Instinct’s New Product Tips Spark Backlash Over AI Shopping Push

AI startup Instinct has started surfacing product recommendations to users through a new feature called Instinct Selections, but the rollout is already drawing criticism from people who say the assistant is beginning to feel more like an ad platform than a helpful tool. The reaction matters because Instinct is one of the buzziest new entrants in consumer AI, and the episode offers an early look at how users may respond when chatbots start mixing conversation with commerce.

The feature, introduced this week by founder Noah Shinn, expands Instinct beyond general AI suggestions and into curated lists for dining, travel, shopping and home goods. Shinn says the company wants to combine the model’s web-based recommendations with input from people with local expertise, but several users responded publicly that they had not asked for the suggestions and did not welcome the interruption.

What Instinct Selections does

Instinct Selections is the company’s new recommendation layer, designed to push tailored product and place suggestions to users in areas such as restaurants, travel routes and retail purchases. Shinn framed the feature as a way to add “human taste” to an AI assistant that otherwise relies on patterns learned from the broader internet.

In practical terms, Instinct says it is partnering with specialists such as chefs, travel guides, designers and architects to surface recommendations that feel more curated than a generic chatbot answer. The company has not disclosed who those partners are, how they are selected, or how much of the recommendation experience is generated by humans versus the underlying model.

Shinn described the feature as a way to let Instinct pull from handpicked lists and specialist recommendations so users can get higher-quality suggestions than they would find from a generic web search or another chatbot.

Why users are reacting negatively

For some users, the problem is not the recommendations themselves but the way they arrived. Several people said Instinct surfaced shopping ideas they had not requested, sometimes as notifications or within the assistant experience, which made the feature feel intrusive rather than useful.

The criticism reflects a broader consumer sensitivity around AI products that begin to resemble targeted advertising. Once a chatbot starts recommending luggage, sunglasses, accessories or home items based on private context, it crosses from assistance into something closer to commerce-driven profiling, even if the company says the intent is editorial curation.

That tension is especially acute for AI assistants that are still trying to define their role. Users may accept recommendations when they are directly relevant to an active request, but unsolicited prompts can create the impression that the product is trying to sell rather than help.

How the backlash showed up on social media

The objections quickly spread on X, where users posted screenshots and complaints about recommendations they said they had never requested. One venture capitalist said the assistant had devolved into something that felt like a generic retail suggestion engine, while other founders and operators said the experience produced an uncomfortable “ew” reaction.

Another user argued that the assistant should have asked before sending recommendations, while also calling for more control over which sources Instinct uses. That broader request points to an emerging expectation in AI: if a system is going to personalize content, users increasingly want visibility, choice and consent.

How Instinct says the feature is supposed to work

Instinct’s pitch is that the assistant will blend machine-generated awareness with curated human expertise. In theory, that could make recommendations sharper, more local and more context-aware than a standard chatbot response built from training data alone.

Shinn said the assistant could recommend a hidden-gem restaurant from a chef’s list, suggest trail routes from local guides or identify home decor pieces from independent designers that match a user’s style and budget. The promise is differentiation: not just answers, but recommendations that feel selected by someone who knows the category well.

The challenge is delivery. If the recommendations appear at the wrong moment, or if they are not tightly aligned with the user’s needs, the experience may feel less like concierge service and more like unsolicited promotion.

Who is behind the criticism?

The first wave of complaints came from a mix of investors, founders and operators who are active on social media and closely watch the AI market. Their objections were not only about one product launch, but also about the direction of the AI assistant category more broadly.

One investor said the suggestions felt like the assistant had suddenly become a recommendation engine for consumer products. A founder in the marketplace space said the experience felt especially uncomfortable because the assistant appeared to infer purchases from email and travel plans. Another user argued that the feature should be opt-in rather than automatic.

Those responses matter because they come from an audience that is often early to adopt and quick to test new tools. If even that group finds the recommendations awkward, consumer trust could become a serious hurdle as Instinct tries to scale.

What makes this different from normal recommendations?

Normal recommendation systems usually live in places where users expect them, such as shopping apps, streaming services or e-commerce pages. Instinct, by contrast, is a general-purpose AI assistant. That means recommendation prompts can feel more intimate, because they are tied to a broader stream of personal context and conversation.

