Technology
The Hundred-Year Language
paulgraham.com
Technology
20 min read → 70 sec
An essay on what programming languages may look like in 100 years, arguing that small cores, flexible semantics, and optimization added later will outlast efficiency-first designs. It predicts faster hardware will make programmer time the real scarce resource.
A usable hundred-year language could be designed now
Lisp already designed much of its core in 1958
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Programming languages evolve slowly because they are notation, more like mathematical notation than transportation technology
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Languages will evolve in branching trees. Java will likely be an evolutionary dead-end like Cobol.
The strongest long-term languages will have small, clean cores with few fundamental operators
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If Moore's Law continued for 100 years
74 quintillion×
faster computers would be
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Most extra computing power will be wasted, because each generation spends gains on simpler, more wasteful designs
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Good waste spends more resources to get simpler designs. Bad waste solves the wrong problem.
Faster hardware will make programmer time more valuable than machine time
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Separate string types are premature optimization. Strings are semantically a subset of lists.
Arc dropped strings, and recursive functions handled some tasks more easily than regular expressions
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Future languages may flatten data structures further, possibly treating arrays, hash tables, and numbers as optimizations
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Future languages should separate program meaning from implementation, with optimization advice added later
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10×
speed cost per interpretation layer
Layered systems buy flexibility and easier change
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Bottom-up programming builds layers that act as languages, producing smaller, more flexible, more reusable software
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Object-oriented programming persists because large organizations can accrete patches with it, not because it ensures reuse
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Parallelism will usually stay optional and late-stage, except in special applications where optimization demands it
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Profilers will matter more than faster compilers, because they guide programs from acceptable to maximal performance
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Open-source languages like Perl, Python, and Ruby show language design shifting from researchers to working hackers
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Static typing blocks true macros, and without macros no language is worth using
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