Three stages, one turning point
Over the past decade, corporate website building has gone through three stages.
The first stage was "having a website." Pick a template, put up a few pages, and launch. The core demand at this stage was "presence"—when customers searched for the company name, they shouldn't see nothing at all. The website was a static storefront, and once it was done, there was basically no need to manage it.
The second stage was "the website has to be useful." Responsive design, mobile adaptation, SEO optimization, and data analytics began to be taken seriously. Companies realized that a website wasn't finished once it launched; it was an acquisition channel that needed continuous maintenance. The hallmark of this stage was: customers started asking, "Why isn't my website getting traffic?" rather than only "When can my website go live?"
The third stage is the stage we are in now. A website is no longer just a page for people to look at, but an outlet for a company's digital assets—the same set of content can have multiple outlets: an official website, mini programs, and other channels; the same set of data can be read and used separately by pages, by programs, and by AI.
The turning point of this shift lies in a change in perception: companies are beginning to realize that the content and data they have accumulated are themselves valuable assets, not appendages of the website.
Once perception changes, website-building products that originally looked similar in the market quickly diverged into several different paths.
Three Paths, Three Trade-offs (Part One): Tool-based SaaS Website Building
Representative examples are the various self-service website-building platforms—register, choose a template, drag and drop to edit, and you can go live the same day.
The core problem it truly solves is "bringing the technical barrier to building a website down to almost zero." For businesses, this means they do not have to find a technical team or understand servers and code, yet can still have a website that looks presentable. This value should not be underestimated; the first version of the official website for the vast majority of small and medium-sized enterprises should take this path.
But its boundaries are equally clear, and these boundaries often only begin to emerge in the second year:
First, the boundaries of capability are determined by the platform. What you can do depends on what the platform has predefined. When a business wants to implement a feature the platform has never offered—such as integrating product data with its own ERP, or organizing the content structure according to its own business logic—there are usually only two choices: accept the limitation, or start over from scratch. A platform will not change its product for one customer's needs.
Second, data is hosted on the platform. Content, case studies, and leads submitted by customers are all stored in the provider's system. This means two things: first, export and migration are often restricted; second, your digital assets sit on someone else's foundation. Changes in platform policies, plan expiration, and changes in the provider's business can all affect you.
Third, the homogenization of templates. The same set of templates may be used by hundreds of businesses. Visually, you can change the color scheme and images, but the underlying information structure is the same. When customers all have the structure of "Home + About + Products + Case Studies + Contact," differentiation can only be made up for through content and design, and it is precisely in these two areas that the platform offers the least freedom.
To sum it up in one sentence: Tool-based SaaS trades "the ceding of capability and control" for "advantages in speed and cost." This is a worthwhile trade, provided you are clear about what you have given up.
Three Paths, Three Trade-offs (Part 2): AI One-Shot Site Generation
A new form that has emerged in the past two years. Input a company's information, and AI generates a complete, fairly professional-looking website within minutes.
The efficiency breakthrough here is real. Work that used to take designers and front-end developers several days now produces a first draft in minutes. For needs such as "quickly validating an idea," "a temporary event page," or "just having something to see the effect," it is almost the current optimal solution.
But there is a structural characteristic that needs to be made clear: The moment generation is complete, the work is basically over.
The design logic of such products is "deliver a finished product in one go," rather than "continuously maintain a system." The chain reactions this brings are:
Difficult to update. A website is not static. Products need new items, teams need new members, cases need updating—but generated sites often lack a structured backend that facilitates long-term maintenance. Change it once, and you may need to regenerate it once.
Difficult to integrate. A company's website will sooner or later need to interact with internal systems—forms need to go into CRM, products need to sync inventory, content needs to be shared with other channels. Generative sites usually do not reserve interfaces for "being called."
Assets cannot accumulate. Every time it is generated, the content starts over. The content, adjustments, and optimizations accumulated in the previous version cannot naturally carry over to the next version. The company's investment becomes consumption, not accumulation.
This judgment is not a denial of it, but a clarification of applicable scenarios: It suits "one-time" needs, not "long-term evolution" needs. The difference between the two should be thought through at the moment the need is proposed.
Three Paths, Three Trade-offs (Part 3): Building an In-House Content Middle Platform
Build the content structure first, then decide which front ends to use for presentation. This is a heavier and slower path.
Its core idea is “separation of content and presentation”: articles, products, cases, people, and forms are first modeled in the backend into structured data; the official website, mini programs, and other channels are all different ways of rendering the same set of data. Change content once, and all front ends update in sync.
Its cost is a high upfront cost. Enterprises must think clearly about the content model at the start—how products are written, what categories cases fall into, and how the team is organized. This is counterintuitive for many enterprises: they are used to “having a page first,” not “having a structure first.”
Its returns show up in the latter half:
When an enterprise wants to expand from “one official website” to “official website + mini program + multilingual site cluster,” it does not need to build everything again; it merely adds rendering outlets; when content is to be handed to AI to understand and use, structured data is naturally friendlier than scattered pages; when the business changes and the structure needs to be adjusted, what changes is the model, not hundreds of pages.
In one sentence: a self-built content middle platform trades “upfront thinking and investment” for “long-term freedom and asset accumulation.”
For these three paths, there is no absolute superiority or inferiority—the difference lies only in two points: what the enterprise is willing to hand over, and how long it expects this thing to be used. A display site intended to be used for only one year, and a digital foundation meant to support the next five years, should not use the same solution in the first place.
An often overlooked criterion: whether AI can actually "touch" your content.
For more than a year now, almost every website-building product has added the word “AI.” But the way AI is integrated into a system varies enormously, and that difference is exactly what determines the real ceiling of AI capability.
