This article discusses how the newest generation of Claude models necessitates a shift in context engineering. Anthropic found that they could remove over 80% of their system prompts without losing performance on coding evaluations by moving away from rigid, often conflicting instructions and instead allowing the model's inherent judgment to guide its behavior based on surrounding context.
Key shifts in methodology include:
- Moving from strict rules to letting models use judgement for nuance such as documentation style or intent interpretation.
- Prioritizing intuitive tool interface design over providing restrictive examples that limit exploration.
- Implementing progressive disclosure by using skills and deferred loading to manage large context windows efficiently.
- Replacing repetitive instructions with streamlined, high-fidelity descriptions directly within tool definitions.
- Transitioning from manual memory management in files toward auto-memory and rich references like HTML artifacts or code snippets.
Key shifts in methodology include:
- Moving from strict rules to letting models use judgement for nuance such as documentation style or intent interpretation.
- Prioritizing intuitive tool interface design over providing restrictive examples that limit exploration.
- Implementing progressive disclosure by using skills and deferred loading to manage large context windows efficiently.
- Replacing repetitive instructions with streamlined, high-fidelity descriptions directly within tool definitions.
- Transitioning from manual memory management in files toward auto-memory and rich references like HTML artifacts or code snippets.
This document contains system prompt instructions for an AI model designed to function as a Gmail Assistant. It details specific protocols for managing email threads, including deciding between providing single or multiple reply options based on user input complexity. The instructions cover tone maintenance, strict prohibitions against hallucinating information not present in context, and precise formatting rules for greetings and sign-offs.
* Decision logic for generating one vs three replies
* Guidelines for maintaining professional email etiquette
* Constraints to prevent making up non-existent information
* Rules for extracting and listing action items from threads
* Decision logic for generating one vs three replies
* Guidelines for maintaining professional email etiquette
* Constraints to prevent making up non-existent information
* Rules for extracting and listing action items from threads
- Understanding why agentic loops increase token costs over time
- Techniques for selective information removal from prompt histories
- Strategies to maintain reasoning capabilities during compression
- Practical implementation steps for optimizing LLM workflows
- Techniques for selective information removal from prompt histories
- Strategies to maintain reasoning capabilities during compression
- Practical implementation steps for optimizing LLM workflows
An analysis of Claude's extensive system prompt, highlighting its components, including tool definitions, behavior instructions, and how it reflects Anthropic's development priorities. The article details changes between Claude 3.7 and 4.0, revealing a shift towards encouraging search functionality and addressing user-observed issues.
Generate terminal UIs (TUIs) with simple text prompts using AI.
"Generate 5 essential questions that, when answered, capture the main points and core meaning of the text. Focus on questions that:
Address the central theme or argument
Identify key supporting ideas
Highlight important facts or evidence
Reveal the author's purpose or perspective
Explore any significant implications or conclusions
Phrase the questions to encourage comprehensive yet concise answers. Present only the questions, numbered and without any additional text."
Address the central theme or argument
Identify key supporting ideas
Highlight important facts or evidence
Reveal the author's purpose or perspective
Explore any significant implications or conclusions
Phrase the questions to encourage comprehensive yet concise answers. Present only the questions, numbered and without any additional text."
code2prompt is a command-line tool (CLI) that converts your codebase into a single LLM prompt with a source tree, prompt templating, and token counting.
A prompt template containing prompting techniques that have worked for the author on over a dozen nuanced medical information extraction tasks.
Stay informed about the latest artificial intelligence (AI) terminology with this comprehensive glossary. From algorithm and AI ethics to generative AI and overfitting, learn the essential AI terms that will help you sound smart over drinks or impress in a job interview.
