Which Software Will Become Unnecessary? ChatGPT and Claude Are Already Building It
Which familiar CMS, CRM, forms, bots, and SaaS tools can already be replaced by a system assembled by AI for a specific workflow—and where does custom development remain risky?
Understand when it is better to buy an existing service and when to build a custom system around data and business processes—and which limits of models, integrations, regulation, and human review cannot be ignored.
What to watch for
Key takeaways
When a model can assemble a website, CMS, forms, bots, and analytics around one workflow, the familiar stack of separate services is no longer the only way to operate.
A website is not a laboratory demo but a mass-market gateway to the internet. If AI changes how websites are built and managed, the same logic will gradually reach mobile apps, CRM, and ERP.
GPT-5.6 Sol can work for days and run parallel threads, but duration alone does not prove quality. Scale of work must be separated from slowness and uncontrolled resource use.
The choice among CMS, open source, and cloud software changes when Codex and Claude can build a function around specific data without requiring the business owner to inspect code.
A questionnaire should continue across the website, Telegram, WhatsApp, SMS, or a call with a manager while preserving one context. A standalone form builder solves only a small part of the problem.
A system serving an international audience must account for GDPR, cookies, languages, channels, and analytics. Those details separate a demo from working infrastructure.
Payments, multiple cards, booking rules, accounting, and exceptions make the real process harder than the page. AI saves development effort only when it captures this operational logic.
Before buying another subscription or building another system, ask whether that layer will still matter in three to five years or become a standard capability of the AI platform.
What this episode is about
A large website, a custom CMS, forms, a contact database, analytics, and campaign-specific landing pages can already be assembled through Codex, ChatGPT, and Claude. This episode is not a “website in five minutes” demo; it is about a shift in the economics of software itself.
The Experiment Started with a Large Live Website
I took a large live website with hundreds of pages and gave the AI systems a practical task: move it into a new environment, understand its structure, preserve the content, and build a custom management system around it. Codex parsed the website, the models helped assemble the architecture, and Claude Fable and GPT-5.6 Sol were used for different parts of the process. This was not a laboratory example or an empty landing page; it involved real volumes of material and real requirements.
AI Is Beginning to Build an Entire Working Environment
A project like this quickly becomes more than a website. The system can create page templates, separate landing pages for products, countries, states, and advertising campaigns, forms and questionnaires, a contact database, internal analytics, bots, and publication rules. Previously, each layer required a separate SaaS product, another integration, and another subscription. A model can now assemble many of those functions inside one system tied directly to a specific business process.
The Main Question Is Not Whether One CMS Disappears
This does not mean every CRM, CMS, and website builder disappears tomorrow. Current models still make mistakes, consume expensive tokens, operate at different speeds, and require human supervision. But the value of the standard software layer is changing. If a business can quickly build its own form, report, or dashboard, it begins to evaluate a generic service, its limits, and its integration cost very differently.
The Investment Is No Longer Only in Software
The episode is therefore less about website creation than about deciding where to invest time, money, and attention. Should you buy another subscription, build a custom system, wait for the next generation of models, or learn to describe the process more precisely? AI can already perform a large amount of technical work, but a person still has to understand the business, set requirements, verify the result, and decide which functions are actually necessary. That becomes the main constraint as code and interfaces become faster to create.
AI does not eliminate software, but it sharply reduces the value of standard intermediary layers. The winning system is built around the real process, data, and accountability—not around another subscription.
Episode transcript
The episode is in Russian; below is an English reading guide to the transcript (the full EN transcript is a machine translation). Voice matching applied to 47 segments: 47 identified, 0 mixed, 0 marked with ✓, and 0 unresolved.
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