The assistant may know about upcoming trips, inbox content or other user signals that make its suggestions more specific. But that specificity also raises the emotional stakes. When a product recommendation appears to be based on private details, users may feel watched, even if the underlying feature is designed to be helpful.

That is the core product risk: personalization can improve relevance, but it can also amplify discomfort if the timing, tone or frequency feels off.

What users appear to want instead

Based on the early complaints, users seem to want three things: permission, relevance and control. They want to be asked before recommendations are pushed. They want suggestions to clearly fit the current task. And they want a way to shape the sources or categories the assistant uses.

That feedback suggests a simple rule for AI product design: curation is welcome when it follows user intent, not when it interrupts it.

Why the timing matters for Instinct’s business

Instinct’s new feature arrives just after the company disclosed a major fundraising milestone. The startup recently completed a $1 billion Series C round that valued it at $10 billion, putting pressure on the company to show a path from hype to durable revenue.

The company has not said whether Instinct Selections will directly monetize through ads, affiliate links or another commerce model, but the feature looks well positioned for all three. Recommendation products are often a gateway to revenue because they can convert trust and intent into transactions.

That possibility makes the backlash more than a branding issue. If recommendations are the start of a monetization strategy, then alienating users on day one could make the long-term economics harder to achieve.

How big is Instinct’s transaction volume?

According to Shinn, the platform is already handling a substantial amount of commerce through the agent. In a recent podcast conversation with investor Patrick O’Shaughnessy, he said annual transactions processed through the system are approaching $1 billion, and more than half of that activity is tied to travel.

Those figures suggest that Instinct is already more than a novelty chatbot. Even so, the company has not publicly provided a user count, which leaves outside observers with limited ways to judge how broad that commerce activity really is or how concentrated it may be among a small number of heavy users.

Here is the key context around the company’s growth story and the new product push:

How does Instinct compare with bigger rivals?

Instinct is entering a crowded field where larger companies have similar ambitions but, at least for now, have been more cautious about inserting shopping-style recommendations into chatbot interactions. That restraint may be one reason some users are especially sensitive to Instinct’s approach.

Meta and OpenAI are among the better-capitalized competitors shaping consumer AI, and the fact that they have not taken the same overt recommendation path gives Instinct an opening to differentiate — but also a higher risk of being seen as overly commercial. If users believe one assistant is trying to nudge them into purchases, rival products that stay more neutral may look more trustworthy.

For a startup trying to define itself as an intelligent companion, trust is a product feature. Once that trust is compromised, even well-designed recommendations can be read as manipulation.

What comes next for Instinct?

The company now faces a familiar startup challenge: how to turn engagement into revenue without breaking the core experience that made the product attractive in the first place. If Instinct Selections becomes a useful, voluntary and clearly contextual feature, it could deepen user value and create a strong monetization path.

If it keeps arriving unprompted, though, the feature may reinforce the fear that AI assistants are just becoming new wrappers for affiliate commerce. The next version of the rollout will likely need better controls, clearer opt-in settings and more transparency about how recommendations are sourced.

TechCrunch said it had asked Instinct for comment. The company had not publicly addressed the backlash in detail at the time of reporting.

Key dates and developments

Instinct’s recommendation push did not appear in a vacuum. It came shortly after a major financing announcement and at a moment when the company is trying to prove it can translate attention into sustainable business value.

• Tuesday: Founder Noah Shinn publicly introduced Instinct Selections.
• This week: Users began reporting unsolicited recommendations.
• Recent weeks: Instinct disclosed a $1 billion Series C.
• Recent podcast interview: Shinn said the platform is nearing $1 billion in annual transactions.

Why this story matters for the AI market

Instinct’s backlash is a reminder that the next battleground in consumer AI may not be model quality alone. It may be product taste — specifically, how and when AI systems introduce commerce into the conversation.

As assistants become more capable and more personal, they will also become more commercially tempting. The companies that win may be the ones that can prove recommendations are genuinely useful without making users feel like they are being sold to every time they ask for help.

For now, Instinct has a clear lesson from its own users: curation is only an upgrade if it feels invited.