The first approach is “skinning.”The original system remains completely untouched, with a conversational entry point wrapped around it. Users ask it questions, and it searches existing content, generates copy, and offers suggestions.But it cannot see or change the system’s internal data structures—it can talk, but not act.
The ceiling of this approach is obvious: AI’s capability equals how thick that shell is made. No matter how thick the shell, it cannot solve a fundamental problem—AI is not a member of the system, but someone standing outside the door shouting through a window.
The second approach is to make AI a “formal caller” of the system. It is not an add-on feature, but is accepted by the system like an internal employee: with a clear identity, clear permission boundaries, able to read content, query data, create pages, and upload assets.
This second approach places much higher demands on the system. It requires the system to assume at the design stage that external programs will call these contents in agreed ways. Once this assumption is established, it will in turn affect all structural design—how data is modeled, how permissions are divided, how interfaces are exposed—all must be thought through in advance.
Conversely, if the system was initially designed “only for people,” and only later wants to be used by AI, then it can only be patched. No matter how good the patches are, they cannot patch together a foundation designed for openness.
This is the real dividing line for “AI capability”: not how fluent the conversational interface is, but whether the system is designed to be “called.”A key criterion for judgment is: In this system, is AI a visitor or a member?
HOLYPro's Choice
HOLYPro has spent ten years providing enterprise digital services. We have resold every kind of website-building product, and we have also built our own digital platform. We are familiar with both models, so our choice is all the clearer.
In the end, we defined our self-developed digital platform as a combination of "content middle platform + private deployment + open capabilities," based on three judgments:
1. Data sovereignty should not be surrendered unconditionally.
The content, case studies, and customer leads on an enterprise website are assets accumulated over the long term. They should not be reset to zero because of a platform policy change, a switch of service providers, or an account expiring. Private deployment means this system runs on the customer's own servers, the data belongs to the customer, and migration depends on no one. This is not technical showmanship; it is about making "asset ownership" clear instead of vague.
2. AI capability should be a fundamental property of the system, not a bolt-on feature.
The digital platform is open by design at its foundation: a single declaration determines the exposure of both REST interfaces and MCP (Model Context Protocol) tools. This means that every time a content type is added, manual operation capability and AI invocation capability become available at the same time, with no need to maintain two sets of logic or to build extra development just for AI. The platform currently exposes 38 tools externally — 25 read-only, 12 write, and 1 login authorization — with clear permission boundaries: read-only tools have the same permissions as anonymous visitors (they cannot read drafts or private content), write tools are divided into permission points by role, and system-level and employee-level credentials are managed separately. The purpose of this design is to make AI's capabilities as great as possible while making its boundaries as clear as possible.
3. The system should be able to grow together with the enterprise.
An enterprise's digital needs come in stages: first a website, then content operations, then customer acquisition, data, and AI applications. If every step up requires tearing down and rebuilding, the costs recur again and again. The idea of the content middle platform is to advance the foundation, the construction, and the growth in layers — building a website today, adding a mini-program tomorrow, and connecting an AI customer service the day after, all stacked on the same base, without having to start over. The 1000+ delivery cases of the past ten years have given us a fairly concrete sense of how enterprises grow.
We also make clear what we don't do.
Talk about choices, but also about boundaries. Digital platforms are not the answer for every company, and we don’t want to present them as a solution that can solve everything.
If the need is “to launch a showcase website within a week, with a limited budget, and no intention of doing content operations in the short term”—then a tool-based SaaS is the more suitable choice. We also represent this type of product ourselves, and we won’t persuade every client to adopt private deployment. Lightweight needs call for lightweight solutions—that is what it means to be responsible to clients.
If the need is “to quickly validate an idea or create a temporary campaign page”—an AI-generated site or a template site is enough; there is no need to adopt a heavyweight system. Using heavyweight tools for lightweight tasks is a waste; using lightweight tools for heavyweight tasks is a hidden risk.
The value of private deployment only truly holds when the following premises are all true at the same time: content will become a long-term asset, data needs to remain in your own hands, the system needs to continue evolving, and the company is willing to spend a little more time at the beginning to think through the structure clearly. If the premises do not hold, the investment is a waste—even if it is technically entirely feasible.
So we would rather return the criteria for judgment to business owners, and replace a recommendation with one question:
What do you want this website to look like three years from now?
If the answer is “still like it is now, as long as it’s enough,” then a lightweight solution is better—it saves money and effort; if the answer is “it will carry more and more things and be the entry point for the company’s digitalization,” then the foundation is worth solidifying from day one.
Both paths are right; what’s wrong is using the standards of one path to judge the other.
Final Thoughts
Enterprise website building is shifting from "delivering a finished product" to "building a system that can grow."
Part of the driving force behind this shift comes from AI. When AI begins to be able to directly operate content, the value of a website is no longer just "being seen," but "being invoked"—it becomes a node in an enterprise's digital assets that can be read and written by programs and understood by AI. A website that can only be viewed by people, and a website that can both be viewed by people and used by machines—the value gap between them will gradually widen as AI becomes more widespread.
What HOLYPro is doing is lowering the threshold for this: enabling enterprises to have a digital platform with data autonomy, open capabilities, and continuous growth without having to build their own technical team. Ten years of delivery experience tells us that what enterprises need has never been the most advanced technology, but the most suitable path.
To sum up our judgment in one sentence—
Underlying capabilities can be complete, but when delivered into people's hands, they should be restrained.
This sentence is both our understanding of products and our observation of the industry. Complete capabilities are for accommodating future changes; restrained delivery is for making them easy for people today to use. The two are not contradictory; they are exactly what a mature product should be like.