For a long time, there was a clear, predictable path from building a useful product to finding an audience. You identified a real need, built a solution, optimized a website around how people searched for it, and waited for that organic demand to trickle in. If the product delivered, early users left reviews, recommended it to colleagues, shared it on social platforms, linked to it, or simply stuck around long enough for search rankings and reputation to compound.
Once those wheels started turning, you could pour fuel on the fire through retargeting, paid acquisition, email campaigns, audience building, and conversion rate optimization. But the critical prerequisite was already met: the first users had arrived, giving you a baseline momentum to accelerate. Search intent, social proof, rankings, word of mouth, and retention formed a self-sustaining growth loop around a product people genuinely wanted.
That path still exists in theory, but the starting engine has become vastly harder to turn over. Countless products now stall out long before that old growth machinery ever kicks in—even when the underlying idea is sharp, the execution is solid, and the market has already proven that demand exists.
The old discovery machinery is getting clogged
The traditional internet ran on intent. Someone encountered a problem, typed a query into Google, and was greeted by a handpicked collection of potential solutions. A company that understood those search queries could build targeted pages, earn backlinks, climb the rankings, and secure a reliable stream of visibility whenever that need resurfaced.
Today, a single software category can contain hundreds of products targeting virtually identical search terms. AI-assisted development has dramatically expanded who can build software—and exploded how much software a single builder can output. Many of these modern entries come wrapped in sleek websites, polished product shots, smooth onboarding flows, and enough baseline utility to pass a quick evaluation with flying colors.
Yet the supply of prime digital real estate hasn't expanded to match. Google still offers only a handful of above-the-fold search results that capture real attention; app stores still feature a strictly limited shelf of curated real estate; and an AI assistant can only recommend two or three options before its answer becomes overwhelming. The supply of software can scale indefinitely, but the choke points where humans actually discover it remain stubbornly narrow.
Search is changing at the same time
This discovery dilemma is further complicated by a fundamental shift in how people search. Users are increasingly turning to AI assistants to research tools, compare alternatives, and recommend solutions. This places a brand-new translation layer between the user and the product—one governed by an entirely different set of rules around authority, citation, explicit context, structured data, and machine readability.
(I have written separately about this shift in AI search and how websites are transforming into structured inputs for recommendation engines—The web is becoming operable by AI).
The core issue for builders is that the old search paradigm is fraying before the new playbook has fully settled. Developers find themselves caught in the middle: trying to decipher the dark arts of AI recommendation engines while simultaneously fighting for survival across traditional search, app stores, social algorithms, and online communities.
When no single channel offers a reliable playbook, a well-crafted product can do almost everything right and still remain completely invisible at the exact moment a prospect is deciding what to buy.
Organic social is crowded too
When search channels dry up, the obvious pivot is to go directly where attention lives: X, LinkedIn, Instagram, TikTok, YouTube, Reddit, newsletters, or niche Discord servers. Founders publish build-in-public updates, stream product demos, document their progress, and attempt to earn enough trust to persuade casual observers to convert into users.
This strategy is logical on paper. People still rely heavily on social proof, particularly when evaluating a young application without a track record. The catch? Everyone else had the exact same idea.
Developers, founders, consultants, agency owners, and hobbyists are all actively building personal brands, distributing newsletters, and publishing short-form video. Add generative AI into the mix, and acceptable content can now be produced at zero marginal cost.
Automated publishing and bot networks further muddy the waters. Synthetic replies, mass-produced posts, and templated videos make it nearly impossible to gauge genuine market pull. A new application desperately needs social proof to attract early adopters, yet those same adopters demand active communities, glowing reviews, and external validation before they are willing to invest their time. The product needs users to generate trust, but it needs trust to attract the users.
Assume the product is good enough
Software fails for two overwhelming reasons that we should intentionally set aside for this argument: poor execution and lack of product-market fit. A massive amount of new software dies simply because it is clunky, buggy, or incomplete. Another vast category fails because it solves a problem nobody cares about enough to change their existing behavior.
For the sake of this discussion, let’s assume the product actually works well, offers a great user experience, and operates in a category where established competitors have already proven people will spend time and money.
By removing bad execution and non-existent demand from the equation, we isolate the real modern bottleneck: even a genuinely useful product must figure out how to squeeze into a digital life that is already at full capacity.
What a normal digital life now contains
I don't have to look far to see this reality in action; my own devices tell the story. My phone hosts anywhere between one and two hundred apps, many of which haven't been opened in years. I keep them around "just in case," only to find that when I finally launch one, it requires a mandatory update before I can even use it.
My desktop is a graveyard of organized folders, bloated download directories, unread PDFs, and saved links I swore I’d return to six months ago. My bank statement features a quiet steady stream of recurring SaaS subscriptions that require quarterly auditing—inevitably revealing a few forgotten tools I’ve been paying for without using.
