The Rebirth of 'Build' in the AI Era

There was a time...not long ago...when the build-versus-buy conversation was mostly about budgeting and resourcing. Teams leaned toward buying software because it promised speed, reliability, and a known quantity. Internal builds were seen as distractions. SaaS vendors thrived in that context.

But AI has rewritten the economics.

Platforms like Replit, Claude, Cursor, GitHub Copilot, and others have changed the nature of building. Today, natural language is a valid way to describe and implement software behavior. That means building is no longer constrained to engineers with deep knowledge of full-stack systems. It’s increasingly accessible to generalists, analysts, and even legal professionals.

The Business Insider story about Netlify engineers building internal tools over a weekend with AI tools wasn’t just anecdotal...it echoed a pattern we’ve seen across many teams. These tools allow developers to skip boilerplate and scaffold functionality quickly, leading to more experimentation and faster iteration. What used to be a multi-week sprint is now a Friday afternoon project.

Anthropic’s Claude recently added support for building interactive apps with no coding or API experience required. This marks a shift from no-code platforms of the last decade, which often required detailed UIs and configuration, toward agentic models that can handle complexity with natural instructions.

Fortune reports that companies like Hewlett Packard Enterprise are now evaluating whether they should build internal AI tools tailored for contract review and legal workflows, citing customization and data control as key advantages. Legal departments that previously outsourced or bought solutions are now turning inward, using internal talent and off-the-shelf LLMs to spin up solutions faster and with more oversight.

One of the clearest impacts of AI in this space is that the cost of attempting to build, once a gating factor, has essentially disappeared. With Copilot or Cursor acting as a fast autocomplete, and Claude interpreting broad instructions, teams can validate whether building is viable much faster. Failed attempts cost less. Successful ones ship faster.

The result? SaaS tools that used to offer convenience are now being scrutinized for their rigidity, pricing, or integration friction. If a team can replicate 80% of the functionality in-house with AI in a weekend, they may never even issue an RFP.

The shift is especially apparent in domains like ops and marketing automation, where workflows are specific and evolve rapidly. Why buy something generic when your team can build something tailored?

This environment requires a fresh lens for evaluating software strategy:

These aren’t abstract questions. They’re operational. And the teams asking them are getting faster and more autonomous.

Hiring great developers used to be the bottleneck. Now it's about finding people who can move fast, collaborate across tools, and co-build with AI.

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As Forbes recently noted, the distinction between building and buying is blurring. Smart teams are blending both: stitching together purchased infrastructure with custom-built functionality. The tools may come off the shelf, but the orchestration is increasingly internal.

In a viral discussion on Hacker News, a developer summarized the shift: “It used to be: build only if you have to. Now it’s: build if you can do it faster or better...and with AI, you often can.”

That mindset is creeping upward. Product leads are discovering that their teams can move faster when AI reduces the overhead of building. Engineering leaders are rethinking capacity planning. And finance teams are seeing a new kind of ROI: not from vendor consolidation, but from eliminating wait time.

Windsurf, recently acquired by OpenAI, reflected this in their post-acquisition interview: “The question isn’t just how fast can we code. It’s how fast can we learn and adapt with AI in the loop.”

Buying software won’t go away. There will always be places where a mature product, with support and reliability, is worth the cost. But the baseline has changed. Building no longer means delay or distraction. It can mean speed, control, and better alignment with the problem at hand.

In the AI era, the most valuable organizations won’t ask whether to build or buy. They’ll ask: what’s the fastest way to solve this problem today?

And increasingly, the answer will start with a prompt.

✔️ From Cloud-First to Control-First (Omniscien Technologies)

✔️ Cracking the AI Infrastructure Code: Cloud, On-Prem, or Hybrid? (TD Synnex News)

✔️ Cloud AI vs. on-premises AI (Plural Sight)