On June 2, 2026, a news story sparked heated discussion across the internet—during his visit to Hangzhou, Lao President Thongloun personally operated a domestically produced humanoid robot. In front of the camera, Thongloun operated the robot's arm to flexibly grasp objects, and from his expression it was clear that he was surprised by the robot's dexterity. This news quickly climbed onto Baidu's trending searches.
Behind this seemingly "interesting" scene is a trend that many people have overlooked: Chinese humanoid robots have already left the laboratory and entered real interaction scenarios. From Hangzhou to Guangzhou, from Beijing to Shenzhen, robots are transforming from "exhibition demonstrations" into "productivity tools that can work."
At the same time, in the field of software development, AI is undergoing the same transformation. If 2024 was the "arms race year" for AI large models, and 2025 was the "year of open-source model popularization," then 2026 is undoubtedlythe first year of implementation for the deep integration of AI capabilities and intelligent hardware。
300% Software development efficiency gains brought by low-code + AI
65% Proportion of software enterprises that have used AI tools to assist development
one trillion 2026 global AIoT market size forecast
The key technical support enabling humanoid robots to "understand" instructions, "see" the environment, and "perform" actions correctly comes from AI large models. Traditional robots rely on pre-programmed fixed instructions to execute tasks, with extremely low flexibility. Robots equipped with AI large models, however, can understand human intent through natural language, recognize the surrounding environment through visual models, and adjust actions in real time through reinforcement learning—this means robots are no longer just "mechanical arms," but true "intelligent agents."
The rise of domestic open-source large models such as DeepSeek has accelerated this process. Open-source models have lowered the cost of acquiring AI capabilities, allowing small and medium-sized enterprises and hardware manufacturers to integrate top-tier AI capabilities into their own products. According to industry data, more than 2,000 enterprises are currently conducting secondary development and commercial implementation based on DeepSeek's open-source model, covering multiple scenarios such as intelligent customer service, educational assistance, industrial quality inspection, and health consultation.
Behind these application scenarios, without exception, solidsoftware developmentcapabilities are required. From custom development of robot operating systems (ROS), to the deployment of cloud-based AI inference services, to the development of mobile control apps—software is defining the "intelligence" of hardware.
Even more noteworthy is that AI is also feeding back into software development itself.
Projects that previously required a team of 3-5 people collaborating for a month can now be completed with 3 times the development efficiency using AI-assisted low-code development platforms. A team leader at a Shenzhen company engaged inWeChat Mini Program developmentshared a recent case: an e-commerce mini program containing user registration, product display, online payment, and logistics tracking functions was completed using AI-assisted tools in just 5 days, from frontend to backend, whereas the traditional development model would require at least three weeks.
The combination of low-code platforms and AI is changing software development at three levels:
For practitioners in the fields ofAPP developmentandWeChat development, this means the question is no longer "whether to use AI," but "how deeply to use AI." With the tools in hand, the gap in efficiency and quality is rapidly widening.
In 2026, the WeChat Open Platform officially released multiple AI capability interfaces to developers, including natural language processing, image recognition, and intelligent recommendations. This meansmini program developmentThe threshold has been further lowered—enterprises no longer need to build an AI algorithm team; they can directly call the AI interfaces officially provided by WeChat to inject intelligent capabilities into their own mini-programs.
Specifically, three major directions are most worth paying attention to:
Robots, smart homes, industrial equipment—more and more of the physical world is being connected to the digital world through sensors. According to industry research reports, by 2026 the global AIoT (Artificial Intelligence Internet of Things) market size will exceed one trillion yuan.
The core driving force behind this growth is the maturity of edge AI. In the past, data collected by IoT devices needed to be transmitted to the cloud for processing, which had problems such as high latency, high bandwidth costs, and data security risks. Today, edge AI chips allow devices to complete data analysis and inference locally, reducing latency from seconds to milliseconds.
In this field,IoTplatform development is becomingsoftware developmentan important sub-track. Specific needs include device registration and management, data collection and cleaning, AI inference model deployment, alerting and monitoring systems, etc. For those withIoTandbig data analysissoftware development teams with technical reserves, this is a rapidly growing market.
Over the past two decades, enterprise digitalization has mainly centered on the construction of management systems such as ERP and CRM. Entering 2026, enterprises are no longer satisfied with "moving offline processes online," but instead pursue "using AI to reconstruct business logic." Currently, enterprises are at different stages of transformation:
For those seekingenterprise digital transformationfor organizations, understanding the stage they are in is crucial. Different stages require different types of digital partners—low-code development is suitable for quickly validating ideas, custom development is suitable for building core competitiveness, and AI-native reconstruction is suitable for future-oriented strategic layout. What kind ofShenzhen software developmentservice provider is chosen often determines the pace and quality of transformation.
This transformation is also reshaping the SaaS industry. The traditional "forms + database" SaaS model is being replaced by "conversational AI services." Users no longer need to navigate through layer after layer of menus to find features; instead, they simply tell the AI Agent "what I need." AI-driven automation brings the marginal delivery cost of SaaS companies close to zero, forcing a fundamental shift in the entire industry's pricing model.
Take cross-border e-commerce SaaS tools as an example. In the first half of 2026, a large number of integrated AI product selection + intelligent customer service products emerged. By using AI to analyze data on millions of products across global e-commerce platforms, they automatically identify hit trends and generate supply recommendations; after intelligent customer service robots handle common inquiries, human agents only need to deal with highly difficult issues. In less than a year, these AI-native SaaS products have already captured more than 30% of the market share.
AI-nativeE-commerce platform developmentis no longer just "building a website or APP," but a systems engineering effort that includes a series of technical components such as AI recommendation engines, intelligent inventory management, and automated marketing.
Based on current trends, the software development field from 2026 to 2028 will show a clear evolutionary path:
Software developers need not only traditional programming skills, but also an understanding of AI model invocation, fine-tuning, and continuous optimization, possessing composite "AI + software" capabilities. For enterprises and developers, now is exactly the window period to embrace AI transformation—delay one step, and it may mean being one position behind a competitor.
From the Lao leader laughing uncontrollably while operating a robot in Hangzhou, to low-code platforms making software development 3 times faster, to the WeChat ecosystem opening AI capabilities to every developer—in the first half of 2026, these signals jointly point to one conclusion: AI has already moved from "being able to chat" into an era of "being able to work." For enterprises, choosing the right software development and digital service partner now will directly determine their competitive position over the next three years.
The implementation of AI does not only happen on robots, but also in every mini program, every management backend, and every data stream on every production line.
This article was generated by Xiangming Technology's AI content system | Official website:https://www.xiangmingit.com
Focusing on: software development, WeChat development, mini program development, APP development, IoT and smart community solutions
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