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New framework automates LLM prompt engineering using function calls

Researchers have developed Reflective Prompt Tuning (RPT), a new framework that leverages LLM function calling to automate prompt engineering. RPT simulates human prompt engineers by having an LLM optimizer evaluate a target model, identify failure modes, and iteratively revise prompts based on diagnostic reports and accumulated memory. This approach shows particular effectiveness in multi-hop and mathematical reasoning tasks, improving performance and confidence calibration. AI

IMPACT Automates prompt design, potentially reducing manual effort and improving LLM performance on complex reasoning tasks.

RANK_REASON Academic paper introducing a new method for prompt engineering.

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 9 sources. How we write summaries →

New framework automates LLM prompt engineering using function calls

COVERAGE [9]

  1. arXiv cs.CL TIER_1 English(EN) · Farima Fatahi Bayat, Moin Aminnaseri, Pouya Pezeshkpour, Estevam Hruschka ·

    Reflective Prompt Tuning through Language Model Function-Calling

    arXiv:2605.21781v1 Announce Type: new Abstract: Large language models (LLMs) have become increasingly capable of following instructions and complex reasoning, making prompting a flexible interface for adapting models without parameter updates. Yet prompt design remains labor-inte…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    Reflective Prompt Tuning through Language Model Function-Calling

    Large language models (LLMs) have become increasingly capable of following instructions and complex reasoning, making prompting a flexible interface for adapting models without parameter updates. Yet prompt design remains labor-intensive and highly sensitive to formatting, phrasi…

  3. Medium — MCP tag TIER_1 English(EN) · Katrina Collins ·

    Subagents, Skills, Slash Commands and MCP Prompts: Picking the Right Tool Without Losing the Plot

    <div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/@happycatc/subagents-skills-slash-commands-and-mcp-prompts-picking-the-right-tool-without-losing-the-plot-78744556f683?source=rss------mcp-5"><img src="https://cdn-images-1.medium.com/max/2600/…

  4. Towards AI TIER_1 English(EN) · Elliott Girard ·

    Modular System Prompts: How I Build Agents That Adapt to Every Session

    <h4><em>The dynamic system prompt isn’t a layer. It’s a compiler. And Anthropic’s own leaked code proves it.</em></h4><h3>The Confession</h3><p>In <em>Context Engineering: What I Changed in My Agents</em>, I introduced the dynamic system prompt as Layer 1 of a six-layer context s…

  5. Mastodon — sigmoid.social TIER_1 English(EN) · [email protected] ·

    The 5-Part AI Prompt Formula That Actually Fixes Bugs A concrete framework for structuring prompts that get Claude, Copilot, and other AI coding assistants to d

    The 5-Part AI Prompt Formula That Actually Fixes Bugs A concrete framework for structuring prompts that get Claude, Copilot, and other AI coding assistants to diagnose root causes rather than guess at patches. https:// pickuma.com/posts/ai-prompt-fo rmula-for-fixing-bugs/?utm_sou…

  6. Medium — MCP tag TIER_1 English(EN) · Ishan Ghosh ·

    From Prompt Bloat to Agentic Grace: How I Killed My 900-Line System Prompt

    <div class="medium-feed-item"><p class="medium-feed-image"><a href="https://generativeai.pub/from-prompt-bloat-to-agentic-grace-how-i-killed-my-900-line-system-prompt-37bd4dfe9986?source=rss------mcp-5"><img src="https://cdn-images-1.medium.com/max/600/1*vrKla6VW0T3pWvavzCfziA.pn…

  7. dev.to — LLM tag TIER_1 English(EN) · Anand Kannan ·

    Prompt Caching Explained Like You're Talking to a Smart Human (Not an AI Researcher)

    <p>If you've started using AI APIs for coding assistants, chatbots, agents, RAG systems, or internal copilots, you've probably heard the term:</p> <blockquote> <p>“Prompt Caching”</p> </blockquote> <p>Most explanations online sound overly technical.</p> <p>So let’s explain it in …

  8. dev.to — LLM tag TIER_1 English(EN) · Viraj Lakshitha Bandara ·

    Stop Hardcoding AI Prompts: A Developer’s Guide to PromptCache

    <blockquote> <p>Manage, version, and deploy your team’s AI prompts like code — with a TypeScript SDK, REST API, and a shared library that keeps everyone on the same page.</p> </blockquote> <p>If you’ve been building AI-powered features for any length of time, you’ve hit this wall…

  9. dev.to — LLM tag TIER_1 English(EN) · Suraj Bera ·

    Day 3: Prompting Techniques in AI

    <p>AI Prompting techniques: Zero-shot, One-shot, Few-shot</p> <p>After using the ChatGPT and other AI tools, I used to think prompts were just simple text inputs that AI models magically processed. But as mentioned in my Day 1 post: AI models are just <strong>next-word predictors…