Incumbent software like Epic often just digitized outdated, paper-based processes, inheriting their inefficiencies and data silos. AI-native companies can ignore this technical and process debt, designing workflows from a clean slate to fundamentally disrupt giants whose products are built on obsolete logic.

The "all-in-one" SaaS pitch is making a comeback because AI agents thrive on comprehensive context. Fragmented point solutions starve AI models of the necessary data to perform at a high level. Therefore, building a single platform that holds all the context is now a critical competitive advantage, not just a convenience.

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.

The shift to AI creates an opening in every established software category (ERP, CRM, etc.). While incumbents are adding AI features, new AI-native startups have an advantage in winning over net-new, 'greenfield' customers who are choosing their first system of record.

Adding AI tools to current processes yields only incremental efficiency. To achieve significant business impact, leaders must rebuild their entire go-to-market system—roles, workflows, and data flow—with AI at the core, not as an add-on.

Startups challenging Salesforce aren't winning with better UI but with agentic capabilities that replace human SDRs to generate pipeline and bookings. This shifts the CRM from a system of record to an automated revenue engine, making it an easy sell despite market saturation.

Incumbent SaaS companies like Salesforce are cutting off API access to prevent AI startups from siphoning value. To build a durable business, new AI companies cannot simply be a "system of action" on top of old platforms; they must aim to become the new system of record, which requires building complex data migration tools from day one.

When generative AI emerged, the team feared their existing product would become obsolete. Instead of retrofitting AI features, they made the strategic decision to rebuild the entire platform from the ground up with AI at its core. This allowed them to realize their long-term product vision.

To succeed in the AI era, SaaS companies cannot just add AI features. They must undergo a 'brutal' transformation, changing everything from their org chart and GTM strategy to their core metrics and pricing model. This is a non-negotiable, foundational shift.