Summary: Jason Parham argues a blunt point: AI-powered dating is all hype, and the real shift is toward meeting people in person—what he calls IRL cruising. This piece examines why that claim lands, where Big Dating went wrong, what the data and culture say, and how singles and platforms can design for real-life connection instead of sacrificing it to algorithms. Consider this a practical playbook for getting people offline and flirting again—because flirtation is a human skill machines can’t mimic.
Why the AI pivot felt inevitable
Big Dating built an industry on scale, metrics, and monetization. When engagement eroded, investors and executives asked a predictable question: how can we squeeze more value from the same product? The answer from boardrooms and R&D labs was AI. AI promised personalization, faster matches, and reduced churn. It sounded like absolution: fix the product, fix the brand, fix the growth curve.
AI features—coaching tools, auto-summaries, wingman copilots—made sense as band-aids. They addressed friction and improved short-term metrics. They promised better conversations and less fatigue. Yet promising less friction is not the same as restoring desire. The industry put tools in front of people who were already worn out. That mismatch matters.
“AI-powered dating is all hype.” Say it with me
Repeat it: AI-powered dating is all hype. Why repeat? Because saying it forces a test: does the technology replace what people value, or does it merely reshuffle surface features? Flirtation, chemistry, awkwardness, timing—those are the variables no LLM can reliably produce. You can automate opening lines, summarize a chat, or suggest a date idea. You cannot manufacture the thrill of discovery when two people actually collide in the real world.
Ask yourself: when was the last time a generated message gave you the same rush as a real person leaning into banter at a bar? If you struggle to answer, that’s not nostalgia. It’s data. Machines can assist, but they cannot be the source of the spark.
Flirting remains a human art
Flirting is intentional, playful, and often messy. It operates on micro-signals—eye contact, timing, tone, a small joke that lands. Those signals create shared risk. That shared risk is what builds trust fast. AI can suggest a line, but it cannot read the subtle micro-expression that transforms a line into chemistry.
To borrow a phrasing: when people intentionally try to find common ground through teasing and testing, they expose preferences and limits. That exposure is a form of information exchange no algorithm can fully reproduce. Saying “No” in a flirt—rejecting a move, setting a boundary—can be the clearest signal of intent. Machines do not navigate the ethical weight of that “No.”
Big Dating’s pivot: redemption or PR?
Big Dating’s AI push looked like two things at once: product evolution and reputation repair. Years of gamified matching, dubious growth hacks, and low-quality experiences created a moral deficit. An AI narrative offered cover: we’re smarter now, we’ve learned, and our tools will make dating sincere.
But sincerity isn’t a toggle. It can’t be deployed with a feature flag. When companies roll out AI as a fix, they risk signaling they think the problem was surface-level. That breeds skepticism. Users see new features and ask, “Will this bring people together, or will it make them more efficient at avoiding real encounters?” Open question: which outcome do you want to back with investment and product design?
Countertrend: people want IRL cruising
In 2025, a countertrend accelerated. Young people—tired of endless swipes and performative chat—sought alternatives. They asked for physical spaces, curated events, and social architectures that reduced the cost of meeting. The market answered: meet-cute pop-ups, bar nights tagged on Instagram, board-game dating, and curated dinner parties. These work because they change the incentives. They reward presence, not profile maintenance.
When Laurie Cooper’s “Sit at the Bar September” took off, it was a reminder: changing behavior requires a visible nudge and a social script. Eventbrite numbers and attendance spikes prove it: people will show up when the format lowers risk and increases plausible deniability. That’s not coincidence; it’s social engineering done honestly.
Numbers that matter
Metrics from 2025 paint a clear picture. Apptopia reports a continuing dip in engagement, while niche IRL events show rising attendance. Friending events grew by 35 percent; board-game dating attendance rose by 55 percent. The AI companion and virtual-relationship market exploded, too—record growth and anomalies like AI-based infidelity and divorces. These are not unrelated trends. They reveal a bifurcation: people either retreat into simulated intimacy or they seek messy, human contact.
