Chapter 10: The Future of Lisp

“Lisp is worth learning for the profound enlightenment experience you will have when you finally get it; that experience will make you a better programmer for the rest of your days, even if you never actually use Lisp itself a lot.” - Eric Raymond

Here we are in 2025, and Lisp is having another moment. But then again, Lisp is always having a moment—it’s just that most people don’t notice until years later when their favorite language adopts features Lisp had in 1960. The future of Lisp isn’t about Lisp catching up to modern languages; it’s about modern languages continuing their slow convergence toward Lisp.

Why Lisp Keeps Coming Back

Every decade, Lisp is declared dead. And every decade, it returns stronger, adapted to new environments, solving new problems. This isn’t nostalgia or stubbornness—it’s evolution. Lisp keeps coming back because it solves fundamental problems that never go away.

The Problems That Never Leave

Complexity Management: As systems grow more complex, we need languages that can abstract complexity without adding their own. Lisp’s macro system remains unmatched for building abstractions.

Domain-Specific Languages: Every industry eventually realizes it needs its own language. Lisp makes DSL creation trivial.

Interactive Development: The compile-run-debug cycle is dying. Developers want immediate feedback. Lisp has been doing this since 1958.

Metaprogramming: As we automate more programming, we need languages that can manipulate themselves. Lisp’s homoiconicity makes this natural.

Functional Programming: The multicore future demands functional thinking. Lisp has been functional from day one.

New Lisps on the Horizon

The Lisp family tree continues to grow. Here are the shoots to watch:

Jank - Clojure Native

;; Jank - Clojure semantics with C++ performance
(defn fibonacci [n]
  (if (<= n 1)
    n
    (+ (fibonacci (- n 1))
       (fibonacci (- n 2)))))

;; Compiles to native code, no JVM required
;; Same Clojure code, but with LLVM backend

Jank promises Clojure’s elegance with native performance. Imagine Clojure for systems programming, embedded systems, and real-time applications.

Carp - Lisp Without GC

;; Carp - Statically typed Lisp with manual memory management
(defn process-data [data]
  (let [processed (map transform data)]
    (delete data)  ; Explicit memory management
    processed))

(deftype Point [x Int, y Int])

(defn distance [p1 Point, p2 Point] Float
  (sqrt (+ (square (- (.x p2) (.x p1)))
           (square (- (.y p2) (.y p1))))))

Carp brings Lisp to domains where garbage collection is unacceptable—game engines, operating systems, embedded devices.

Basilisp - Lisp on Python

;; Basilisp - Clojure-compatible Lisp for Python runtime
(ns my-app.core
  (:import [numpy :as np]
           [pandas :as pd]
           [tensorflow :as tf]))

(defn train-model [data]
  (-> data
      pd/DataFrame
      (.fit model)
      (.predict test-data)))

;; Full access to Python's ML ecosystem with Lisp syntax

Basilisp brings Lisp to data science and machine learning, leveraging Python’s vast ecosystem.

WASM Lisps

WebAssembly is creating new opportunities for Lisp:

;; Lisp compiled to WebAssembly
(defun calculate-physics [particles]
  ;; Runs at near-native speed in browser
  (loop for p in particles
        do (update-position p)
           (apply-forces p)))

;; Deploy anywhere WASM runs: browsers, edge computing, IoT

The Eternal Relevance of S-expressions

While the industry argues about syntax—semicolons vs. whitespace, braces vs. indentation—Lisp solved this in 1958. S-expressions aren’t just syntax; they’re a universal data format that happens to be executable.

Configuration as Code

;; Modern configuration files are converging on S-expressions
;; This is valid EDN (Extensible Data Notation)
{:database {:host "localhost"
            :port 5432
            :credentials {:username #env "DB_USER"
                         :password #env "DB_PASS"}}
 :services [{:name "auth"
            :endpoints ["/login" "/logout" "/refresh"]}
           {:name "api"
            :rate-limit 1000}]}

;; It's also valid Clojure code!

