Alternatives
Products that do what I replaced every function in a codebase with English – it still works does
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…
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- 2PA
Hey HN! We just launched PromptL: a templating language built to simplify writing complex prompts for LLMs like GPT-4 and Claude. Why PromptL? Creating dynamic prompts for LLMs can get tricky, even with standardized APIs that use lists of messages and settings. While these formats are consistent, building complex interactions with custom logic or branching paths can quickly become repetitive and hard to manage as prompts grow. PromptL steps in to make this simple. It allows you to define and manage LLM conversations in a readable, single-file format, with support for control flow and…
2024 · promptl.ai
- 3A1
I've seen a lot of comments about how complex frameworks like LangChain can be. Over the holidays, I wanted to see how minimal an LLM framework could get if we stripped away everything non-essential. The result is an LLM framework in just 100 lines of code. These 100 lines capture what I see as the core abstraction of most LLM frameworks: a nested directed graph that breaks down tasks into multiple LLM steps, with branching and recursion to enable agent-like decision-making. From there, you can layer on more advanced features like agents, RAG, task decomposition, and more. I’ve intentionally…
2025 · github.com
- 4LF
Hey HN, I built SWE-Kit, LLM toolkit (Function callable tools) which makes building agents specialised in coding like Devin very easy. I noticed a typical pattern while building local agents: creating & perfecting LLM tools to interact with system or codebase was the repeated and time-consuming. We created a layer that simplifies building agents that can interact with code, file system, git, shell and allows you to quickly solve for a wide variety of coding agent use cases. Aren’t there open coding agents already? Well, yes, but most folks would want to solve their specific use case like a…
2024 · swekit.dev
- 5CR
hi everyone. how does moving llm call prompts and output structure definitions away from code into configuration land sound? would you use something like this if it was stable and well documented enough? please don't hold back the criticism. i appreciate all feedback (constructive & otherwise).
2024 · github.com
- 6OS
Hi HN, we’re Dylan and Matthew, building sublingual (https://github.com/sublingual-ai/sublingual), an open-source LLM observability tool you can use with zero code changes. As developers focused on iterating and building features as fast as possible, we felt observability would’ve been a helpful tool to have, but we found existing solutions had too much overhead to set up. So we gave ourselves the challenge of building an observability tool that you can integrate without changing a single line of code in your project. How it works Run your python application as usual with…
2025 · github.com
- 7LI
Hey HN! We built Lunon to make LLM development way less of a headache. Ever wanted to see how different models handle the same prompt without all the setup hassle? That's what we fixed. Our API lets you compare Claude, GPT, Mistral and others in real-time with just a few lines of code. No more complex infrastructure or managing multiple API connections - we handle all that boring stuff behind the scenes. Plus, you can cut costs by intelligently routing requests to the right model for each task. Use the powerful (expensive) models only when you really need them. If you're building with LLMs…
2025 · lunon.com
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Skip the regex docs. Describe it, get working code back.
27d ago · rapidapi.com
- 9LA
We combined Stanford's ACE (agents learning from execution feedback) with the Reflective Language Model pattern. Instead of reading traces in a single pass, an LLM writes and runs Python in a sandbox to programmatically explore them - finding cross-trace patterns that single-pass analysis misses. The framework achieved 2x consistency improvement on τ2-bench.
Mar 2026 · github.com
- 10TA
Hi HN, TamedTable is an LLM harness for data ETL. And yes, it was developed using AI, meaning you can take the entire specification and recreate it to your desires: https://github.com/ZSvedic/TamedTable
Aug 2026 · tamedtable.com
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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 1000 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!
25d ago · github.com
- 12LC
Debugging is hard for LLMs, because they primarily depend on source code, and they don't have access to runtime state. I spent countless hours debugging code, and the only way I found LLMs useful for that, is to ask them to add log lines. That's annoying, because it pollutes my code and adds unnecessary diffs. So we made an MCP server that solve this problem. It gives MCP clients (like Claude Code) access to a NodeJS inspector, so they can: 1. set breakpoints 2. step in, step out, continue 3. fetch the current execution location 4. read console output 5. run JS using eval To try: 1. run a…
2025 · github.com
- 13PL
Hi, I’ve been exploring Claude 3.5 code generation abilities for a while and it looks like it can generate more consistent code than other models. However it would still be unmaintainable if you ask it to write a lot of code and it still sucks at system design. So, I’ve been playing around the idea of using the code repository with a template for directory layout and infrastructure, then adding the repository information to Claude and asking it to generate code. It seems that it works, if I pass the structure of some OpenAPI based backend it can update the API definition and implementation…
2024 · github.com
- 14GA
hi hn, today I'm open sourcing a new SQL-like query language that's built for the web. it has dedicated syntax for request, parsers, selectors, and javascript snippets... it was built on nodejs with the incredible moo lexer and nearley parser. if you're a fan of regular expressions, do I have some code to show you! the website is mostly just a few examples and a playground where you can write & run (& share!) your own queries. there's also an introductory blog post where i try but ultimately fail to justify why this should be its own language and not a library/framework. enjoy!
2024 · getlang.dev
- 15OS
I built an open-source research agent. You ask a question, it searches the web via Tavily, synthesizes an answer with an LLM, and shows the sources it used. Answers stream in real-time. The interesting part is the backend. It's a single JS file (~100 lines) that handles web search, LLM streaming, and per-user conversation history. No vector database, no Redis, no separate storage service. It runs inside a cell — an isolated environment with a built-in database, search index, and filesystem. The cell handles persistence and streaming natively, so the agent code only has to deal with the…
Apr 2026 · github.com
- 16TF
A few weeks ago I got rejected from a role and the feedback was that I needed a deeper understanding of FAISS and LlamaIndex. So I built triage.flow — an AI assistant that lets you explore and understand GitHub repositories through a chat interface. It clones a repo, indexes it using FAISS + BM25 + tree-sitter parsing, and powers a full UI where you can: - Ask natural-language questions like “how does auth work?” or “explain @src/components/Modal.tsx” - Mention specific files/folders with @filename.ts (autocomplete supported) - See how the agent thinks in real time (Thought →…
2025 · github.com
- 17HL
At testup.io we have been working for a while to bring artificial intelligence to the field of test automation. Just a few years ago, the primary challenge laid in accurately identifying UI elements following minor structural changes, such as updates to IDs or paths. The emergence of Large Language Models (LLMs) raised the bar for what it meant to be smart. Now, we anticipate the robot to do lots of things autonomously, such as retry in cases of unresponsiveness or handle minor error reports. A more challenging, but soon expected feature, would involve the test robot navigating your web shop…
2024 · github.com
- 18MC
Hi HN, I'm excited to introduce Mixlayer, a platform I've been working on over the past 6 months that allows you to code and deploy prompts using simple JavaScript functions. Mixlayer recreates the developer experience of using LLMs locally without having to do all of the local setup yourself. I originally came up with this idea when using LLMs on my MacBook and thought it’d be cool to build a product that makes it easy for everyone. It compiles your code to a WASM binary and runs it alongside a custom inference stack I wrote in Rust. When you integrate LLMs in this way, your code and the…
2024 · mixlayer.com
- 19LC
2023 · github.com
- 20MC
multilspy is a cross-platform library designed to simplify the process of creating language server clients to query and obtain results of various static analyses from a wide variety of language servers that communicate over the Language Server Protocol. It is easily extensible to support any language that has a Language Server and currently supports Java, Rust, C# and Python. We aim to continuously add support for more language servers and languages. Language servers are tools that perform a variety of static analyses on code repositories and provide useful information such as type-directed…
2024 · github.com
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