This split should guide product strategy. Ask: will you design for retreat or for real connection? Which customer behavior will you reward with product features and marketing spend?
What works in person: concrete rules for IRL flirting
Flirting in real life follows practical rules. These aren’t platitudes; they are testable behaviors you can train.
• Make entry points explicit. Create a reason to approach: a game, a comment about the setting, a shared task. People need permission to start.
• Build scripts that permit failure. If you create events where a failed line is normal and recoverable, people will experiment more. That’s where chemistry is found.
• Reward small commitments. A five-minute conversation in person is low friction, but it often leads to longer interactions. Design experiences that require small, visible commitments—standing in line together, sharing a plate, joining a group game.
• Normalize boundary-setting. Teach people how to use “No” constructively. Mirroring the other person’s words—repeat a phrase back—helps check intent without escalation. Ask calibrated questions: “What would make this night worth staying?” Then listen. Then pause. That pause creates space for honest replies.
Designing platforms that nudge people offline
If you run a dating product, the design question is straightforward: what metrics will you optimize for? Time in app? Matches? Or time spent meeting in person? Choose the last and your product roadmap changes overnight.
Practical features to consider:
• Event-first onboarding: make the first step a local meetup ticket, not a chat. People commit more when cash or scarcity is present.
• Mutual-connection pairing: match via friends and contexts, not just swipes. Cerca-style models reduce anonymity and increase accountability.
• Curated small groups: design gatherings for six to eight people. Randomness becomes manageable and interaction more likely.
• Accountability nudges: prompt users to schedule a real-life check-in within seven days of a match. Ask open-ended questions like “What would make a first meet feel safe for you?” Mirror answers in your prompts to show listening.
For singles: what to try next
If you’ve been burned by apps or bored by features that promise magic, try this short experiment. Say “No” to another swipe night. Say “Yes” to an IRL event. Commit to one small action: sit at a neighborhood bar for an hour, join a board-game meetup, buy a ticket to a curated dinner. Track what happens. Did you leave with a connection, even a small one?
Try it and tell someone about it. Commitment and consistency work psychologically: telling another person you’ll show up increases the odds you will. Then ask: what changed about the quality of the interaction? That feedback loop is how we learn better social design.
For platforms: pick a side and measure differently
If you lead a dating product, a simple test will reveal commitment. Run an experiment that prioritizes IRL meetups over chat metrics. Offer credits for attending events. Measure retention based on offline attendance and repeat in-person meetings, not app dwell time. Use social proof in marketing: show real attendees, not staged screenshots.
Authority matters here: if your product can credibly say it moved X number of people into real dates, you gain trust. Use that claim; display it where users sign up. That’s reciprocity—give people a clear path off the screen and they’ll repay with presence.
What this means for society and policy
The shift back toward IRL contact has public implications. Urban design, nightlife regulation, and public transport influence how easily people meet. Policy that supports safe, accessible public spaces is not moralizing; it’s infrastructure for connection. If society wants lower loneliness and stronger social capital, it must prioritize places where people can meet without a commercial intermediary every step of the way.
Companies will continue to push AI because it raises margins. But civil society and local business can respond by investing in spaces and programs that make meeting cheap and low-risk. Ask local leaders: what do you want your city to be known for—efficient transactions or a place where people actually meet?
Final prescription: build tools that send people into the world
AI has a role: it can reduce friction, suggest venues, and help users prepare. But it should not be the destination. Successful products will be those that use machine learning to increase the odds of successful in-person contact, not to replace it.
If you are designing product or choosing where to spend your social energy, consider this calibrated question: would you rather optimize for time on a screen or for the next moment that changes a life? Pause. Think it through. Then act. Say “No” to endless swipes. Say “Yes” to a seat at the bar, a game night, or a dinner with strangers who could become friends.
#IRLCruising #BigDating #ModernFlirting #RealConnections #DatingDesign #MeetInPerson #SocialNudges
Featured Image courtesy of Unsplash and Mehrpouya H (FJBISdttbSE)
