The value in software is shifting from SaaS platforms (like CRMs) to the AI agent layer that automates work on top of them. This will turn established SaaS companies into simple data repositories, or "hooks," diminishing their stickiness and pricing power as agents can easily migrate data.
Popular AI coding benchmarks can be deceptive because they prioritize task completion over efficiency. A model that uses significantly more tokens and time to reach a solution is fundamentally inferior to one that delivers an elegant result faster, even if both complete the task.
Despite premier access to OpenAI's models, Microsoft is failing to integrate them effectively and quickly. This execution problem is so severe it's deemed a "skill issue." CEO Satya Nadella’s personal focus on Copilot is viewed as a sign of existential crisis rather than strategic leadership.
Agentic coding tools like Claude Code represent a new, distinct modality of AI interaction, as significant as the advent of image generation or chatbots. This shift is creating a new category of power users who integrate AI into their daily workflows not just for queries, but for proactive, complex task execution.
Instead of a traditional top-down sales model, Anthropic is embedding its technology within enterprises by training 30,000 Accenture consultants on its tools. This creates a distributed, third-party implementation force that drives bottom-up adoption, effectively outsourcing enterprise sales and integration.
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."
While Amazon's massive AI spending plans seem ambitious, they are highly achievable due to the company's superior supply chain and data center construction capabilities. Unlike competitors who face delays, Amazon's projects are consistently on time and can scale rapidly, positioning them to out-build rivals in the AI infrastructure race.