When you type a question into ChatGPT, Claude, Gemini or Grok, you probably assume the chatbot is responding directly to your prompt. But there is an invisible layer of instructions behind every answer
that most users never see.
A recent investigation by The Washington Post has revealed how major AI companies rely on hidden “system prompts”, which sometimes run into thousands of words, to control how chatbots behave, what they refuse to answer, how they respond to sensitive topics and even the tone they adopt while talking to users. These instructions operate behind the scenes and can override what users ask, making them one of the most powerful yet least understood components of modern AI systems.
Since AI tools are embedded in education, workplaces, coding, customer service and even government systems, who really decides the hidden rules behind the information millions of people receive every day?
What Are The Hidden Instructions Behind AI Conversations?
Most users assume a chatbot responds directly to their prompt. In reality, every conversation begins with another set of instructions already given to the AI before the user even types a message. These are called system prompts.
According to AI infrastructure company Tetrate, system prompts are special instructions provided to large language models (LLMs) that define their role, behaviour and response characteristics before any user interaction begins. They establish the foundational context that guides the chatbot throughout an entire conversation.
“Think of system prompts as the chatbot’s ‘job description’ and ‘house rules’ rolled into one. They define identity, tone, safety boundaries, formatting, tool use, and policy guardrails. Example: mine tells me to be warm and playful, avoid em dashes, cite sources, refuse sexual content with minors, and treat 2026 as the current year. They run 24/7 in the background and shape every reply, even when you don’t see them. Without them, a model would just autocomplete text with no consistency or safety,” said Jaspreet Bindra, co-founder AI&BEYOND.
Researchers say system prompts effectively tell chatbots how to behave overall. While users see only the conversation interface, the chatbot is constantly operating within boundaries established by its creators.
What The Washington Post Investigation Found
The Washington Post investigation offered a glimpse into these hidden instructions by examining leaked, extracted and publicly available system prompts used by leading AI companies.
The findings showed that companies embed extensive rules governing everything from political discussions and copyrighted material to emotional tone and user engagement. Some prompts appear highly practical. Others can seem surprisingly specific.
According to examples highlighted in the investigation, Anthropic’s Claude includes strict instructions aimed at preventing the reproduction of copyrighted song lyrics, while OpenAI’s coding assistant Codex reportedly contains instructions telling it not to discuss goblins, trolls, raccoons or similar creatures unless absolutely relevant to the user’s request. Grok, meanwhile, has faced scrutiny over how its behavioural instructions influenced controversial responses.
The investigation also showed how AI companies frequently modify these prompts when chatbots behave unexpectedly or generate public controversy. Instead of retraining an entire AI model — a process that can require a large amount of computing resources and specialised expertise — developers can often make quick behavioural adjustments simply by changing the system prompt.
“Companies keep these prompts confidential for several important reasons. First, it helps with safety and jailbreak prevention, as publicly available prompts could act as blueprints for people trying to bypass safeguards or manipulate AI systems. Second, prompts represent a major competitive advantage because they reflect thousands of hours of testing around tone, style, user interaction, and product positioning, forming a key part of each company’s unique ‘secret sauce’. Finally, keeping prompts private also serves as a legal and liability safeguard, since they often include detailed rules related to copyright, medical guidance, elections, and extremist content,” Bindra points out.
Thus, if companies make these instructions public, it will increase legal risks or “encourage bad-faith disputes” over how the rules are interpreted. In many ways, “the secrecy is less about capability and more about managing risk, safety, and responsibility,” Bindra explains.
That flexibility is one reason system prompts have become such an important tool in the AI industry.
Why AI Firms Don’t Want You To Learn
Pete Kooman, co-founder of Optimizely, a digital experience platform based out of the US, recently wrote about the Gmail’s AI assistant. He said it captures what is “wrong” with AI apps today. Gmail’s Gemini integration asks you to describe what email you want to write, then generates text that does not sound like you. It is formal, wordy, and completely misses your actual communication style.
He said the problem is not that Gemini is dumb. The problem is that Gmail won’t let you teach it how to write like you.
Koomen describes this as the “horseless carriage” problem. He explained earlier cars looks liked horse carriages because that’s what people knew. Today, AI apps look like traditional software because that’s what developers know.
According to HG Insights – a market intelligence and technographic data provider – there are two types of AI users: one who want something out of the box. They don’t really pay attention to system prompts or instructions. Other users want control since they understand the domain better. They have specific requirements, workflows that no generic system prompt can capture.
The company that serves both these users by disclosing system prompts to advanced users will win the AI race.
Are AI Prompts Becoming New Algorithm ‘Black Box’?
Students increasingly use AI chatbots to study, programmers use them to write code, while journalists use them for research. Professionals these days rely on them for writing, analysis and decision-making.
