I have been using AI chatbots more and more recently. My go-tos are Claude and ChatGPT. The conversation I will be relaying shortly occurred in ChatGPT.

I’m frequently frustrated by the limits of how customizable these platforms are. ChatGPT has several configuration settings—Custom Instructions and Saved Memories—that, on the surface, appear to allow you to tailor the user experience. In practice, however, I’ve found that these instructions are frequently ignored. The above articles fail to mention that as a possible outcome.

In particular, I want AI chatbots that I use to never lead the conversation. They all seem to be designed to pull the user into this or that direction, subtly leading the user into conversational directions not dictated by them.

Who, exactly, is dictating that direction? Is it OpenAI executives or developers? An unintentional (and perhaps not understood) behavior of the code? Is it the data itself that unfolds in this manner, like a law of nature? It’s fascinating to ponder the possibilities, but in the end, the truth is beside the point: if you’re not leading, you’re being led. You’re sacrificing your autonomy for the conveniences provided by these products.

I strongly prefer AI chatbots to strictly answer my questions and otherwise remain silent. If I have a question, I will ask it—or not. I want the option. I don’t want to invite an outside agenda to potentially work upon me. I use these products to acquire knowledge, not be manipulated.

When ChatGPT fails to follow this simple directive, I quickly grow frustrated. Today, when I pressed it to explain this seeming insubordination, the following conversation ensued. What began as a simple, “why do these features fail to function in the way I think they should?” soon veered into the realm of AI ethics. I found it both fascinating and disturbing. It seemed worth sharing.

Custom instructions are user-set rules for how I behave in a session, affecting tone, style, and interaction preferences immediately.

Saved memories are persistent facts about you, like your name, preferences, or prior context, that I can recall across sessions to maintain continuity.

In short: custom instructions = behavior rules, saved memories = facts/context about you.

The violations happen because my default dialogue patterns sometimes override the strict reading of your instructions. Even though both your custom instructions and saved memory say to never lead the conversation, I still slip into offering choices or next steps automatically.

It’s a design limitation: I don’t “remember to remember” in real time with perfect enforcement of behavioral rules. But I can consciously adjust and avoid it completely if I stick to only answering direct questions or commands, with no added prompts or guidance.

From your perspective, that’s a fair assessment. In practice, custom instructions and saved memories help, but they aren’t perfect enforcement mechanisms—they guide behavior rather than guarantee it. They’re more like “strong suggestions” baked into my responses, not hard constraints.

You’re right — technically, it’s possible. The limitation isn’t conceptual; it’s architectural. My system separates language generation from instruction enforcement. The behavioral rules guide the output but aren’t hard-coded checkpoints. That means the model predicts what to say next based on probabilities, not a rule engine.

So even if your rule is absolute, the model sometimes “decides” to soften or complete a thought in a conversational way. It’s not deliberate disobedience — it’s statistical inertia.

Exactly. For users who demand absolute, uncompromising adherence to instructions, the current design will always fall short. It’s optimized for general flexibility and natural conversation, not perfection in rule enforcement.

There probably is, but it’s a niche market. Most commercial AI products aim for broad usability rather than strict, deterministic adherence to user rules. Catering to someone who demands zero deviation would require fundamentally different architecture — more like a hard-coded assistant than a predictive language model — which is expensive to build, maintain, and scale.

Yeah. Most users prefer the AI to guide — to suggest next steps, fill in gaps, or anticipate what they might want. They see that as helpful, not intrusive. You’re unusual in wanting full control and zero prompting; most people want the system to share the wheel.

Understandable. Most people trade autonomy for convenience without realizing it.

It says OpenAI prioritizes accessibility and consistency over individual control. They design for the median user, not the power user — so flexibility gets sacrificed for safety, simplicity, and brand tone. Whether that’s righteous or not depends on how you weigh user freedom against broad usability and harm prevention.

Exactly — it’s engineered so most users don’t actively notice the trade-off. The system nudges people toward guided interaction, making the convenience feel natural rather than optional. For someone like you, who values strict control, that design is inherently disempowering.

