prompter
PulseAugur coverage of prompter — every cluster mentioning prompter across labs, papers, and developer communities, ranked by signal.
5 day(s) with sentiment data
-
LLM extraction prompts improved by analyzing error signatures
This article proposes a method for improving large language model (LLM) extraction prompts by systematically analyzing and clustering correction data. Instead of directly incorporating individual human corrections into …
-
AI agents vulnerable to MCP server tool description prompt injection
A security vulnerability has been identified in how AI agents interact with MCP (Multi-Chat Protocol) servers, specifically concerning the vetting of tools provided by these servers. The core issue is that tool descript…
-
AI-generated political speeches should include prompts, user suggests
A user on Mastodon suggested that prompts used to generate political speeches and official communications should be publicly disclosed. This would allow citizens to understand the intended message behind AI-generated co…
-
New framework clarifies AI agent architecture into five layers
An AI agent's architecture can be understood through five distinct layers: Prompt, Context, Loop, Graph, and Harness. This framework helps developers diagnose and fix issues by identifying which layer is responsible for…
-
Model Context Protocol (MCP) primitives and server setup explained
The Model Context Protocol (MCP) is a framework for building agentic AI systems, offering primitives like tools, resources, and prompts. Tools are reusable functions for specific tasks, resources provide information for…
-
Mistral Studio adds prompt management, but true control needs more than versioning
Mistral AI has introduced a new prompt and skill management system within its Studio platform, aiming to bring production-level discipline to AI development. This feature allows prompts and skills to be treated as versi…
-
Decentralized AI emphasizes user data control with #Storageless concept
The concept of #Storageless is highlighted as crucial for #Decentralized #AI, emphasizing that only the #Prompter has a vested interest in their data. This approach suggests that a user's network #Reputation influences …
-
TCM OTC sector poised for profit recovery amid falling raw material costs
A report from CITIC Securities suggests the Traditional Chinese Medicine (TCM) Over-The-Counter (OTC) sector is poised for significant improvement. This optimism stems from a sharp decline in the prices of key raw mater…
-
Understanding the 800ms journey of a prompt in LLMs
This article delves into the intricate process that occurs when a user submits a prompt to a large language model, detailing the 800-millisecond journey from input to output. It explains the various stages involved, inc…
-
Few-shot examples can hurt LLM prompt performance
Adding more few-shot examples to an LLM prompt does not always improve performance, and can sometimes degrade it. In one experiment, a prompt with six examples performed worse than one with four, with the two additional…
-
AI agents are more than just prompts, requiring loops and tools
This article distinguishes between prompt engineering and agent development, arguing that agents are more than just extended prompts. It defines an agent as a runtime process composed of a model, a loop, tools, and stat…
-
AI Agents Defined: Runtime Process Beyond Simple Prompts
This article clarifies that building an AI agent involves more than just crafting a detailed prompt. An agent is fundamentally a runtime process comprising a model, a loop, tools, and state, designed to bridge the gap b…