When Software Becomes Cheap: Industry Implications (Topic 2) in Module 1 – AI-at-Work (BG)

When Software Becomes Cheap: Industry Implications

The Economics of Custom Software — Before AI

Building custom software has historically been expensive and slow. A modest web application — a few screens, a database, user authentication — might cost $50,000–$200,000 to build professionally and 3–6 months to deliver. This meant custom software was only economically viable for large organizations or well-funded startups.

The practical consequence: most small businesses used off-the-shelf SaaS tools that were 80% of what they needed, because custom was unaffordable.

The Post-Vibe-Coding Shift

With AI coding tools, that same modest application can be built in days by a non-specialist at minimal cost. This has several cascading economic effects:

1. Cheaper internal tools: Organizations can build their own internal tools instead of purchasing SaaS subscriptions. A custom tool that does exactly what the team needs rather than a $500/month SaaS that does 80% of it.

2. One-person software businesses: The barrier to building and selling a niche software product now approaches zero. Solo founders can build and ship products that would have required a team of 5+.

3. The 'SaaS squeeze': Generic SaaS products that relied on the high cost of custom software as a moat are being disrupted. If anyone can build custom, why pay for generic?

4. Non-technical innovation: Domain experts (lawyers, nurses, teachers, tradespeople) can now build software for their specific domain without needing to hire or partner with engineers.

What This Doesn't Change

  • Complex, large-scale systems still require engineering expertise
  • Security, reliability, and compliance for enterprise software remain engineering problems
  • User experience research and product design remain distinctly human skills
  • Software businesses still require distribution, marketing, and customer acquisition
Sign in to join the discussion.
Recent posts
No posts yet.

When Software Becomes Cheap: Industry Implications

The Economics of Custom Software — Before AI

Building custom software has historically been expensive and slow. A modest web application — a few screens, a database, user authentication — might cost $50,000–$200,000 to build professionally and 3–6 months to deliver. This meant custom software was only economically viable for large organizations or well-funded startups.

The practical consequence: most small businesses used off-the-shelf SaaS tools that were 80% of what they needed, because custom was unaffordable.

The Post-Vibe-Coding Shift

With AI coding tools, that same modest application can be built in days by a non-specialist at minimal cost. This has several cascading economic effects:

1. Cheaper internal tools: Organizations can build their own internal tools instead of purchasing SaaS subscriptions. A custom tool that does exactly what the team needs rather than a $500/month SaaS that does 80% of it.

2. One-person software businesses: The barrier to building and selling a niche software product now approaches zero. Solo founders can build and ship products that would have required a team of 5+.

3. The 'SaaS squeeze': Generic SaaS products that relied on the high cost of custom software as a moat are being disrupted. If anyone can build custom, why pay for generic?

4. Non-technical innovation: Domain experts (lawyers, nurses, teachers, tradespeople) can now build software for their specific domain without needing to hire or partner with engineers.

What This Doesn't Change

  • Complex, large-scale systems still require engineering expertise
  • Security, reliability, and compliance for enterprise software remain engineering problems
  • User experience research and product design remain distinctly human skills
  • Software businesses still require distribution, marketing, and customer acquisition
Sign in to join the discussion.
Recent posts
No posts yet.
Info
You aren't logged in. Please Log In or Join for Free to unlock full access.