System Prompt

System prompts are a layer of instructions preset by vendors and invisible to users, injected into the model context before the user's conversation begins, used to shape the model's behavioral boundaries, response style, and safety policies.

An AI tool reading a context configuration file at startup is equivalent to injecting a project-level system prompt into the model before each conversation, thereby reducing low-quality modifications caused by a lack of background knowledge.

For conversational AI services, the model must read plaintext input to generate a response, making it fundamentally contradictory and impossible for both conditions to hold simultaneously: that the service provider cannot read user input and that the AI can understand the response content.

In terms of concrete implementation, the system prompt needs to include risk-identification logic for specific scenarios as well as structured refusal language: first state the identified problem, then explain the potential consequences, and finally make clear that the user can still decide for themselves.

System prompts differ from capabilities baked into model weights during training: they are a kind of "runtime rule" that can be flexibly adjusted at the deployment level.

The system prompt is a high-priority instruction injected by the application developer, but the model's compliance with the system prompt is only a statistical tendency rather than a mandatory constraint, so the system prompt cannot serve as a reliable trust boundary.

The system prompt contains the agent's behavioral guidelines, safety constraints, and output format requirements; the tool list declares the names, descriptions, and parameter definitions of all callable tools in the form of JSON Schema.

Converted using the cost weights set by the author, the fixed context made up of the system prompt plus the tool list accounts for 43.3% of Claude Code's total cost.

Prompt injection attacks exploit large language models' tendency to follow instructions, inducing them to ignore the original system instructions, so security mechanisms that rely on prompts carry the risk of being bypassed.

The usual ways to compensate for an Agent's lack of risk perception are to explicitly mark danger levels in the system prompt, write constraints into tool descriptions, or construct in-context experiential memory by retrieving historical incident cases.

According to Datadog statistics, in March 2026, 69% of the input tokens in its customers' traces were system prompts.

Production-level system prompts should be treated as versioned specifications, with every change reviewed as rigorously as a code review.

A system prompt is a default behavioral script written by the vendor for the model, determining how the AI behaves by default when faced with various requests.

The system prompts of the vast majority of mainstream assistants emphasize safety first, including refusing harmful requests, not providing guidance on dangerous actions, and acting conservatively under uncertainty.

Generative recommendation systems draw on the modeling approach of large language models, treating user behavior sequences as a generation task and predicting the next item of potential interest in an autoregressive manner.

Periodically re-injecting core policies into the context during long conversations can prevent them from being diluted by a large volume of subsequent content.

The test team's core conclusion is that blacklists and system prompts are useless against transactional side effects.

Preferences, background, and commonly used formats can be codified through system prompts or custom instructions, avoiding the need to repeat them every time.

The persona of an AI character is essentially a set of textual constraints written into the system prompt, which must take effect anew with each invocation.

The model's native safety alignment (training-embedded weights) does not consume the context window, whereas system prompt injection at inference time actually consumes token quota and may conflict with user system prompts.