I was talking with a friend about the overlaps I see between dating apps and job platforms. We’d just heard a pitch from a founder building AI-powered skill assessments for hiring. Good solution to a real problem, but I felt a bit deflated watching another startup cater to the hirers’ triaging workflows.

I think there’s a lot being left on the table regarding the emotional space of people seeking. The problems around how to represent yourself/how to signal your appeal or X-factor feel more profound to me than problems about managing huge applicant pools. And there’s something civically motivating about how the same problem shows up on both sides of seeking/accepting dynamics: How can I enable the right people to find me? and How can I make myself known to the right people?

You sometimes see job descriptions that list out all their qualifiers—8 years of experience and such—and then say something like “…if you don’t meet any of this, still reach out anyway.” They say that because they know criteria only help up to a point. We lean on metrics and static signifiers in lieu of more dynamic ways to convey value through matching systems.

Metrics and hard requirements are proxies for something harder to articulate. You might want to date tall people because you want the sense of capability you associate with height. You might want an artist or a poet, though the underlying qualities that draw you to them aren’t exclusive to those people. By filtering for tall poets or for job applicants who’ve already done the exact thing you’re hiring for, you miss richer ways people could meet your needs. Traditional systems force a shape-fitting paradigm¹ (reducing complex qualities to flat attributes), which pressures people to self-present in ways that don’t guarantee actual fit.

After qualifications and criteria are cleared, any matching decision ultimately comes down to vibes… the fuzzier, harder-to-articulate signals that the criteria only sketched around.² The hiring manager or the dater needs someone who fills a particular gap and creates a particular feeling. Current matching systems don’t really touch this emotional space, but it’s where real compatibility lives and struggles to express itself.

Moving beyond shape-fitting

AI matching using sophisticated vector embeddings holds some promise, but it risks being a more complex form of shape-fitting; you’d plug in keywords, and the system finds things closer to those keywords. A more novel direction might bypass the keyword step entirely: matching signal to signal, letting the fuzzy things find each other directly without forcing them through structured descriptions first. A better north star might be curiosity-driven connection rather than just “better matching” (finding the shape faster). Instead of assuming the seeker knows exactly what they want, a more curiosity-driven system would allow for emergent fit, acknowledging that:

• We tend to think of shapes first, then look for people to match them. Shapes are lossy at best and reductive at worst.
• The “perfect match” can change your understanding of what you needed in the first place. Discovery can shift criteria.
• Moving toward signal-based matching also shifts incentives away from pressuring people to fit themselves into static shapes.

What could power this? I keep thinking about ambient signals, something like digital pheromones that allow for serendipitous stumbles into people with compatible vibes. Or matching that values the energy of someone’s interests over the content—because connection often stems from sharing one’s world, not just overlapping taste.

The Browser Company on “Emotional Design”:

Humor us for a moment and picture your favorite neighborhood restaurant... handmade textile seat cushions, a caramel wood grain throughout, and colorful ornaments dangling from the ceilings. Can you picture yours? Do you feel the warmth and spirit of the place?

A Silicon Valley optimizer might say, “Well, they don’t brew their coffee at exactly 200 degrees. And the seats look a little ratty. And the ceiling ornaments don’t serve any function.”

But we think that’s exactly the point. That these little, hand-crafted touches give our environment its humanity and spirit. In their absence, we’re left with something universal but utterly sterile — a space that may “perfectly” serve our functional needs, but leave our emotional needs in the lurch.

[…] When our software optimizes for numbers alone — no matter the number — it appears doomed to lack a certain spirit, and a certain humanity.

[…] We wanted to optimize for feelings.

It’s hard to justify “delight” in a spreadsheet. Most commercial design processes prioritize what can be measured (clicks, conversion, time-on-site) because those numbers can be optimized; there’s always a clear next move toward a ‘solution.’ But as Nick Foster notes here, focusing purely on the solution can mean ignoring the elegance of how you got there. Benek Lisefski lends more to this in saying that relying on data alone has a way of flattening things out:

… relying on data alone ignores that some goals are difficult to measure... [The commercial design process] creates more generic-looking interfaces that may perform well in numbers but fall short of appealing to our senses.

