Context:
Based on Brooks’s “No Silver Bullet”, there has not been any 10x improvement in software development in productivity, reliability, or simplicity since high-level languages became popular: No Silver Bullet - The Fundamental Argument
Rise of the modern AI and modern low-code solutions.
From the original text (1986):
“Many people expect advances in artificial intelligence to provide the revolutionary breakthrough that will give order-of-magnitude gains in software productivity and quality.4 I do not.”
“Automatic” programming. For almost 40 years, people have been anticipating and writing about “automatic programming”, the generation of a program for solving a problem from a statement of the problem specifications. Some people today write as if they expected this technology to provide the next breakthrough. Parnas implies that the term is used for glamour and not semantic content, asserting, In short, automatic programming always has been a euphemism for programming with a higher-level language than was presently available to the programmer.8 He argues, in essence, that in most cases it is the solution method, not the problem, whose specification has to be given. ”
“Graphical programming. A favorite subject for PH.D. dissertations in software engineering is graphical, or visual, programming, the application of computer graphics to software design.9 Sometimes the promise of such an approach is postulated from the analogy with VLSI chip design, where computer graphics plays so fruitful a role. Sometimes the approach is justified by considering flowcharts as the ideal program design medium, and providing powerful facilities for constructing them. Nothing even convincing, much less exciting, has yet emerged from such efforts. I am persuaded that nothing will. ”
Low-code systems and generative AI continue the historical pattern of attacking the accidental layer. They:
- Simplify syntax and automate scaffolding.
- Empower non-programmers to compose systems via templates or prompts.
Yet they don’t eliminate the essential tasks—understanding requirements, defining domain abstractions, ensuring conceptual integrity, or managing evolving complexity. These still demand architectural insight and human judgment. In modern terms, Brooks’ idea translates as: AI may automate code-writing, but not software design thinking. The “no silver bullet” principle still applies: productivity jumps are bounded by the rate at which humans can articulate precise, evolving models of the world (and use the tools of the day to express and implement them)
Sources: No Silver Bullet - Frederick P. Brooks, Jr Is AI a Silver Bullet? - Ian Cooper Paper Summary: No Silver Bullet: Essence and Accidents of Software Engineering - Fayner Brack Wikipedia page
Note
This content was drafted with assistance from AI tools for research, organization, and initial content generation. All final content has been reviewed, fact-checked, and edited by the author to ensure accuracy and alignment with the author’s intentions and perspective.