Prompt Engine – Auto pick LLMs based on your prompts
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…
Prompt Engine – Auto pick LLMs based on your prompts launched on December 6, 2024 with 93 votes, #411 of 5,365 launches that month and more than 90% of that year's launches. The site was still online in September 2026, 1 year on.
In plain words
Prompt Engine automatically selects the optimal large language model for each prompt from hundreds of available options, addressing the challenge of manual LLM selection. It provides prompt storage for reusability, caching to improve performance, and maintains consistency when models depreciate or configurations change. Designed for teams running multiple prompts across different LLMs, it eliminates fear of breaking existing workflows while enabling updates and upgrades.
written from the facts on this page · September 2026
From the sources
Applications that use LLMs typically tend to use more than one model or provider, depending on your use case. This is because not all LLMs are built the same, while GPT-4o might be good at basic customer support chat, Claude 3.5 Sonnet would be good ...
In the maker’s words, at launch
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…
Does a similar job
all alternatives →- APAutomatic prompt optimizer for LLMs2023 · promptperfect.jina.ai · ▲126
- RARL Agent that can auto-optimize your LLM prompts2024 · nomadic-ml.github.io · ▲14
Hey everyone! Along with my team, I've developed a reinforcement learning system that automatically optimizes LLM prompts, complete with a visualization feature to track both prompt structure and learning progress over time. Take a look here: https://nomadic-ml.github.io/nomadic/cookbooks/Nomadic_Promp... Check out our website too:https://www.nomadicml.com/ In terms of how this visualization works: The RL Prompt Optimizer employs a reinforcement learning framework to iteratively improve prompts used for language model evaluations. At each episode, the…
- RARelari – Auto Prompt Optimizer as Lightweight Alternative to Finetuning2024 · ▲32
Hi HN, we are the founders of Relari (https://www.relari.ai). We launched our LLM evaluation stack on HN a few months ago (https://news.ycombinator.com/item?id=39641105), which is now used in production by AI teams at companies like Vanta and PwC. We have since expanded to directly optimizing parts of an LLM pipeline using a data-driven approach. In particular, we see a lot of potential in the Auto Prompt Optimization—which could be an attractive alternative to fine-tuning in many cases—to use data to align LLMs for domain-specific tasks. Here’s a demo video:…
AI-assisted prompt builder2023 · outset.ai · ▲61Integrate LLMs into your product in minutes with AI's help
2000 Large Language Models (LLM) Prompts2023 · miguelanticonam.gumroad.com · ▲106Unlock your knowledge with 2000 LLM prompts
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Source: Show HN post ↗ · launch text quoted in part
