AI · alternatives · 2026

24 alternatives to I replaced every function in a codebase with English – it still works

Tril converts every function in a repo into plain English descriptions, then runs and tests them — using an LLM as the interpreter instead of a runtime. The concept: programming languages exist because machines couldn't understand human intent. LLMs can. So what happens if you remove the code entirely and just... describe what each function should do? The tool replaces functions one by one, runs your test suite after each swap to confirm nothing breaks, and outputs a .md file. Then `tril run` spins up an HTTP server that sends each function's English description to Claude and returns the…

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.

1
Why write code if the LLM can just do the thing? (web app experiment)▲436
I spent a few hours last weekend testing whether AI can replace code by executing directly. Built a contact manager where every HTTP request goes to an LLM with three tools: database (SQLite), webResponse (HTML/JSON/JS), and updateMemory (feedback). No routes, no controllers, no business logic. The AI designs schemas on first request, generates UIs from paths alone, and evolves based on natural language feedback. It works—forms submit, data persists, APIs return JSON—but it's catastrophically slow (30-60s per request), absurdly expensive ($0.05/request), and has zero UI…
Nov 2025 · github.com · its alternatives →
2
My LLM CLI tool can run tools now, from Python code or plugins▲529
LLM 0.26 is out with the biggest new feature since I started the project: support for tools. You can now use the LLM CLI tool—and Python library—to grant LLMs from …
2025 · simonwillison.net · its alternatives →
3
Magentic – Use LLMs as simple Python functions▲283
This is a Python package that allows you to write function signatures to define LLM queries. This makes it easy to mix regular code with calls to LLMs, which enables you to use the LLM for its creativity and reasoning while also enforcing structure/logic as necessary. LLM output is parsed for you according to the return type annotation of the function, including complex return types such as streaming an array of structured objects. I built this to show that we can think about using LLMs more fluidly than just chains and chats, i.e. more interchangeably with regular code, and to make it…
2023 · github.com · its alternatives →
4HL
How LLMs Work – Interactive visual guide based on Karpathy's lecture▲245
All content is based on Andrej Karpathy's "Intro to Large Language Models" lecture (youtube.com/watch?v=7xTGNNLPyMI). I downloaded the transcript and used Claude Code to generate the entire interactive site from it — single HTML file. I find it useful to revisit this content time to time.
Apr 2026 · ynarwal.github.io · its alternatives →
5
Code Mode▲144
I’ve been testing a simple idea inspired by Apple/Cloudflare/Anthropic: LLMs are far better at writing a small program than coordinating multiple tool calls. So instead of giving the model 10+ tools, I exposed one: a TypeScript sandbox with access to the same interfaces. The model writes a script → it runs once → done. What changed - +68% reduction in token use - No multi-step drift or retries - Local models (Llama 3.1 8B / Phi-3) became much more reliable Repo: https://github.com/universal-tool-calling-protocol/code-mode Curious whether others have seen…
Nov 2025 · github.com · its alternatives →
6
Find the best local LLM for your hardware, ranked by benchmarks▲283
Find the local LLM that actually runs and performs best on your hardware. Ranked by real, recency-aware benchmarks, not parameter count. One command, run it instantly. - Andyyyy64/whichllm
May 2026 · github.com · its alternatives →
7DA
DTL: a language and JavaScript lib to transform and manipulate data▲63
DTL is a project that began it's life as part of a another piece of software for a startup I founded a few years ago. For that project I needed a way to describe how to rewrite data in a portable way. I needed to be able to create the rules on the fly and store them in a database, I needed them to be able to describe transformations I hadn't thought about, but also needed them to be safe and predictable. Though the startup didn't survive, the language I made was so useful to me I felt I had to extract it and make it usable to everyone. DTL is the result. Though the npm module is relatively…
2022 · getdtl.org · its alternatives →
8
Ell – A command-line interface for LLMs written in Bash▲214
Hi HN! I've created a CLI tool called "ell" that allows you to interact with LLMs directly from your terminal. Designed with the Unix philosophy in mind, ell is simple, modular, and extensible. You can easily pipe input and output to integrate with other tools. Its templates and hook-based plugins enable you to customize and extend its functionality to suit any needs. Check out the README for usage instructions and examples. I developed this tool because existing solutions often felt too heavy, with many dependencies, or they weren't friendly to piping and customization. I, on the contrary,…
2024 · github.com · its alternatives →
9IW
I wrote a technical history book on Lisp▲252
The book page links to a blog post that explains how I got about it (and has a link to sample content), but the TL&DR is that I could not find a lot of books that were on "our" history _and_ were larded with technical details. So I set about writing one, and some five years later I'm happy to share the result. I think it's one of the few "computer history" books that has tons of code, but correct me if I'm wrong (I wrote this both to tell a story and to learn :-)). My favorite languages are Smalltalk and Lisp, but as an Emacs user, I've been using the latter for much longer and for my…
Feb 2026 · berksoft.ca · its alternatives →
10IC
I created a language called AntiLang – breaking all the conventions▲143
AntiLang is an interpreted programming language written in Go. The basic idea of this is to keep all the logical parts of a language same, but reverse the structure of it. The idea for this project came when I was having a long midnight conversation with my friend and thought of writing such a weird language. The initial draft was far worse than the current implementation; we thought of reversing the brackets and the language would be read from bottom to top. I'm happy that I dropped that idea Technical details: As the interpreter is written in Golang, I compiled it to WASM, and the whole…