AI and Machine Learning

Lisp’s symbolic processing makes it natural for AI:

;; Symbolic AI is making a comeback
(defrule diagnose-condition
  (symptom fever)
  (symptom cough)
  (duration > 7)
  =>
  (assert (diagnosis pneumonia)))

;; Neural networks as S-expressions
(defnetwork classifier
  (input 784)
  (dense 128 :activation 'relu)
  (dropout 0.2)
  (dense 10 :activation 'softmax))

Quantum Computing

Quantum circuits are naturally expressed as S-expressions:

;; Quantum circuit DSL
(defcircuit grover-search [qubits]
  (hadamard-all qubits)
  (oracle target-state)
  (diffusion qubits)
  (measure-all qubits))

;; Compiles to quantum assembly

New Domains for Lisp

Blockchain and Smart Contracts

;; Smart contract in Lisp
(defcontract token
  (state ((balances (hash-map address uint256))
          (total-supply uint256)))

  (defn transfer [to amount]
    (require (>= (get balances msg.sender) amount))
    (update balances msg.sender #(- % amount))
    (update balances to #(+ % amount))
    (emit 'Transfer msg.sender to amount)))

;; Formal verification built-in
(prove (forall [from to amount]
         (=> (valid-transfer? from to amount)
             (= (sum balances-before)
                (sum balances-after)))))

Infrastructure as Code

;; Define infrastructure with code
(definfra my-cluster
  (vpc {:cidr "10.0.0.0/16"
        :availability-zones ["us-east-1a" "us-east-1b"]})

  (kubernetes {:version "1.28"
               :nodes [{:type "t3.medium" :count 3}
                      {:type "t3.large" :count 2}]})

  (database {:engine :postgres
             :version 15
             :multi-az true}))

;; Deploy with: (deploy my-cluster :production)

Edge Computing

;; Lisp at the edge
(defedge image-processor
  :trigger http-request
  :memory 128
  :timeout 3000

  (fn [request]
    (-> request
        :body
        decode-image
        (resize 256 256)
        (apply-filter :gaussian)
        encode-response)))

;; Deploys to CDN edge locations worldwide

The Language Feature Convergence

Watch as every language slowly becomes Lisp:

Pattern Matching (Now Everywhere)

// JavaScript (2024)
match (expr) {
  {type: "add", left, right} => left + right,
  {type: "mul", left, right} => left * right,
  _ => 0
}

;; Lisp (1960)
(case (car expr)
  (add (+ (cadr expr) (caddr expr)))
  (mul (* (cadr expr) (caddr expr)))
  (otherwise 0))

Macros (Coming Soon)

// Rust macros getting more powerful
macro_rules! dsl {
    ($($tokens:tt)*) => {
        // Transform arbitrary syntax
    }
}

;; Lisp macros (always been there)
(defmacro dsl [& body]
  ;; Transform arbitrary syntax
  `(do ~@(transform body)))

Structural Editing (The Future of IDEs)

// Future IDEs will edit ASTs, not text
// Select expression → Transform → Refactor
// No more syntax errors
// No more parsing

;; Lisp has been doing this since the 1970s
;; Paredit, SLIME, structural navigation
;; Code is data, edit it as data

The Lisp Renaissance in Education

Universities are returning to Lisp, not for nostalgia but for necessity:

Teaching Fundamentals

;; Build a computer from first principles
(define (make-cpu)
  (let ((registers (make-vector 8 0))
        (memory (make-vector 65536 0))
        (pc 0))

    (lambda (instruction)
      (case (car instruction)
        ((load) (vector-set! registers (cadr instruction)
                           (vector-ref memory (caddr instruction))))
        ((store) (vector-set! memory (caddr instruction)
                            (vector-ref registers (cadr instruction))))
        ((add) (vector-set! registers (cadr instruction)
                          (+ (vector-ref registers (caddr instruction))
                             (vector-ref registers (cadddr instruction)))))))))

;; Students build languages, compilers, interpreters
;; Understanding, not just using

Research Languages

New research often starts with a Lisp:

  • Probabilistic Programming: Church, Anglican
  • Theorem Proving: ACL2, Coq’s Ltac
  • Genetic Programming: Push, Clojush
  • Music Composition: Overtone, Common Music

The Philosophical Victory

Lisp has already won the philosophical war. Modern programming embraces:

  • Immutability: The default in new languages
  • First-class functions: Universal now
  • REPL-driven development: Everyone wants it
  • Homoiconicity: Config files are becoming code
  • Macros: Every language is adding them
  • Functional programming: The future of parallelism

The industry spent 60 years reimplementing Lisp, badly, in other languages. Now we’re coming full circle.

