AI · alternatives · 2026
24 alternatives to Code Mode
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…
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
- 1
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
Read this article by Cloudflare this morning https://blog.cloudflare.com/code-mode/ the main argument being that LLMs are much better at writing typescript code than tool calls because they've seen typescript code many more times. HN Discussion: https://news.ycombinator.com/item?id=45399204 https://news.ycombinator.com/item?id=45386248 Deno provides a great sandbox environment for Typescript code execution because of its permissions system which made it easy to spin up code that only has access to fetch and network calls. Stick an MCP proxy…
2025 · github.com · its alternatives →
- 3
I spent a lot of time and money on this rather big side project of mine that attempts to replicate the mechanistic interpretability research on proprietary LLMs that was quite popular this year and produced great research papers by Anthropic [1], OpenAI [2] and Deepmind [3]. I am quite proud of this project and since I consider myself the target audience for HackerNews did I think that maybe some of you would appreciate this open research replication as well. Happy to answer any questions or face any feedback. Cheers [1]…
2024 · github.com · its alternatives →
- 4UC
Hi HN, Code Llama was released, but we noticed a ton of questions in the main thread about how/where to use it — not just from an API or the terminal, but in your own codebase as a drop-in replacement for Copilot Chat. Without this, developers don't get much utility from the model. This concern is also important because benchmarks like HumanEval don't perfectly reflect the quality of responses. There's likely to be a flurry of improvements to coding models in the coming months, and rather than relying on the benchmarks to evaluate them, the community will get better feedback from people…
2023 · continue.dev · its alternatives →
- 5
Hey HN, We’ve been building browser agents for a while. In production, we kept converging on the same pattern: deterministic scripts for the happy path, agents only for edge cases. So we built Demonstrate Mode. The idea is simple: You perform your workflow once in a remote browser. Notte records the interactions and generates deterministic automation code. How it works: - Record clicks, inputs, navigations in a cloud browser - Compile them into deterministic code (no LLM at runtime) - Run and deploy on managed browser infrastructure Closest analog is Playwright codegen but: - Infrastructure…
2025 · notte.cc · its alternatives →
- 6
Hey HN, I made Browser-Use, an open-source tool that lets (all Langchain supported) LLMs execute tasks directly in the browser just with function calling. It allows you to build agents that interact with web elements using natural language prompts. We created a layer that simplifies website interaction for LLMs by extracting xPaths and interactive elements like buttons and input fields (and other fancy things). This enables you to design custom web automation and scraping functions without manual inspection through DevTools. Hasn't this been done a lot of times? Good question, as a general…
2024 · github.com · its alternatives →
- 7
Your AI agent is burning 6x more tokens than it needs to just to browse the web. We built OpenBrowser MCP to fix that. Most browser MCPs give the LLM dozens of tools: click, scroll, type, extract, navigate. Each call dumps the entire page accessibility tree into the context window. One Wikipedia page? 124K+ tokens. Every. Single. Call. OpenBrowser works differently. It exposes one tool. Your agent writes Python code, and OpenBrowser executes it in a persistent runtime with full browser access. The agent controls what comes back. No bloated page dumps. No wasted tokens. Just the data your…
Apr 2026 · openbrowser.me · its alternatives →
- 8
Code Llama 70B▲144New, performant version of Meta's LLM for code generation
2024 · developer.meta.com · its alternatives →
- 9AT
I recently built a small open-source tool to benchmark different LLM API endpoints — including OpenAI, Claude, and self-hosted models (like llama.cpp). It runs a configurable number of test requests and reports two key metrics: • First-token latency (ms): How long it takes for the first token to appear • Output speed (tokens/sec): Overall output fluency Demo: https://llmapitest.com/ Code: https://github.com/qjr87/llm-api-test The goal is to provide a simple, visual, and reproducible way to evaluate performance across different LLM providers, including…
2025 · llmapitest.com · its alternatives →
- 10
Gram Functions▲119Hi HN, Georges from the Gram team here. We're really excited to share a major update to Gram, our platform for curating tools for agents, in the form of Gram Functions. Gram initially started out by letting users upload OpenAPI documents and turning them into tools that can be curated into small MCP servers that power your agentic use cases. We've known for quite some time that many existing REST APIs are simply not suitable as LLM tools and we wanted to solve this problem by letting users simply write code and we would take care of deploying that code for them and hosting MCP servers. We…
Nov 2025 · speakeasy.com · its alternatives →
- 11
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 →
- 12
Recently featured in a LangChain blog https://blog.langchain.dev/empowering-development-with-flowt... , use LLMs to construct an API first runnable workflow with an IDE experience.