2025 · siruscodes.github.io · its alternatives →
11
AGL a toy language that compiles to Go▲83
I spent the past 2 weeks making this toy programming language. I basically forked the Go scanner/parser, and changed the syntax to have functions return a single value. This enable proper Result/Option type to be used as well as propagating errors with an operator. I also wanted to have short "type inferred" anonymous functions to be able to use functions like Map/Reduce/Filter, without having to use 100 characters to specify the types.
2025 · github.com · its alternatives →
12
Replacing my OS process scheduler with an LLM▲77
Replacing the OS process scheduler with an LLM. Contribute to mprajyothreddy/brainkernel development by creating an account on GitHub.
Dec 2025 · github.com · its alternatives →
13
Llm2sh – Translate plain-language requests into shell commands▲67
This is my take on the common "use llms to generate shell commands" utility. Emphasis is placed on good CLI UX, simplicity, and flexibility. `llm2sh` supports multiple LLM providers and lets LLMs generate multi-command sequences to handle complex tasks. There is also limited support for commands requiring `sudo` and other basic input. I recommend using Groq llama3-70b for day-to-day use. The ultra-low latency is a game-changer - its near-instant responses helps `llm2sh` integrate seamlessly into day-to-day tasks without breaking you out of the 'zone'. For more advanced tasks, swapping to…
2024 · github.com · its alternatives →
14
The Tsonic Programming Language▲62
You can see some examples here: https://github.com/tsoniclang/proof-is-in-the-pudding And a hugo clone (which compiles to native code) here: https://github.com/tsoniclang/tsumo Linux and macOS for now.
Jan 2026 · tsonic.org · its alternatives →
15
Pipelex – Declarative language for repeatable AI workflows▲122
We’re Robin, Louis, and Thomas. Pipelex is a DSL and a Python runtime for repeatable AI workflows. Think Dockerfile/SQL for multi-step LLM pipelines: you declare steps and interfaces; any model/provider can fill them. Why this instead of yet another workflow builder? - Declarative, not glue code: you state what to do; the runtime figures out how. - Agent-first: each step carries natural-language context (purpose, inputs/outputs with meaning) so LLMs can follow, audit, and optimize. Our MCP server enables agents to run pipelines but also to build new pipelines on demand. - Open…
Oct 2025 · github.com · its alternatives →
16
LLM, a Rust Crate/CLI for CPU Inference of LLMs (LLaMA, GPT-NeoX, etc.)▲45
G'day, HN! I'm one of the maintainers of `llm`. I've been working alongside a trusty group of contributors to bring this project to life, and we're now at a point where we're ready to share it with the world. Large language models (LLMs) are taking the computing world by storm due to their emergent abilities that allow them to perform a wide variety of tasks, including translation, summarization, code generation, and even some degree of reasoning. However, the ecosystem around LLMs is still in its infancy, and it can be difficult to get started with these models. `llm` is a one-stop shop for…
2023 · github.com · its alternatives →
17
Building an LLM from Scratch in TypeScript▲33
The from-scratch guide to building large language models in NodeJS.
9d ago · book.humanexperiences.io · its alternatives →
18
Run – a CLI universal code runner I built while learning Rust▲96
Hi HN — I’m learning Rust and decided to build a universal CLI for running code in many languages. The tool, Run, aims to be a single, minimal dependency utility for: running one-off snippets (from CLI flags), running files, reading and executing piped stdin, and providing language-specific REPLs that you can switch between interactively. I designed it to support both interpreted languages (Python, JS, Ruby, etc.) and compiled languages (Rust, Go, C/C++). It detects languages from flags or file extensions, can compile temporary files for compiled languages, and exposes a unified REPL…
2025 · github.com · its alternatives →
19
Online Haskell REPL▲82
We heard your requests for Haskell and today we're excited to finally announce Haskell as yet another language we support. We've decided to put our focus...
2017 · repl.it · its alternatives →
20
Open-source SDK for creating custom code interpreters with any LLM▲64
Python & JS/TS SDK for running AI-generated code/code interpreting in your AI app - GitHub - e2b-dev/code-interpreter: Python & JS/TS SDK for running AI-generated code/code interpreting in your AI app
2024 · github.com · its alternatives →
21
6to5 – Turn ES6 code into vanilla ES5 with source maps and no runtime▲48
🐠 Babel is a compiler for writing next generation JavaScript. - babel/babel
2014 · github.com · its alternatives →
22
Recursive LLM Prompts▲97
I've been playing with the idea of an LLM prompt that causes the model to generate and return a new prompt. https://github.com/andyk/recursive_llm The idea I'm starting with is to implement recursion using English as the programming language and GPT as the runtime. It’s kind of like traditional recursion in code, but instead of having a function that calls itself with a different set of arguments, there is a prompt that returns itself with specific parts updated to reflect the new arguments. Here is a prompt for infinitely generating Fibonacci numbers: > You are a…
2023 · github.com · its alternatives →
23
I wrote a VM and Compiler for a small language in Go▲37
My implementation of Thorsten Bell's book (Writing an Interpreter in Go) - actuallyachraf/monkey-giggle
2020 · github.com · its alternatives →
24
Openleetcode – Local LeetCode runner where tests live in the repo▲73
You write a standard solution, just like on LeetCode, and run it through the CLI. It identifies the problem by ID or title, executes your code against local test cases, and shows the result. It currently supports around 1.4k problems and multiple languages, including Python, C++, Rust, Java, Go, TypeScript, Swift, and others. The project is still an MVP. System design, SQL, and concurrency problems are not supported yet, but support for more problem types is planned. Made in Haskell!
Aug 2026 · github.com · its alternatives →

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