I see a similar tension in movies. Martin Scorsese’s critique of Marvel is essentially about the same trade-off between a “perfect product” and something with genuine risk:

…Cinema was about revelation — aesthetic, emotional and spiritual revelation.... What’s not there is revelation, mystery or genuine emotional danger. Nothing is at risk... The pictures are made to satisfy a specific set of demands... market-researched, audience-tested, vetted, modified, revetted and remodified until they’re ready for consumption.

Massive budgets don’t guarantee resonance. Braden Kowitz at Google Ventures mentions a time they chose not to optimize a button purely for attention because they wanted to prioritize trust and quality instead. As Lisefski puts it: “While you’re chasing a 2% increase in conversion rate you may be suffering a 10% decrease in brand trustworthiness.”

I love how Wikipedia’s network of pages is so dense that you can “hyperlink-hop” to nearly any page from another. There must be a word for the specific pleasure of having 20+ tabs open while going down a rabbit hole.

Spending so much time on Wikipedia as a kid made me more curious about how things connect. WIRED’s deep dive calls it the “last best place on the internet”:

Like Instagram, Twitter, and Facebook, it broadcasts user-generated content. Unlike them, it makes its product de-personified, collaborative, and for the general good... It is one of the few remaining places that retains the faintly utopian glow of the early World Wide Web. A free encyclopedia encompassing the whole of human knowledge, written almost entirely by unpaid volunteers: Can you believe that was the one that worked?

It’s one of the few places left where you can find in-depth coverage of almost any topic without ads, paywalls, or fluff.

Fan-made “Wikis” (usually on Fandom.com) lack Wikipedia’s strict objectivity, but they’re a fun scaffolding for fans to document their obsessions in obsessive detail. They continue the same spirit of “specialized self-indulgence” that Wikipedia enables:

[…] Wikipedia is built on the personal interests and idiosyncrasies of its contributors... Editors' passions can drive the site deep into inconsequential territory—exhaustive detailing of dozens of different kinds of embroidery software... a brief but moving biographical sketch of Khanzir, the only pig in Afghanistan.

This e-flux essay makes a case for looking at social media as more than just a place to post photos:

Social networking is much more than just a dominant discourse. We need to go beyond text and images and include its software, interfaces, and networks that depend on a technical infrastructure consisting of offices and their consultants and cleaners, cables and data centers, working in close concert with the movements and habits of the connected billions. (...)

We treat the internet as something ethereal, but “the cloud” is mostly just rows of humming server racks in giant warehouses. Because we don’t see the physical hardware, it’s easy to miss how much of our digital life is manufactured.

… Before we enter the social media sphere, everyone first fills out a profile and choses a username and password in order to create an account. Minutes later, you’re part of the game and you start sharing, creating, playing, as if it has always been like that [...] The platforms present themselves as self-evident. They just are—facilitating our feature-rich lives.

Before movies matured into a standard format, they were all “experimental,” including plot structures. We now take for granted conventions like following a protagonist through a rising action and climax, but things didn’t have to turn out that way. Social media is the same. The focus on “engagement metrics” and “personalization” isn’t a natural law; it’s a design choice optimized for business incentives.

Treating social media as ideology means observing how it binds together media, culture, and identity into an ever-growing cultural performance (and related “cultural studies”) of gender, lifestyle, fashion, brands, celebrity, and news from radio, television, magazines, and the web—all of this imbricated with the entrepreneurial values of venture capital and start-up culture, with their underside of declining livelihoods and growing inequality.

Software gives us a simplified, imaginary relationship to the hardware it runs on. We don’t interact with transistors; we interact with “desktops” and “recycling bins.” In the same way, social platforms produce a specific kind of “user.”

Software “fulfills almost every formal definition of ideology we have, from ideology as false consciousness to Louis Althusser’s definition of ideology as a ‘representation’ of the imaginary relation of individuals to their real conditions of existence.’”
Software, or perhaps more precisely operating systems, offer us an imaginary relationship to our hardware: they do not represent transistors but rather desktops and recycling bins. Software produces users. Without operating system (OS) there would be no access to hardware; without OS no actions, no practices, and thus no user. Each OS, through its advertisements, interpellates a “user”: calls it and offers it a name or image with which to identify.