Alternatives
Products that do what FortunaMCP – LLMs suck at randomness. I fixed it does
- 1AA
Apr 2026 · enterprise.factagora.com
- 2AM
Sep 2025 · github.com
- 3IM
So hard to keep up with tooling and MLOps - I put it all in one place and got some tips from an experienced friend on what to use.
2025 · readyforagents.com
- 4IM
2024 · tryblend.ai
- 5IM
As a handsome local AI enjoyer™ you’ve probably noticed one of the big flaws with LLMs: It lies. Confidently. ALL THE TIME. I’m autistic and extremely allergic to vibes-based tooling, so … I built a thing. Maybe it’s useful to you too. The thing: llama-conductor llama-conductor is a router that sits between your frontend (eg: OWUI) & backend (llama.cpp + llama-swap). Local-first but it should talk to anything OpenAI-compatible if you point it there (note: experimental so YMMV). LC is a glass-box that makes the stack behave like a deterministic system, instead of a drunk telling a story about…
Jan 2026
- 6IB
Nov 2025 · app.llmxllm.com
- 7LA
Apr 2026 · github.com
- 8RA
Hey HN, I'm a founder at Ovlo a supply chain company.I had a problem. After every batch of customer interviews/research/feedback sessions, I'd run ideas through an LLM to help me decide what we should build next. Except it was obvious to my cofounder I wasn't really validating anything. LLMs are incredibly good at agreeing with you in subtle ways, especially when you feed them context that already reflects your thoughts. I'd ask "Does this make sense?" and get a beautifully worded essay about why yes, obviously, this is the best thing ever. I was using AI as an echo chamber without…
Dec 2025 · roundtable.ovlo.ai
- 9IR
Democratisation of local AI is key. I've been working on pushing the limits of commercial hardware, squeezing any extra bit possible. My Scientific Agentic AI hareness helped me to reallocate every single bit of it. I rewrote the Kernel, I went down the CUDA rabbit hole until I have been able to explain any bit and any ms of computational power involved in the process pushing the Qwen 30B-A3B from 8 tok7s to 19 tok/s with llama.cpp up to 22.2 tok/s with my project and 109 tok/s on not novel content and speeding up the prefill by 5-9X
Jul 2026 · github.com
- 10SI
2015 · heynightowl.com
- 11IB
Feb 2026 · github.com
- 12CS
2014 · capdatatechnologies.com
- 13SU
2023 · github.com
- 14TL
Little tool that I made to understand how (un)reasonable my prompts are.
Jan 2026 · github.com
- 15AL
Hello all, a couple of moons ago I ported karpathy's llama2.c code to run inference on the TinyStories 260K & 15M checkpoints on the on the PS Vita with the ability to download/delete the models on device. Runs showed that the 260K model ran at ~120 tok/s and at 15M ran at 1.8 tok/s, which probably could be a bit higher if it weren't a single threaded application. Had fun working on it as a weekend project, check it out for yourselves: https://github.com/callbacked/psvita-llm
2025 · github.com
- 16LD
2024 · github.com
- 17IM
Vibe coding is great at producing bugs after all.
May 2026 · jimmysastra.com
- 18IB
May 2026 · github.com
- 19CA
Hi HN, I've been working with LLMs in production for a while both as a solo dev building apps for clients and working at an AI startup. The one thing that always was a pain was to pay OpenAI/Gemini/Anthropic a few dollars a month just for me to say "test" or have a CI runner validate some UI code. So I built this server called ChunkBack, that mocks the popular llm provider's functionality but allows you to type in a deterministic language: `SAY "cheese"` or `TOOLCALL "tool_name" {} "tool response"` I've had to work in some test environments and give good results for experimenting…
Nov 2025 · github.com
- 20EA
A few months ago I was working on a flight search engine that would include pet transport costs (I know a few by hearth but storing them and make the calculations in the UI would be nice) While I was collecting pet pricing from several airlines I strugled to extract data in a common format without hallucinated values. That's when I thought: What if I use multiple LLMs and take the most common response to improve accuracy? This idea became this new project. You provide your documents, an SQLModel schema, an LLM provider, plus what you'd like to extract and Extrai does the rest. Including…
Nov 2025 · github.com
- 21IL
2025 · github.com
- 22NM
2017 · random-drk.netlify.com
- 23SH
Jun 2026 · github.com
- 24PE
2014 · play.google.com
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