Introduction: A Seismic Shift in Software
Are we witnessing a monumental change in technology? According to a recent analysis by Martin Alderson, we might be on the verge of a 90% drop in software building costs. This isn't just about new tools, but a paradigm shift driven by Agentic Coding.
After decades of evolution—from SaaS to mobile, through to cloud—the economics of development are undergoing their most radical transformation. If 2025 showed the first signs, 2026 might catch many professionals off guard.
"The economics have changed dramatically now with agentic coding, and it is going to totally transform the software development industry."
Martin Alderson, Software Expert
For a complete deep dive into the original thesis that inspired this breakdown, please refer to the source article: Has the cost of building software just dropped 90%?.
The Problem: The Era of Complexity
To understand the solution, we must look at recent history. Alderson describes the recent period as the "era of complexity." Despite the advent of Cloud and Open Source, real costs haven't dropped as promised. Why?
- Over-engineering: Massive adoption of microservices and Kubernetes even where unnecessary.
- Labor-Intensive Processes: Patterns like rigid TDD (Test Driven Development) and hyper-complex React frontends.
- Coordination Overhead: The larger the team, the more time spent on meetings, tickets, and hand-offs rather than coding.
The Solution: Agentic Coding and Inverse Brooks's Law
Agentic Coding changes the game by drastically reducing manual labor. We aren't talking about simple autocomplete assistants, but agents capable of writing entire test suites or converting business specs into working APIs in hours.
What is Agentic Coding?
It is the use of autonomous AI agents that plan, write, and execute complex code based on high-level instructions, shrinking development timelines from weeks to days.
A project that took a month and a full team can now be finished in a week by a single person aided by AI. This triggers an Inverse Brooks's Law: by reducing the headcount needed, communication overhead vanishes. A small team powered by AI becomes exponentially more productive than a large traditional department.
Economic Impact: Jevons Paradox
Does a 90% cost reduction mean mass unemployment for developers? Not necessarily. This is where Jevons Paradox comes in: when a resource becomes more efficient and cheaper, total consumption increases rather than decreases.
Unlocking Latent Demand
There is infinite latent demand for software that is currently unmet because it's too expensive. Every company has hundreds of processes managed in Excel sheets that deserve a dedicated app.
- Previous Scenario: An internal app costs $50k. Only critical projects get approved.
- Agentic Coding Scenario: The same app costs $5k. Suddenly, hundreds of micro-projects become economically viable.
The New Developer Role: Domain Knowledge
If AI writes the code, what is left for the human? The answer is domain knowledge. The "YOLO" approach (blindly trusting AI) leads to disaster. An expert pilot is needed.
Value shifts from syntax to semantics:
- Architecture and Strategy: Choosing the right frameworks and defining structure remains a human task.
- Agent Babysitting: Verifying output, correcting hallucinations, and guiding iteration.
- The True 10x Engineer: An industry expert (e.g., in finance or logistics) paired with Agentic Coding tools can outperform entire traditional dev teams.
Conclusion: Preparing for 2026
AI models are evolving rapidly (think Opus 4.5 and beyond). Those fighting this change risk the fate of those who dismissed the iPhone in 2007. It is not true that LLMs are only for new (greenfield) projects; they are exceptional at deciphering and refactoring legacy (brownfield) code too.
Software is becoming "disposable": if an idea doesn't work, scrap it and restart, because the cost of rewriting is negligible. The real scarce resource becomes conceptual thinking, not typing.
FAQ on Agentic Coding
What exactly is Agentic Coding?
Agentic Coding refers to using AI agents that don't just complete code but autonomously plan and execute complex software development tasks under human supervision.
Will Agentic Coding eliminate developer jobs?
Likely not, due to Jevons Paradox. By lowering costs, the demand for software will increase, shifting the developer's role towards architecture and supervision.
How does AI reduce software costs by 90%?
AI slashes time spent on writing, testing, and refactoring. Projects requiring months and large teams can now be handled in days by fewer people, eliminating coordination costs.
Does AI work on legacy code or just new projects?
AI is highly effective on legacy code. Agents can analyze old codebases, explain functionality, find bugs, and suggest modernization much faster than a human.
What will happen to software development in 2026?
A massive acceleration in AI agent adoption is expected. Companies failing to adapt risk being outpaced by smaller, agile competitors capable of rapid iteration.