Agentic coding is like compiler. Initially compiler wass like alien technology that improved productivity 100x and made dynamic programming and other advanced coding possible. But eventually no company makes significant amount of money by writing compiler. The actual software companies that have customers and revenues make the money

Just like the compiler shifted the abstraction layer of software development in the 20th century, agentic coding is shifting the abstraction layer today. Here is my reasoning:

1. The Value Shifts from Tool to Application

In the early days of computing, creating a better compiler was a massive competitive advantage. Over time, however, compilers became commoditized, open-source, and standardized (like GCC and LLVM).

  • The Past: The massive financial winners of the software revolution weren’t the companies selling compilers; they were companies like Microsoft, Adobe, and Google, who used compilers to build operating systems, design tools, and search engines.
  • The Present: Right now, there is a gold rush to build the “best” AI coding agents. Millions of dollars are pouring into foundational developer tools. But eventually, agentic coding will become a baseline utility—integrated directly into every IDE and workflow for free or at a very low cost. The real wealth will be captured by businesses that use these agents to solve specific, complex user problems faster than ever before.

2. The Nature of “Advanced Coding” Changes

You noted that compilers made advanced paradigms like dynamic programming practical. Before high-level languages, managing memory and registers manually made complex algorithms incredibly prone to human error.

  • With Compilers: Developers were freed from worrying about machine architecture, allowing them to focus on complex software architecture and logic.
  • With Agents: Developers are being freed from syntax, boilerplate, API integration mechanics, and routine debugging. The new “advanced coding” will shift toward system design, data architecture, security boundaries, and product user experience (UX).

3. The 100x Productivity Paradox

When a tool increases productivity by 100x, it drops the marginal cost of writing a line of code to near zero.

  • Because code is cheap to generate, software will become hyper-abundant.
  • When code itself is no longer scarce, the value of a company will be measured entirely by its proprietary data, unique distribution channels, and deep understanding of customer workflows.

In short, AI agents are the new compilers. They will turn natural language and high-level intent into execution. The companies that win the next decade won’t be the ones bragging about the AI tool they used to write their app; they will be the ones who used that tool to build a deeply entrenched, highly valuable product for their customers. What specific industries or types of software applications do you think will benefit the most from this shift in software abundance? Let me know your thoughts in the comments.