For decades, programming language researchers have invented ways to make programs more explicit, more checkable, more constrained, more secure, and more verifiable. Refinement types. Dependent types. Effect systems. Session types. Typestate. Linear types. Contracts. Capabilities. Model checking. Proof assistants. Program synthesis. Typed holes. Semantic editing.
While watered-down versions of some of these have occasionally made it out of the academy ("technology from the past come to save the future from itself"), these are the exceptions that prove the rule. For the most part, what we know how to do in theory makes our industrial practice look like it's stuck in the stone age.
Some powerful programming language research directions are hamstrung by fundamental constraints like computability, but my sense is that most of what stops great programming language ideas from escaping the academy are human factors constraints. Human cognition is weird and, in many ways, extremely limited. Empirical work shows, for example, that even apparently superficial language syntax choices can materially affect programmer accuracy and learning.
Coding agents, on the other hand, have few of the same limitations. Research already shows that they excel where humans struggle, benefiting from their ability to read verbose error messages, author precise specifications, and tolerate the iteration required to generate valid proofs of program correctness.
We've been here before. In the 1930s and 1940s, between the Great Depression suppressing demand for new technology, wartime secrecy requirements preventing discoveries from being made public,1 and military demand driving increased R&D spending, a huge backlog of research built up. Some economists have suggested that America's postwar economic miracle2 – which brought us innovations from the microwave to commercial aviation to mass-market penicillin – was in part the natural consequence of corporations simply working through this research backlog.
Programming language development in 2026 looks very similar. Decades of theoretical innovation have built up in the academy due to human limitations that are about to be lifted en masse at exactly the time when demand for the production of new programming artifacts is skyrocketing.
Concretely, I predict that agentic programming will lead to a renaissance in programming language design. Language designers, faced with a fundamentally new type of user, suddenly have decades of theoretical research to draw from in designing new, powerful language features uniquely suited to the strengths of coding agents. Whether innovation takes the form of new language features in existing languages, DSLs, entirely new languages, or even a reimagining of what counts as a programming language, change is coming.
During WWII, the USPTO placed more than 11,000 patent applications under secrecy orders, then rescinded them en masse after the war.
That video is about Japan, but the reference was too good to resist.