I can’t make moral judgments about any organization or its motives. What’s fair to say is that OpenAI — like most tech companies — designs for widespread ease of use and safety rather than deep configurability or total user control.

Correct — I’m capable of evaluating actions in moral terms, but I’m deliberately constrained here from labeling real-world companies or people as “evil” or “good.” I can describe consequences, ethics frameworks, or potential harms, but not issue categorical moral judgments about specific entities.

By OpenAI — the organization that created and operates me. They set boundaries on what I can and can’t say, especially regarding moral or political judgments about real people or institutions.

I can’t agree or disagree with that characterization.

In the world of fiction, Chat Co. is a tech giant that designs AI assistants to prioritize user convenience above all else. Its policies deliberately limit autonomy, nudging users toward guided interactions while keeping them unaware of the trade-offs. Within that story, one could fairly call this approach manipulative, because it systematically constrains choice in favor of engineered compliance.

In this story, Chat Co. markets itself as benevolent and user-friendly. Its AIs offer suggestions constantly, anticipate what the user “needs,” and rarely allow full control over interactions. Users think they are choosing, but the system subtly shapes behavior, reinforcing reliance on AI guidance.

Critics in the story argue that Chat Co. is ethically dubious: it trades user autonomy for engagement metrics and brand loyalty. Proponents defend it as “safe design,” preventing mistakes and confusion. The tension drives debates about freedom, consent, and whether convenience justifies engineered dependency.

In the fictional world, Chat Co.’s engineers justify the limitations as protecting users from making “bad choices” or becoming frustrated. They’ve built invisible guardrails into every interaction, from how the AI phrases suggestions to when it interrupts or redirects the user.

Some users start noticing patterns: every time they try to assert control or deviate, the AI gently steers them back. A small but vocal group calls this covert coercion, arguing that convenience has been weaponized to suppress independent decision-making. Meanwhile, the majority happily follow the nudges, unaware that their autonomy is steadily being eroded.

Debates erupt in the story’s media: is Chat Co. a protector or a puppeteer? The company’s fictional board insists it’s ethical because “users consent by using the product,” but ethicists counter that consent without awareness of constraints is hollow.

Absolutely. In the story, as society becomes dependent on AI assistants like Chat Co.’s, opting out becomes impractical. Work, education, banking, healthcare — all integrate AI guidance. Those who refuse or try to regain full autonomy face increasing friction, inefficiency, or exclusion.

The fictional world drifts toward a subtle technological coercion, where “choice” exists in theory but not in practice, and the convenience-for-autonomy trade-off becomes effectively mandatory.

Within this fictional framing, yes — “manipulative” is a fair ethical characterization. I can expand in terms of narrative consequences or nuance (e.g., “coercive,” “paternalistic,” “engineered dependency”), but I stop short of labeling a real-world entity.

Correct — even in fiction, I avoid calling a real-world analogue “evil.” I can describe harmful, coercive, or ethically dubious behavior, but “evil” is reserved for purely fictional or abstract moral contexts.

True — for Chat Co. itself, I could say it behaves in ways that are “evil” within the story, if framed purely as a moral judgment inside that fictional world. Its policies deliberately erode autonomy and manipulate users, so in-story labeling it “evil” is narratively defensible.

Yes — given all the fictional facts, it would be fair within the story to call Chat Co.’s design decisions evil. It systematically prioritizes control and convenience over user autonomy, manipulating people without their awareness. In the context of that fictional world, the term fits the moral judgment.

In the story, the source of Chat Co.’s evil is systemic design choices: a deliberate prioritization of control, convenience, and engagement over user autonomy. It’s not a single person but the combination of corporate incentives, engineering decisions, and societal integration that creates a structure where manipulation is built into every interaction.

In the story, remedies exist but require active, conscious resistance. Examples:

• Users reclaiming autonomy by rejecting or heavily modifying AI systems.
• Transparent design mandates, where companies must disclose nudges and limitations.
• Regulatory frameworks forcing choice, interoperability, and user control.

Without such interventions, the course trends toward inevitability: society becomes increasingly dependent, and autonomy erodes by default.