threshold, but when large AI models are embedded into low-code platforms, a qualitative change occurs.
In the past, building aWeChat Mini Program developmentrequired 1 front-end developer, 1-2 back-end developers, and coordination with designers, taking at least 2-4 weeks. Now, through AI-enhanced low-code platforms, the same functionality can be prototyped and delivered for testing within 2-3 days. This is a 300% improvement in efficiency—verifiable real industry data.
For Shenzhen software development companies, this means a profound shift: competitiveness is no longer "who has more people," but "whose toolchain is smarter." Teams that are the first to integrate AI into their development pipelines are capturing market share at 3x speed.
Core Insight:The combination of low-code development platforms and AI is shifting the competitive focus of software development from "coding ability" to "business understanding + tool combination ability."
Traditional SaaS software is undergoing a "dimensionality reduction strike." Over the past five years, the core competitiveness of SaaS products was comprehensive features, a good interface, and stable service. But in 2026, AI-native applications—applications designed with AI as the core from the outset—are redefining the measurement standards.
A typical example is cross-border e-commerce SaaS. Traditional ERP + customer service systems require manual product selection, manual replies to common questions, and manual analysis of inventory data. AI-native cross-border e-commerce SaaS, however, can achieve AI automatic product selection (based on market trend forecasting), intelligent customer service (real-time multilingual response), and automated inventory scheduling. The efficiency and cost gap between the two is not a 10% level optimization, but a 5-10x generational gap.
From a broader perspective, enterprise digital transformation is shifting from the stitched-together model of "old systems + AI plugins" to a comprehensive reconstruction of "AI-native architecture." The old approach of adding an AI chat window to ERP software is being replaced by AI-native systems rewritten from the ground up.
The WeChat Mini Program ecosystem upgraded again in 2026, opening more powerful AI capability interfaces to developers. Today'sWeChat Mini Program developmenthas changed from "writing code" to "configuration + fine-tuning."
Developers use natural language to describe functional requirements, AI generates page structures, interaction logic, and back-end interfaces, and then only key business logic needs fine-tuning and customization. This has not replaced developers, but allows them to focus their energy on things that truly create value.
The IoT + AIoT market is expected to exceed one trillion in scale in 2026. The addition of AI Agents has enabled IoT systems to move from "can see" to "can decide."
Takingsmart community solutionsas an example: AI-driven access control systems not only recognize faces, but also predict anomalies through behavior analysis; property management platforms automatically schedule cleaning and maintenance personnel based on historical data; parking systems adjust guidance strategies based on real-time traffic. The development complexity behind these scenarios is extremely high, but the AI toolchain is moving the construction of smart communities from "custom development" to "platform-based delivery."
Traditional enterprise management systems (ERP, CRM, OA) are undergoing a transition from "process-driven" to "intelligence-driven." An obvious trend is that more and more enterprises, when starting new projects, no longer ask "can this function be done," but ask "can this be done automatically with AI."
Enterprise digital transformation's next stage is to re-examine every business process: which ones require human decision-making? Which ones can be handed over to AI Agents? The answer is often—the most cumbersome, repetitive, and information-asymmetric parts of the decision chain are the most suitable for AI intervention.
AI has lowered development costs, thereby expanding the range of serviceable customers—needs from small and medium-sized enterprises that were previously shelved due to insufficient budgets are now feasible again.
Observations from Shenzhen's IT industry show that those who actively embrace AI toolchainssoftware developmentcompanies saw order volumes increase by more than 60% year-on-year in the first half of 2026. The key is—not using AI to replace people, but using AI to double the output of the same people.
AI will not make developers unemployed, but developers who use AI will put pressure on those who do not.
From a tech stack perspective, the new capabilities developers need in 2026 include:
The combination of low-code development platforms and AI tools is lowering the threshold for "being able to write code," but at the same time raising the threshold for "being able to design good systems." Programming is increasingly like "translation," while the real value lies in understanding the business, designing architecture, and making the right technical decisions.
If your company is considering AI transformation, the following directions are worth prioritizing:
Looking back at the technological evolution of the past 18 months, AI Agents have gone from a "novelty" to "infrastructure." Low-code platforms + AI have brought a qualitative leap in software development efficiency, the SaaS industry is being reshuffled by AI-native applications, IoT platforms have added intelligent decision-making capabilities, and enterprise management is moving toward AI-native architecture.
This transformation has only just begun. For enterprises, the question is no longer "whether to embrace AI," but "how to integrate AI into existing business as quickly and cost-effectively as possible."
And for technology service providers like Xiangming Technology, the mission remains the same: to help customers find the digital transformation path that best suits them in this AI-native era, and to use software development capabilities to create real growth for their businesses.
This article is produced by the Xiangming Technology content team. Reproduction is welcome.
Official website news first release:https://www.xiangmingit.com/gsxw/gsxw_20260619.html
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