My inbox is a constant triage zone: deliberate newsletter subscriptions, transactional receipts, product updates, cold outreach, security alerts, and the occasional sophisticated phishing email that slips past the filters. X serves up more fascinating thinkers than I could ever keep up with, while creators I used to love quietly fade from my feed the moment my clicking habits subtly shift. YouTube presents an endless buffet of subscribed channels offering far more video content than a single lifetime allows.
Facebook and Instagram capture different social circles, complete with their own implicit posting norms and lingering usage habits. LinkedIn commands another corner, serving as a repository for professional updates and industry commentary. Layer on top of that private chat groups, Slack workspaces, AI prompts, cloud storage drives, work suites, personal project boards, calendars, task managers, and the relentless ping of notifications tied to every single one of them.
This isn't an extreme case—it is simply what a standard modern digital life looks like. When you view it all at once, the sheer volume of cognitive input required to manage it is staggering. Every tool or platform is valuable in isolation, but together they form a perpetual queue of uncompleted tasks demanding to be read, updated, answered, reviewed, or organized.
The user is already trying to remove things
Most software creators still market to users as if they were pitching to a clean slate. Download this app, start this free trial, enable notifications, join our Discord, create an account, install this extension, subscribe to this feed. Each request sounds harmless when evaluated on its own.
The problem is that the person receiving that pitch is often operating in the exact opposite mindset. They are actively purging apps they haven't touched, canceling unused subscriptions, turning off push notifications, hitting "unsubscribe," unfollowing inactive accounts, and desperately trying to shrink their surface area of digital obligations.
Your shiny new product isn't arriving in a void—it is knocking on the door at the precise moment the occupant is aggressively clearing out the furniture.
This is why viewing today's market purely through the lens of a "replacement economy" misses a crucial dynamic. Replacement implies a user who is actively searching for a swap. In reality, modern users are often looking for subtraction. A new product must not only survive initial discovery and earn trust—it must prove that it deserves a permanent lease in a digital life the user is actively trying to downsize.
Your competitor may already be installed
If I launch a brand-new task management app, my obvious competitors are Asana, Todoist, and Things. But my real competitors are the built-in Apple Calendar the user already understands, the messy Notes app they've relied on for five years, the unread Slack message they are deliberately leaving unread as a mental reminder, and the yellow sticky note sitting next to their keyboard. My true competition is the path of least resistance—the messy, "good enough" habits already entrenched in their routine.
If I build a specialized AI assistant, I am not just competing with niche tools; I am competing against established habits already directed at ChatGPT, Claude, or Gemini. If I start a new private community, I am competing for leisure time currently spent on YouTube, Reddit, online gaming, or simply stepping away from screens entirely. If I launch a newsletter, I am asking for space in an inbox where the owner is actively trying to reach inbox zero.
A successful product can no longer just prove that it works. It must either displace a tool that currently occupies that slot or deliver so much value that the user willingly accepts the overhead of adding another commitment to their life.
Building became cheap before human attention expanded
Generative AI has introduced a massive structural imbalance to the tech industry. The barrier to entry for building software has collapsed, empowering solo creators to construct and test complex systems that once required an entire engineering squad. The exact same shift has played out in content creation, allowing a single individual to produce text, graphics, and video at a volume that used to require a media studio.
Yet human attention remains strictly finite. The day still has twenty-four hours, the smartphone screen remains roughly six inches tall, the first page of search results still only holds a few prime positions, and an AI recommendation becomes useless if it hands you a list of fifty options. Beyond a certain threshold, every extra subscription, login credential, notification dot, or content feed stops feeling like an exciting feature and starts feeling like an unpaid chore.
This leaves modern builders facing a fundamental strategic question once the code is written: How do you earn a permanent position inside a digital environment that is already overflowing?
Distribution increasingly starts with subtraction
This shift changes how products must be positioned from day one. It is no longer sufficient to highlight what your software adds. The far more compelling proposition is explaining what your software allows the user to delete. Can your product eliminate a duplicate tool, cancel a subscription, automate a repetitive chore, flatten an annoying interface, or remove an entire tedious step from a workflow?
The most resilient products of the coming decade may well be those designed to fit effortlessly into existing behaviors with zero friction—taking over a routine task so smoothly that another piece of digital bloat simply fades away.
This is precisely why there is growing interest in software that operates natively inside existing ecosystems, such as AI assistants or established productivity suites. Asking a user to navigate to a new URL, register a new account, configure new settings, and build a new daily habit carries an extraordinarily high friction cost. Bringing an intelligent capability directly into an environment where the user already lives changes the math completely.
We are generating more software, more media, and more digital choices than the human brain was built to process—all while the people on the receiving end are quietly looking for the exit. Moving forward, the ultimate test for builders will be less about whether they have the capability to create something useful, and more about whether a cluttered world can be convinced to make room for it.