Your Journey Forward

If you’ve made it this far, you’re changed. You’ve seen that:

  • Parentheses aren’t a barrier; they’re liberation
  • Simplicity enables power
  • Programs can write programs
  • Development can be conversational
  • Languages can evolve without committees

Next Steps

  1. Pick a Lisp and go deep: Master one dialect completely
  2. Build something real: Not toys, but production systems
  3. Contribute to the ecosystem: Libraries, tools, documentation
  4. Teach others: The enlightenment is meant to be shared
  5. Create your own Lisp: Every Lisper eventually does

Communities to Join

  • r/lisp: General Lisp discussion
  • Planet Lisp: Blog aggregator
  • Clojurians Slack: 20,000+ members
  • Common Lisp Discord: Active and helpful
  • Local meetups: Every major city has Lisp users

Projects to Study

  • Emacs: 40+ years of continuous development
  • Nyxt: Modern web browser in Common Lisp
  • Metabase: Business intelligence in Clojure
  • Racket: Language-oriented programming
  • SICM: Structure and Interpretation of Classical Mechanics

The Eternal Language

Lisp isn’t the past of programming—it’s the future that keeps arriving. Every generation rediscovers it, reimplements it, and realizes that McCarthy got it right the first time. The parentheses that seemed like obstacles become wings.

In 2025, Lisp is everywhere:

  • Your credit card transactions (Common Lisp)
  • Your text editor (Emacs Lisp)
  • Your streaming service (Clojure)
  • Your browser apps (ClojureScript)
  • Your package manager (Guix in Guile)

But more importantly, Lisp is in every language. The features you love in Python, JavaScript, Rust—they’re Lisp ideas, finally arriving home.

The Final Secret

Here’s the secret that every Lisp programmer knows: Lisp isn’t a programming language. It’s a notation for expressing computation. It’s a tool for thought. It’s a medium for ideas that haven’t been invented yet.

Other languages are products of their time. Lisp is timeless. It was modern in 1960, it’s modern in 2025, and it will be modern in 2070. Because Lisp isn’t about syntax or features or paradigms. It’s about the fundamental nature of computation itself.

When you learn Lisp, you’re not learning a language. You’re learning to think. And once you learn to think in Lisp, every other language becomes just syntax.

Welcome to the brotherhood and sisterhood of the parentheses. May your functions be pure, your macros hygienic, and your recursion properly tail-called.

The future of Lisp isn’t something that will happen. It’s something that’s been happening for 67 years and shows no signs of stopping. Lisp is dead. Long live Lisp.

“The greatest single programming language ever designed.” - Alan Kay

“Lisp is the most important idea in computer science.” - Alan Kay (again, because it bears repeating)

Epilogue: Your First Lisp

If you’re inspired to write your own Lisp (and you should be), here’s a minimal Lisp interpreter in Python to get you started:

def eval(expr, env):
    if isinstance(expr, str):  # Variable
        return env[expr]
    elif not isinstance(expr, list):  # Literal
        return expr
    elif expr[0] == 'quote':  # Special form
        return expr[1]
    elif expr[0] == 'if':
        return eval(expr[2] if eval(expr[1], env) else expr[3], env)
    elif expr[0] == 'lambda':
        return lambda *args: eval(expr[2], {**env, **dict(zip(expr[1], args))})
    elif expr[0] == 'define':
        env[expr[1]] = eval(expr[2], env)
    else:  # Function application
        func = eval(expr[0], env)
        args = [eval(arg, env) for arg in expr[1:]]
        return func(*args)

# Now you have Lisp!
env = {'+': lambda x, y: x + y, '-': lambda x, y: x - y}
eval(['define', 'three', ['+', 1, 2]], env)  # Define a variable
print(eval('three', env))  # => 3

# Define a function
eval(['define', 'square', ['lambda', ['x'], ['*', 'x', 'x']]], env)
env['*'] = lambda x, y: x * y
print(eval(['square', 5], env))  # => 25

Go forth and Lisp. The parentheses await.

End of Book

“The Lisp programmer knows the value of everything and the cost of nothing.” - Alan Perlis

“Any sufficiently complicated C or Fortran program contains an ad hoc, informally-specified, bug-ridden, slow implementation of half of Common Lisp.” - Greenspun’s Tenth Rule

“Lisp isn’t dead. It just smells funny.” - Anonymous

“Learn Lisp, and you will be enlightened. Use Lisp, and you will be free.” - The Author