Is AI Coding a Dead End? The Software Market Is Systematically Collapsing — Why Learning to Code Doesn't Mean You Can Sell Products. From 'Consuming AI' to 'Business Builder': A Cognitive Shift and Action Strategy! AI Can Do 100 Things for You, But It Doesn't Know Which One Is Worth Doing!

Mon, 11 May 2026 17:40:00 +0800

Everyone is rushing to learn AI coding, as if mastering it guarantees software riches. Big-tech engineers are looking for an exit, product managers want to build their own MVPs, and non-technical people dream of getting rich through software.

But have you noticed something strange? The software you painstakingly built gets zero buyers once it goes online.

This isn’t a problem with your skills — the entire software market is undergoing an unprecedented “systematic collapse.”

Three Types of People All Fell Into the Same Trap

Let’s look at who is most eager to learn AI coding and what predicaments they each face:

Group	Motivation	Predicament
Big-tech engineers	Facing layoff pressure, hoping to become a “one-person company” after learning AI coding	Have the skills but don’t understand the market — no idea what to build that people will pay for
Product managers	Finally free from depending on engineers — just buy a `Cursor` subscription and build an MVP	After building the product, discover the market is saturated with no paying users
Non-technical people	Brainwashed by “make $50K in a week with software” videos, dreaming of getting rich	Product goes online with zero interest — lack deep understanding of industry needs

These three groups share one fatal trait:

They all treat “knowing how to code” as their moat.

Big-tech engineers have strong skills but don’t know what to build that anyone will buy. Product managers finally break free from engineer dependency, excitedly build an MVP, only to watch it sink in a red-ocean market. Non-technical people have it worst — they haven’t even figured out where the market is before diving in headfirst.

Software Supply Side: Explosive Growth

Why can’t anyone sell what they build? Because the number of people who can build software is exploding at an alarming rate.

Claude Code, Cursor, Codex, OpenCode — these AI coding tools have dropped the development barrier to historic lows.

Metric	Data
GitHub new repositories in 2025	121 million, averaging 230 new projects per minute
App Store submission growth in 2025	Up 24%
App Store submission growth in 2026	Year-over-year surge of 84%, the largest increase in nearly a decade
Apple review status	Review cycles stretched indefinitely due to the sheer volume of incoming software

When everyone can write software, software itself is no longer a moat.

In the past, developing an app required a professional team spending months. Now one person with AI tools can deliver in days. The supply side hasn’t just “increased a bit” — it has experienced explosive growth.

Software Demand Side: Cliff-Drop Plunge

While supply skyrockets, demand for purchasing software is experiencing a cliff-drop plunge.

Many software ideas can now be handled by AI Agents developed by large model companies — just add a SKILL, write some scripts connecting different services, and set up scheduled push notifications to fulfill most needs.

75% of traditional software demand has been directly eliminated by agents.

Even scarier, even users who used to pay for software have stopped buying. That browser translation plugin that cost $580 per year? Now anyone can build a replacement with AI in a single day.

So where did the money go? It all flows to Tokens — buying Claude subscriptions, buying GPT plans — users handle most needs themselves.

Dimension	Past (Pre-AI)	Present (Post-SaaS)
Development barrier	High — requires professional teams and months of R&D	Extremely low — AI-assisted delivery in days
Supply scale	Limited by the number of skilled professionals	Explosive growth (repositories counted in billions)
Pricing model	High-margin SaaS subscription	Zero marginal cost, Token-based pricing
Competition intensity	Stable market, 1:100 supply-demand ratio	25x to 100x extreme competition

Before, one company built software and sold it to 100 customers. Now 10 companies fight over 1 customer.

This isn’t just a little harder — it’s 50x to 100x more brutal.

Capital Markets Already Cast a Vote of No Confidence

If the data above doesn’t shock you enough, see what Wall Street has to say:

Event	Impact
`Claude` launches AI data analytics tools	`Thomson Reuters` drops 18% in a single day, `Gartner` drops 21%
Market value evaporated in one day	Over $280 billion
`Claude` launches AI design tools	`Adobe` and `Figma` stock prices plummet
S&P 500 Software Services Index	Overall decline exceeds 20%, with peak drop reaching 40%

Investors are telling you with real money: the golden age of SaaS is over.

This isn’t one feature defeating one product — the entire software industry is experiencing a systematic collapse.

The Market Hasn’t Disappeared — It’s Transforming

If selling general-purpose software is a dead end, where did the demand go?

The answer: the enterprise agent market.

In the past, when enterprises wanted to digitize, they’d buy ERP, buy CRM, hire outsourcing firms for custom development — easily spending hundreds of thousands to millions, with implementation cycles of six months to a year. After spending big, the systems were cumbersome, and companies often reverted to Excel.

Now? A skilled agent consultant, armed with deep industry understanding, spends 3 to 5 working days on-site using a “knowledge base + skills” approach to build the client’s core business processes into agents — accounting management, contract tracking, data reporting — all handled.

Comparison	Traditional Software Development	Agent Solutions
Implementation cost	Hundreds of thousands to millions	A fraction of the original cost
Implementation timeline	Six months to a year	3 to 5 working days
Customization level	Generic solutions that struggle to fit individual needs	Fully tailored to the enterprise’s specific business processes
Final outcome	Often reverts to Excel	Embedded in existing workflows, continuously operating

Over 80% of traditional software needs for SMEs will be rapidly replaced by agents.

