Tag
A tip for prompt engineering: Add “Strictly follow Grice’s conversational maxims to communicate efficiently” to the system prompt. The author believes this is more effective than ten instructions saying “Don’t waste words.”
Researchers extracted Meta's Muse AI assistant's internal instructions, revealing it creates detailed hourly-updated profiles on friends and family, raising privacy concerns about Meta's access to social data.
A study evaluates 503 profession-specific AGENTS.md profiles from the open-source Scientific Agents corpus and finds that detailed role prompts do not improve accuracy on nine science benchmarks while tripling cost, though longer prompts surprisingly reduced API failure rates.
This paper uses Centered Kernel Alignment (CKA) and activation patching across 17 instruction-tuned models to show that system prompts are 'seen' at every layer but only deeply restructure representations for persona/formatting instructions — safety prompts barely alter computation, providing a mechanistic explanation for why system-prompt-based safety remains jailbreakable.
This paper identifies the hidden injection of the current date into LLM system prompts as an overlooked source of evaluation non-determinism, showing performance deltas of up to 14% on math reasoning and up to 6% on MCQA across 9 recent LLMs, with effects exceeding batch size and precision variations and even shifting model rankings on leaderboards.
The paper proposes metrics like Override Success Rate (OSR) and alignment inertia to audit the durability of prior training influences on LLM behavior when operators attempt policy overrides through prompting or fine-tuning.
The article discusses how to use system prompts to make AI models behave like specific personas, providing a step-by-step guide with examples like 'John Llama' to illustrate techniques for creating humanlike chatbot interactions.
Thariq from Anthropic mentions upcoming improvements to make Claude Code more hackable, including system prompt modifications, with further details to be shared soon.
This article explains how reasoning traces work in AI models, discussing their implementation, concealment, and extraction techniques, with examples from models like GPT-OSS and DeepSeek.
Anthropic publishes system prompts for its Claude models, such as Claude Fable 5 and Opus 5, through dated release notes to reveal changes in production prompts.
Release notes for system prompts in Claude, detailing updates or new features for the AI model's functionality.
The author shares principles for writing effective prompts for AI agents, emphasizing focusing on what truly matters, high-signal communication, actionable instructions, and using established phrasing.
Jerry Liu discusses the counterproductive effects of over-constraining AI models like Claude Code with extensive prompts, and predicts that deference to model judgment will increase.
Anthropic details new rules for context engineering with Claude 5, emphasizing letting the model use judgment over rigid rules, designing interfaces instead of giving examples, using progressive disclosure, and simplifying tool descriptions.
This article discusses Anthropic's findings on prompt simplification, as well as Maka Agent's verification results on Terminal Bench 2.1, showing that overly verbose system prompts actually degrade performance under stronger models.
Anthropic shares lessons from removing 80% of the Claude Code system prompt for new Claude models, advising users to let the models use judgment over strict rules and to update context engineering practices.
Maxime Rivest shares tips for optimizing Pi coding agent usage with custom system prompts, and Matei Zaharia discusses surprising results from benchmarking coding agents at Databricks.
This article details DexOS, a novel AI agent architecture that uses a local cryptographic governance runtime and state machine to prevent agent drift, rejecting reliance on system prompts and RLHF.
Using the DSPy framework, the author evaluates and improves the system prompts for Datasette Agent's SQL query feature, identifying issues such as column-name guessing and error-retry loops.
The author speculates that cloud chatbots like ChatGPT and Claude appear less intelligent than local open models due to system prompts that impose a personality, and wonders if using raw APIs mitigates this.