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The decision to build or buy software has evolved. Companies should buy commodity infrastructure (e.g., dialers, CRM plumbing) but must own the "intelligence" layer—the unique business logic for things like ICP definition or lead scoring. This allows for customization and portability, preventing vendor lock-in.

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When deciding to build or buy, the key factor is strategic importance. Never cede control of technology that is core to your unique value proposition to a vendor. Reserve outsourcing for necessary but commoditized functions that don't differentiate you in the market.

The key for enterprises isn't integrating general AI like ChatGPT but creating "proprietary intelligence." This involves fine-tuning smaller, custom models on their unique internal data and workflows, creating a competitive moat that off-the-shelf solutions cannot replicate.

The rise of AI agents introduces a new strategic layer for marketers. They must now decide when to buy out-of-the-box agents, use workflow tools for assembly, or custom-build agents for niche, proprietary tasks. This "build vs. buy" competency is becoming a key marketing differentiator.

Companies will adopt a hybrid "build vs. buy" approach. They will use AI agents to build bespoke, simple software "screwdrivers" for specific workflows on the fly, eliminating many niche SaaS tools. However, they will continue to "rent" large, foundational platforms like ERPs and CRMs, which serve as heavy-duty "trucks."

For decades, buying generalized SaaS was more efficient than building custom software. AI coding agents reverse this. Now, companies can build hyper-specific, more effective tools internally for less cost than a bloated SaaS subscription, because they only need to solve their unique problem.

The traditional wisdom to "build what's core" to your business is becoming obsolete for AI. The immense cost and rapid advancement of foundational models by major labs mean most companies are better off buying or partnering for core AI capabilities rather than attempting to build them in-house.

When deciding whether to build or buy an AI tool, purchase stable, undifferentiated infrastructure (like a dialer). In-house resources should focus on building proprietary intelligence that creates a unique competitive advantage, such as a custom pre-call research model tailored to your specific customer profile.

When deciding to build versus buy, tech-enhanced services companies should only build software that codifies their unique strategic opinions and subject matter expertise. Commoditized features, even if core to the workflow, are better bought or rented, preserving engineering for true differentiation.

Nimble small and medium-sized businesses will increasingly use AI to build custom internal tools, especially for CRM. They will opt to create the 20% of features they actually need, rather than pay for complex, expensive enterprise software where they ignore 80% of the functionality.

Forgo building custom AI tools for common problems. Instead, purchase 90% of your AI stack from specialized vendors. Reserve your in-house engineering resources for the critical 10% of tasks that are unique to your business and for which no adequate third-party solution exists.