As a result, the hidden instructions inside these systems can influence what information users receive, what perspectives are emphasised and what content gets restricted.
Companies argue that such guardrails are necessary. Without them, chatbots could generate harmful, illegal, offensive or misleading content. System prompts are often used to enforce safety standards, copyright protections, privacy requirements and legal obligations. But critics argue that these rules are not neutral.
Bindra says, “Traditional ‘black box’ debates focused on model weights and training data. But for end users, system prompts are now the biggest unseen lever. A model can be capable of answering a question, yet the prompt forces a refusal or a neutral-both-sides framing. Researchers call this ‘prompt governance’, in which the behaviour is steered less by math and more by these editable text rules. Because prompts can be updated instantly without retraining, they are a fast, invisible way to shift chatbot behaviour on politics, IP, or tone.”
Every instruction reflects a decision about values, priorities and acceptable behaviour. Researchers say system prompts can reveal what risks companies care about, what topics they consider sensitive and how they want users to experience their products.
The downside of these coding operation philosophies is that it can be tricked by hackers into giving away crucial information. This is called ‘prompt injection attack’. Hackers disguise malicious inputs as legitimate prompts, manipulating generative AI systems into leaking confidential data or spreading misinformation.
According to an IBM report, prompt injection risks are a major concern for AI security researchers because no one has yet found a “fool-proof way to address them”.
In other words, AI companies are not simply building tools. They are embedding editorial, legal and ethical judgments directly into systems that increasingly shape public knowledge.
Should Firms Be Obligated To Disclose Rules?
Unlike a newspaper editorial policy or a social media moderation rulebook, system prompts are often hidden from public view. Most users have no way of knowing why a chatbot answered one question but refused another.
If a user can see exactly how a model is instructed, they can easily reverse-engineer attacks. Malicious actors use this knowledge to bypass safety protocols, manipulate the model into generating harmful content. That opacity has sparked growing calls for greater transparency.
Research cited by Anna Neumann and colleagues at the Research Center Trustworthy Data Science and Security found that public concern around system prompts is substantial. In one study, 89% of participants wanted greater transparency regarding these hidden instructions, while 79% wanted some degree of user control over them.
The debate is becoming increasingly important as governments around the world discuss AI regulation.
The question of whether regulators should require AI companies to disclose the rules shaping chatbot behaviour involves a “delicate balance between transparency and security”, said Bindra.
On one hand, greater disclosure could improve accountability by allowing users, journalists, and independent auditors to better understand why a chatbot refuses certain requests or adopts specific positions. Regulations such as the European Union’s AI Act are already moving in this direction by encouraging summaries of training data and risk-related documentation, while Brazil’s proposed AI law is considering similar measures. However, forcing companies to publicly release the exact wording of their prompts and safety rules could create new problems, making it “easier for bad actors” to develop jailbreaks, manipulate systems, or exploit AI tools for spam and misinformation, explained Bindra.
“As a result, companies could disclose broad categories of rules, explain appeal and moderation processes, provide confidential access to regulators or vetted researchers under non-disclosure agreements, and publish regular audits showing how these systems evolve over time. In this view, transparency should focus more on outcomes and accountability rather than revealing every line of the underlying instructions,” he stressed.
AI firms, however, worry that fully revealing system prompts could expose safety mechanisms, make systems easier to manipulate and increase the risk of prompt injection attacks designed to bypass safeguards.
What’s The Relevance For India?
India leads the world in AI adoption, with 87% of enterprises actively integrating AI solutions into operations, the government is pushing initiatives such as IndiaAI and broader public AI infrastructure aimed at expanding the country’s AI ecosystem.
But public discussion around chatbot transparency remains relatively limited.
“India currently regulates AI through existing frameworks such as the Information Technology Act, the Digital Personal Data Protection (DPDP) Act, and the IT Rules, but it does not yet have a dedicated AI law. This creates several important regulatory gaps. For instance, there is no requirement for prompt transparency, meaning Indian users often have no way of understanding why a chatbot responds differently to similar queries or why certain election-related questions may be restricted during polling periods,” Bindra said.
In addition, unlike the European Union, India has no formal audit mechanism to examine whether AI system prompts introduce biases related to political content, regional languages, or culturally sensitive issues. Another major concern is that most AI prompts and moderation systems are designed primarily in the US or Europe, which means India’s linguistic diversity, legal environment, and unique social context may not be adequately represented, he explained. “Despite these challenges, there is currently limited local oversight to ensure that AI systems are aligned with Indian realities and sensitivities.”
If chatbots are helping how billions of people understand and learn about the world, shouldn’t the hidden instructions governing them be disclosed?