2024 · github.com · its alternatives →
- 13
Hey HN – Gregor & Magnus here again. A few months ago, we launched Browser Use (https://news.ycombinator.com/item?id=43173378), which let LLMs perform tasks in the browser using natural language prompts. It was great for one-off tasks like booking flights or finding products—but we soon realized enterprises have somewhat different needs: They typically have one workflow with dynamic variables (e.g., filling out a form and downloading a PDF) that they want to reliably run a million times without breaking. Pure LLM agents were slow, expensive, and unpredictable for these…
2025 · github.com · its alternatives →
- 14
Hi HN! Stefan here from superglue and today I’d like to share a new benchmark we’ve just open sourced: an Agent-API Benchmark, in which we test how well LLMs handle APIs. We gave LLMs API documentation and asked them to write code that makes actual API calls. Things like "create a Stripe customer" or "send a Slack message". We're not testing if they can use SDKs; we're testing if they can write raw HTTP requests (with proper auth, headers, body formatting) that actually work when executed against real API endpoints and can extract relevant information from that response. tl:dr: LLMs suck at…
2025 · github.com · its alternatives →
- 15
So, it feels like this should exist. But I couldn't find it. So I tried to build it. Agentflow lets you run complex LLM workflows from a simple JSON file. This can be as little as a list of tasks. Tasks can include variables, so you can reuse workflows for different outputs by providing different variable values. They can also include custom functions, so you can go beyond text generation to do anything you want to write a function for. Someone might say: "Why not just use ChatGPT?" Among other reasons, I'd say that you can't template a workflow with ChatGPT, trigger it with different…
2023 · github.com · its alternatives →
- 16
Single-agent LLMs suck at long-running complex tasks. We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress. How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents We tested this on a Putnam-level math problem, but the…
Feb 2026 · github.com · its alternatives →
- 17
Anthropic released the Model Context Protocol a couple weeks ago - https://www.anthropic.com/news/model-context-protocol. They have official sdks for python and typescript but nothing for go, so I wrote one! The main goal is to provide a low boilerplate sdk to write MCP servers, you can spin up a server which can give an LLM access to weather forecasts like this: https://github.com/metoro-io/mcp-golang/blob/main/examples/g... . Using it here: https://youtu.be/xaMkMl_R-0A The library handles generating all the MCP…
2024 · github.com · its alternatives →
- 18
Hi HN, I spent my easter weekend stuck in the house with COVID and I decided to play with llama.cpp [1] and fauxpilot [2] to see if I could get LLM code assist working on pure CPU. As a proof of concept I'd say I've proven that it's possible. However there's still a lot to do. The auto complete is quite slow at the moment. PRs welcome. [1] https://github.com/ggerganov/llama.cpp [2] https://github.com/fauxpilot/fauxpilot
2023 · github.com · its alternatives →
- 19LF
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 · its alternatives →
- 20
Hi HN! Run it: OPENROUTER_API_KEY="sk" npx bff-eval --demo We built a tool to help people take LLM outputs and easily grade them / eval them to know how good an assistant response is. We've built a number of LLM apps, and while we could ship decent tech demos, we were disappointed with how they'd perform over time. We worked with a few companies who had the same problem, and found out scientifically building prompts and evals is far from a solved problem... writing these things feels more like directing a play than coding. Inspired by Anthropic's constitutional ai concepts, and amazing…
2025 · github.com · its alternatives →
- 21
Hey HN. I built this because my Anthropic API bills were getting out of hand (spoiler: they remain high even with this, batch is not a magic bullet). I use Claude Code daily for software design and infra work (terraform, code reviews, docs). Many Terminal tabs, many questions. I realised some questions are ok to wait on and with that comes some cost savings. So here is a small MCP that lets you send work directly to Anthropic's Batch API from inside Claude Code, for the same quality responses just 50% cheaper, results come back in ~30min-1hr. How it works: you type /batch review this…
Feb 2026 · github.com · its alternatives →
- 22
The from-scratch guide to building large language models in NodeJS.
8d ago · book.humanexperiences.io · its alternatives →
- 23
Hey HN! We just released a new library for building LLM-powered applications: @axflow/models. It is part of a larger suite of libraries we're developing for TypeScript developers working with generative AI. This library provides the simplest APIs for 1) invoking the most popular LLM and embedding models (openai, anthropic, cohere, huggingface, etc.) 2) streaming LLM responses to clients, including augmenting the streams with additional arbitrary data and 3) building client-side applications with React hooks. @axflow/models has zero dependencies and is built using only the…
2023 · docs.axflow.dev · its alternatives →
- 24
Hey HN, I built browser-use, an open-source alternative to OpenAI’s Operator for browser-use systems, and here’s why I think it’s better: Flexibility: You can use any LLM with our tool – Gemini, Anthropic, Qwen, Llama, DeepSeek, and more. As new models improve, so does your agent. Open Source: No need to pay $200/month or endure long waitlists – it’s free and accessible to everyone today. Custom Automation: Our Python package allows you to build actual web automations. Your LLM can gain new tools, like file uploads. Cost: Our system is 30x cheaper than Operator, e.g., when used with…
2025 · github.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →