A friend of mine spent last weekend building a SaaS tool. Using AI code assistants and a pre-packaged boilerplate, he scaffolded a database, integrated Stripe, designed a gorgeous interface, and deployed the entire app in under 48 hours. Ten years ago, this would have taken a team of three developers three months and thousands of dollars.

On Monday morning, he clicked “publish.” Then, absolute silence.

He didn’t get silence because his product was bad. He got silence because the pipeline to reach his customers is completely blocked. We have entered a weird era of software: building is virtually free, but distribution has become an expensive luxury. When it is easy for you to build, it is easy for everyone else to build too, resulting in an infinite supply of software screaming for a finite amount of human attention.

The GTM Gridlock is Real

If you try to use the standard startup marketing playbook today, you run into a brick wall of algorithms.

Take cold email outreach. In early 2024, Google and Yahoo implemented strict new email protections, setting a hard spam complaint ceiling of 0.3%. If you cross that threshold, your domain is instantly blacklisted. Because AI has made it easy to generate thousands of “highly personalized” cold sequences, inboxes are flooded. Buyers have built massive psychological walls, and their AI-powered spam filters do the rest, auto-categorizing or replying to pitches before a human ever sees them.

Inbound marketing is facing a similar crisis. Gartner recently predicted that organic search engine traffic will drop by 25% by 2026, driven by the rise of conversational AI search engines like Perplexity, ChatGPT, and Gemini. If you write a blog post or a newsletter to reach your ICP, they probably won’t read it. Instead, their AI reader tools or custom LLM feeds scrape the text, strip out your stories, voice, and nuance, and deliver a dry, bulleted summary personalized to their screen.

Even if you buy paid ads on Google or LinkedIn, you are entering a bidding war against thousands of other micro-SaaS startups targeting the exact same keywords and job titles. With LinkedIn CPCs regularly hitting $15 to $20 for decision-makers, the math quickly breaks. Your Customer Acquisition Cost (CAC) eclipses the Lifetime Value (LTV) of the customer.

We are moving away from B2B (Business-to-Business) marketing. We are now operating in an A2A (Agent-to-Agent) economy, where your message is filtered by one machine and summarized by another.

Why Companies Still Buy Software

If any junior developer can spin up a custom tool with AI, it begs the question: Why does anyone still buy software? Why wouldn’t a company just build its own custom internal tools instead of paying thousands of dollars for a subscription?

The answer comes down to the difference between software creation and software ownership.

Building an app is a one-time event; maintaining it is a lifelong tax. If a logistics company builds its own custom project tracker, it now owns the responsibility of keeping it secure, handling backups, updating dependencies when React changes, and fixing bugs. The moment Chrome rolls out a new security update and breaks their custom login system, their core engineers have to stop working on customer-facing features to fix an internal tool.

It is an issue of opportunity cost. A business should focus its engineering power on its core value—the thing that makes them profitable. Standard context tools, like ITSM trackers or payroll software, are rented because the customer is paying to outsource the headache of maintenance. However, simple bespoke tasks, like formatting a specific CSV file or integrating a local spreadsheet with a database, are now built internally using scripts rather than being outsourced to niche micro-SaaS vendors. Niche utility SaaS is getting squeezed out.

The Invariant Timeline

Technology advances, but human systems and relationships do not scale at the speed of microchips.

Think about modern agriculture. We use GPS-guided tractors, drone monitoring, and automated soil sensors to manage crops. We replaced manual labor with machines and automated systems. Yet, despite all the high-tech sensors, a tomato seed still takes its own biological time to sprout and grow. You can monitor a plant with a 4K camera, but you cannot code a tomato to ripen in five minutes.

Software is the same. AI can generate the code in five seconds and monitor the system in real-time, but human trust, organizational adoption, and change management still take their natural biological time. You cannot accelerate the “sprouting time” of a business relationship, no matter how fast your AI generates the product.

Surviving the A2A Economy

If you want to sell software when the digital pipeline is clogged, you have to operate in the gaps where AI gatekeepers cannot easily intervene.

If a buyer’s AI agent is searching the web for a solution, your software needs to be readable by the machine. This means focusing on clean API documentation, open-source integrations, and structured data that LLMs can parse and recommend. You are marketing to the algorithm, not just the human.

At the same time, you have to go bottom-up. Build a free, hyper-focused utility tool that solves a single employee’s daily bottleneck. Once they adopt it, it spreads horizontally through the team until management is forced to pay for the enterprise license.

Finally, bypass the screen entirely. When digital channels are saturated with automated noise, offline relationships become a premium asset. Real-world handshakes, localized dinners, and direct phone calls bypass the AI filters. We are returning to a high-touch, relationship-driven sales model—one that is slow, human, and impossible for an AI agent to replicate.

The game hasn’t changed; the abstraction has just scaled up. We aren’t going backward.

We don’t go back to where we started; we loop back over the same themes at a higher level of abstraction.