Every week, another solopreneur launches an app built with Claude Code, Cursor, Replit, or Lovable. A Boston University senior built the pilot of her vintage clothing marketplace in five days and spent under $2,000 to get it running. A new mom used Lovable to build a baby nutrition app, often working in 30-minute bursts before her baby needed feeding. Two cofounders vibe-coded an AI content tool in 14 days, launched it to 250 paying customers on day one, and reached $50,000 in monthly recurring revenue within six weeks.
If you run a software agency, headlines like these can feel like a countdown. Why would anyone hire a development team when a prompt and a free weekend seem to do the job? But I don’t think vibe coding is killing software agencies. I think it is killing an outdated agency model that depended on software being slow, expensive, and inaccessible.
I’m the founder of two tech agencies, and I've had a front-row seat to this shift. Here is what actually changed, what didn’t, and why I believe the old agency model had to die for our industry to grow.
There’s no point denying it
AI has accelerated and democratized software development. Businesses no longer need to wait months just to see a basic MVP, and the data shows they’re acting on it. McKinsey’s State of AI 2026 survey found that 32% of respondents say their organizations decided against buying at least one software product or feature because they could build it in-house with agentic coding tools. Veracode reports that in organizations using AI coding tools, AI now writes roughly half of all committed code.
Client expectations have moved accordingly. They want faster delivery, smaller teams, clearer ROI, and a lower total cost of ownership. Many prospects now show up to the first call with a working prototype they built themselves. Asking a client to wait four months and fund a team of six before seeing a single clickable screen now sounds like selling fax machines. That was the old engagement model: long upfront specs, big teams, billable hours as the main unit of value, and a first demo somewhere in the distant future.
Custom software is moving downmarket
Before AI, many small and midsize companies wanted custom software but couldn’t justify the investment. We would often tell them honestly: “Use off-the-shelf SaaS. Custom software will not pay off for you yet.” The math simply didn’t work for a 30-person company when a monthly subscription covered 70% of their needs.
That is changing fast. With AI-assisted development, custom CRMs, internal management systems, workflow tools, and customer portals can be built with AI faster and at a far more realistic cost. The market for custom software is expanding downward, from enterprises to SMBs. For agencies willing to adapt, that’s less a threat than an opportunity to work with clients who were previously priced out.
Where vibe-coded apps hit the wall
Yes, more people can build apps on their own. That is a good thing, and I mean it. But look closely at the success stories. The college founder mentioned she had some coding experience before Claude Code sped her up. The mom behind the nutrition app said the hardest part was building the internal infrastructure, and she credits her husband, a machine learning engineer, with helping. The content tool’s CTO taught himself to code in college and later worked as a data scientist at Deloitte. These aren’t arguments against vibe coding. They’re a reminder that the stories we celebrate often have an engineer somewhere in the frame.
The apps that don’t make headlines tell a different story. Vibe-coded products often hit a wall when they need to scale, stay secure, support real users, integrate with business systems, or evolve over time. When Escape analyzed more than 5,600 publicly available vibe-coded apps, it found over 2,000 vulnerabilities, 400+ exposed secrets, and 175 instances of leaked personal data, including medical records and IBANs.
Veracode’s 2026 testing showed that about 44% of AI code generation tasks introduced a risky vulnerability, with an average security pass rate of 56%, barely up from 55% in its first report. Developers feel it too: in Stack Overflow's developer survey, 66% named AI solutions that are almost right, but not quite, as their biggest frustration.
I’ve written before about how this plays out in practice: founders build, devs fix. It’s also why we launched a dedicated vibe code cleanup service, because more and more founders come to us with apps that shine in a demo and crack under real traffic. A prototype can be built with prompts. A reliable product still needs product thinking, architecture, testing, security, maintainability, and most importantly, engineering discipline.
What AI-native development actually looks like
At Redwerk, we see AI as an accelerator, not a replacement for engineering judgment. Two decades of traditional software development help us use AI in a sustainable way, with security, scalability, maintainability, and market conditions in mind. That’s the foundation of our AI-native custom software development approach.
In practice, AI takes on boilerplate, test drafts, documentation, and first-pass refactoring. Engineers make the architecture calls, review everything that touches authentication, payments, or personal data, and own the integrations with the systems a business actually runs on. Discovery gets shorter, but it doesn’t get skipped: a clickable prototype in days lets a client validate the idea before paying for a full build. Teams get smaller and more senior, because reviewing AI output well takes more experience, not less.
In the new agency model, clients pay for outcomes: the right product, built faster and with fewer mistakes. If AI cuts coding time in half and an agency keeps billing the same hours, that’s a business model with an expiration date.
We’ve heard this promise before
Low-code tools once promised to replace developers. Gartner predicted that by 2026, developers outside formal IT departments would make up at least 80% of the user base for low-code tools. Low-code found its niche, and developers didn’t disappear. Now natural language coding tools are making the same promise at a much larger scale, and they’re far more convincing because they genuinely work better.
But the human problem has not changed. Founders still rush into building without clear requirements, skip business analysis, underestimate security, and confuse a working demo with a real product. I saw all four mistakes twenty years ago, and I see them every week today, just delivered faster. AI changes the tools. It does not remove the need for judgment.
So, should agencies be worried?
Some should. Agencies that sold hours, headcount, and waiting time are watching their value proposition evaporate. Agencies that sell judgment, on the other hand, have a growing market to serve. Vibe coding didn’t take clients away from us. It brought us businesses that couldn’t afford custom software before, and founders who already proved their idea works and now need it to survive real users.
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