Tech • IA • Crypto
Claude 4.7 le prompt system enfin accessible !
8/10TL;DR
The evolution of prompt systems from Claude 4.6 to 4.7 reveals a major shift in how AI models handle search and decision-making logic.
KEY POINTS
A structured and dense prompt architecture
The system relies on dozens of pages of instructions, up to 50 pages for version 4.7. These documents precisely define model behavior, using short, directive, almost technical sentences, closer to a programming language than natural text.
Three fundamental pillars of reasoning
Each request is processed according to three core questions: what context to retrieve, what action to execute (tool or function), and how to verify the relevance of the result. This structure forms the core of so-called “agentic” systems, capable of decision-making and automation.
A deeply modified search logic in 4.7
Version 4.7 enforces a key rule: perform a search before every factual question. In 4.6, this step was only triggered if internal knowledge was considered outdated. This change increases token usage but improves the reliability and freshness of responses.
The central role of “gathering context”
Models use dedicated functions to collect information: web search, file reading, image analysis, or data extraction. This mechanism feeds decision-making and determines when available tools are activated.
Tools driven by precise triggers
Tool usage relies on detailed descriptions and activation conditions. Each word in a query can influence the activation of specific neurons, inherited from model training, and trigger particular behaviors.
An execution system close to a real environment
Some functions simulate a full computing environment, such as a Linux Ubuntu system, with storage in virtual directories like /mnt/user/data/output. The model must anticipate and structure its actions as if executing real code.
Advanced control and restriction mechanisms
The system distinguishes three possible responses: yes, no, or maybe with redirection. Refusals notably cover copyright, access to sensitive data, or limits related to the knowledge cutoff. An intermediate zone handles ambiguous cases.
A new ability to end a conversation
Unlike previous versions, Claude 4.7 can trigger an “End conversation” function under certain conditions, especially in cases of attempts to extract sensitive data. This evolution addresses security concerns related to chatbot attacks.
Limited impact of raw performance, but major impact on usage
Performance differences between 4.6 and 4.7 remain small, around 2% according to benchmarks. However, how prompts are written and structured radically transforms model behavior, highlighting the strategic importance of prompt engineering.
CONCLUSION
The transition to Claude 4.7 marks a turning point in AI design, where prompt structuring and search logic now matter as much as the model’s raw performance.