The New Role Top AI Companies Are Fighting For: FDE

This transformation isn’t just changing business models — it’s also creating an entirely new professional role.

OpenAI’s CEO Sam Altman recently announced: OpenAI is now sending engineers directly to enterprise CEO offices, sitting beside CEOs, automating daily workflows, decision-making processes, and all routine tasks with AI. Shopify’s CEO was the first business leader to fully embrace this model.

This role now has a dedicated term:

FDE — Frontier Deployment Engineer.

Anthropic is doing the same — their Applied AI team specifically deploys engineers to strategic clients’ offices.

Where do they recruit from? From Palantir, Salesforce — from the “veterans” who understand enterprise business best.

The top AI companies are mass-recruiting an entirely new role whose core competency isn’t coding — it’s understanding business, industry, and clients.

FDE isn’t someone sitting at a computer writing code — they’re a “business translator” who walks directly into the enterprise:

Capability	Description
On-site problem solving	Embedded within the enterprise, sitting beside the CEO to observe decisions and workflows, identifying manual bottlenecks up close
Deep industry Know-how	Top AI companies don’t want the best coders — they want the “veterans” who understand enterprise business best
Process transformation	Can spot pain points at a glance, rapidly converting complex business processes into automatable tasks for agents

Silicon Valley’s top companies are laying off aggressively, yet revenue isn’t declining and products keep shipping. They’re investing more in AI models and agents, not in software development teams.

What enterprises will truly pay for in the future isn’t software products — it’s Tokens and solutions.

Are You “Learning AI” or “Consuming AI”?

At this point you might think: then I should learn AI even harder, right?

First, ask yourself a question: “Where exactly is your time going every day?”

“Yesterday GPT released a new version so I had to test it. Today DeepSeek got an update so I have to test that too. Tomorrow there’ll be another new model…”

Every time a new model drops, comment sections fill with people comparing: which model is slightly better, which Token is slightly cheaper. And after all the comparing?

Time spent on	Proportion	Actual output
Chasing latest model benchmarks	Massive	Virtually zero
Comparing which Token is cheaper	Massive	Virtually zero
Testing various AI tools	Massive	Virtually zero
Meeting clients, understanding needs	Minimal	Where the real money is

If you spend 90% of your time researching which knife is sharper but never walk into the forest to chop wood, you’re not sharpening the blade — you’re avoiding the real battle.

“Sharpening the axe doesn’t delay the woodcutting” — most people only understand the first half. But if you sharpen the axe every day and never once go chop wood, that’s not wisdom — that’s you haven’t figured out what you’re actually supposed to do.

Archimedes’ Lever Was Missing One Line

Archimedes said: “Give me a lever long enough, and I can move the earth.”

AI is undoubtedly the “10,000x lever” that can amplify our capabilities 10x, 100x. Used well, 100x isn’t even the ceiling.

But many people forget — Archimedes left out one line:

You need a fulcrum. Without a fulcrum, no matter how long the lever, you can only move air.

What’s a fulcrum? It’s not which AI model you know, nor which programming language you’ve mastered.

Not a fulcrum	The real fulcrum
Knowing how to use `Claude`, `GPT`, `Cursor`	Deep understanding and accumulation in a specific industry
Mastering a programming language	The trust relationship built with clients
Tracking the latest model benchmarks	Knowing where clients truly hurt and where they’re willing to spend

AI can write code for you, but it can never replace your understanding of an industry, the trust built face-to-face with clients, or the Domain Know-how accumulated over years on the front lines.

AI can do 100 things for you, but it doesn’t know which one is worth doing. The person who knows the answer is you — the one who accumulated Domain Know-how on the front lines.

From “Software Engineer” to “Business Builder”

All the analysis points to the same conclusion: you need to complete an identity transformation.

Before	After
`Software Engineer`	`Business Builder`
“I’ll build the software and wait for buyers”	“I’ll find clients first and understand their real needs”
Moat: can build software	Moat: knows what clients need
Selling generic products in a red-ocean market	Targeting niche scenarios with tailored solutions

Software engineers think “build it and they will come”; business builders think “find the demand first, then use AI to solve the problem.”

Your time allocation must also completely reverse:

Current allocation	Ideal allocation
90% chasing tools and trends	10% staying sharp on trends
10% vaguely thinking about what to do	90% meeting clients, understanding needs, finding your fulcrum

AI coding itself has no problem — it gives you the ability to build your own tools.

But your expectations for it must change:

AI coding is your tool, not your way out. Your way out lies in the industry you know best.

One Concrete First Step

Invite an old friend from the industry you know best for a 30-minute chat. Don’t talk about AI, don’t talk about models, don’t talk about tools. Just ask one question:

“In your current work, what tasks are still handled manually and repetitively?”

That manual process that causes pain, high costs, and low efficiency — that is where your fulcrum lies.

Find it, place the 10,000x lever of AI on top, and your capabilities can truly be amplified, creating real value.

The real blue ocean isn’t in the collapsing general software market — it’s hidden in those industry pain points that no one has yet solved with agents.

Finding the right fulcrum is where it truly begins.

Reference

别学 AI 编程了，AI 编程是一条死路 - YouTube

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