Alternatives
Products that do what LLMBlitz.io does
LLM Not listening? LLM response keeps changing?
- 1WW
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
- 2RY
Hey HN, we've just finished building a dynamic router for LLMs, which takes each prompt and sends it to the most appropriate model and provider. We'd love to know what you think! Here is a quick(ish) screen-recroding explaining how it works: https://youtu.be/ZpY6SIkBosE Best results when training a custom router on your own prompt data: https://youtu.be/9JYqNbIEac0 The router balances user preferences for quality, speed and cost. The end result is higher quality and faster LLM responses at lower cost. The quality for each candidate LLM is predicted ahead of time…
2024 · unify.ai
- 3PE
Nowadays, a common AI tech stack has hundreds of different prompts running across different LLMs. Three key problems: - Choices, picking from 100s of LLMs the best LLM for that 1 prompt is gonna be challenging, you're probably not picking the most optimized LLM for a prompt you wrote. - Scaling/Upgrading, similar to choices but you want to keep consistency of your output even when models depreciate or configurations change. - Prompt management is scary, if something works, you'll never want to touch it but you should be able to without fear of everything breaking. So we launched Prompt…
2024 · jigsawstack.com
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- 6RL
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
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- 8AI
Hi I am Jan, CTO @ Pathway. A use case we have been working on with LLMs is to let people know when an answer to their query changes due to revisions of source documents. Obviously, we want to avoid periodically re-computing all queries for the LLM. Why I think it’s cool? - We don’t spin in a loop to repeat with the LLM. - Alerts are LLM-deduplicated - no spamming users with typo fixes - And the best - our framework, Pathway takes care of handling the updates, the example looks nearly like a regular, static RAG chatbot. More context + GIF of how it works for Google Drive document alerts:…
2023 · github.com
- 9CL
I tried to port LLMLingua-2's official Python implementation into TypeScript. For best performance, open the URL with a WebGPU enabled web browser. Learn More: https://github.com/atjsh/llmlingua-2-js
2025 · atjsh.github.io
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- 11SW
Chrome now includes a native on-device LLM (Gemini Nano) starting in version 138. I've been building with it since it was in origin trials, it's powerful but the official Prompt API is still a bit awkward: - Enforces sessions even for basic usage - Requires user-triggered downloads - Lacks type safety or structured error handling So I open-sourced a small TypeScript wrapper I originally built for other projects to smooth over the rough edges: github: https://github.com/kstonekuan/simple-chromium-ai npm: https://www.npmjs.com/package/simple-chromium-ai…
2025 · github.com
- 12LA
I used to play the Wikipedia Game in high school and had an idea for applying the same mechanic of clicking from concept to concept to LLMs. Will post another version that runs with an LLM entirely in the browser soon, but for now, please enjoy as long as my credits last... Warning: the LLM does not always cooperate
Jan 2026 · llmgame.ai
- 13GV
Hey HN, I just updated my project that compares some LLMs. It uses your prompt for all the models and runs at the same time. You can see the results being generated in real-time and decide what's the best for your use case. I'm open to any suggestions and feedback. Thanks!
2024 · geminivsgpt.com
- 14MC
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
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- 16LI
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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- 18LB
For the past few months I've been building a lot of things with LLMs (GPT-3, Codex, etc.) as I've been trying to push them to their limits (especially towards applying them to the tabular data domain) When working on this, I've found there are some common patterns for solving problems (templating, chaining, functional-programming style operations, etc.) As I've iterated, I've come to believe that a functional style interface is likely going to power a new wave of systems I'm calling "prompt-machines"(systems where the core new unit of work is a "named" LLM prompt, extending the "function"…
2022 · github.com
- 19EL
Hey HN! I built Experiment to solve a common frustration in LLM development: the lack of proper tools for prompt engineering experimentation. Here's what makes it different: Key Features: - Load and edit chat completion logs from CSV files - Fork and modify specific conversation entries - Run inference via Anthropic, Mistral, and OpenAI - Define custom tools using JSONSchema format - Visual tool usage analysis with collapsible, sorted key-value pairs - Full mobile support and available as installable PWA Technical Highlights: - Built with React using custom isomorphic architecture -…
2025 · github.com
- 20HP
Hi HN. I heard you like dev tools and AI, so we wanted to share our project that we’ve been working on. We’re working on Horizon [1] - a higher level abstraction for LLMs so that developers can spend less time trying to grapple with LLMs to make them work and more time with users. This is the starting feature set which takes an auto-ML approach to identify the optimal LLM model, hyperparameters, and prompt - instead of just giving you the tooling to figure it out yourself. You can read more about it in our documentations. Our view is that as LLMs become increasingly commoditized and prompts…
2023 · gethorizon.ai
- 21LO
Hi HN! I built LLM OneStop (https://www.llmonestop.com), a unified interface for accessing multiple AI language models in one place. The main problem I wanted to solve: constantly switching between different AI platforms, managing multiple subscriptions, and losing conversation context when comparing outputs across models. Key features: Switch between GPT-4, Claude, Gemini, Llama, and other models mid-conversation Compare responses side-by-side Single interface instead of juggling multiple tabs/subscriptions Free tier available to try it out (no credit card needed) "Connect"…
Nov 2025 · llmonestop.com
- 22FA
LLM agents rely on tool calls — but tool responses are huge. Gmail, CRMs, and APIs return bloated JSON LLMs choke on large responses You only need 2–3 fields, but frameworks give you zero control Toolflow is an AI-native framework to fix this: * Filter tool responses before they hit the LLM * Context modes: `minimal`, `full`, `custom`, or `ai` * Composable TypeScript tool registry GitHub: [https://github.com/dksingh1997/toolflow](https://github.com/dksingh1997/toolflow) Would love feedback — especially from those building with LLMs in production.
2025 · github.com
- 23AL
any-llm is a library that provides unified access to multiple LLM providers. switching between providers like OpenAI, Anthropic, Google, Mistral, and even Ollama is just a string change. This demo makes it easy to look at and compare responses from different models. Interesting to see how ChatGPT, Claude, Gemini, and local models each reason through the same problems. Let us know what you think!
2025 · github.com
- 24LC
Hey, folks here is a peek into Jujutsu. We at Poozle are working with hundreds of APIs and it has been always frustrating to 1. Search the API in the documentation or ask ChatGPT 2. Then copy it to the postman and understand/test the API 3. Generate code to integrate into the codebase We thought how about having all of this at one place. We currently fine-tuned LLM on public REST APIs to reduce hallucination and then combined it with ChatGPT and Postman. I look forward to feedback, feature requests and discussions!
2023 · loom.com
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