Coinbase, Shopify, and Ramp Built Their Own Coding Agents... and Still Pay Anthropic
Coinbase, Shopify, and Ramp have built their own coding agents but still rely on Anthropic. We analyze the hybrid architecture that is defining enterprise software development and its impact on DevOps and business.
2 min read

In the race to dominate AI-powered software development, major tech companies are converging on a common architecture: building their own coding agents on top of third-party AI models. Coinbase, Shopify, and Ramp are clear examples of this trend, and they all still pay Anthropic for the underlying models.

Why Build Instead of Buy?
The decision to build custom agents stems from the need to control the workflow, integrate with internal systems, and maintain data privacy. However, Anthropic's language models (Claude) remain the cognitive engine powering these solutions. This reveals a hybrid strategy: differentiation at the application layer, but dependence at the model layer.
For SysAdmin and DevOps teams, this means that AI infrastructure becomes a critical component that must be managed, monitored, and optimized. Latency, cost per token, and reliability of Anthropic's APIs are now operational variables that directly affect development productivity.

Impact on Business Strategy
From a business perspective, investing in custom agents can be seen as a bet on long-term competitive advantage. By personalizing agents, these companies achieve greater efficiency in their specific workflows, reducing development time and improving code quality. However, the cost of maintaining this infrastructure is significant, and dependence on an external provider like Anthropic introduces pricing and availability risks.
For organizations that have not yet adopted this architecture, the lesson is clear: generative AI is not an add-on but a central component of engineering strategy. Those who do not integrate it deeply will be left behind.

Recommendations for Your Team
If you are considering building your own coding agent, first evaluate your specific needs and the maturity of your infrastructure. It's not just about technology, but also processes and culture. Ensure you have a team capable of maintaining and evolving the agent, and establish clear metrics to measure its impact.
It is also crucial to maintain a strategic relationship with model providers like Anthropic, negotiating agreements that give you flexibility and cost predictability. The architecture you choose today will define your agility tomorrow.
To delve deeper into how persistent agents are changing development, we recommend our analyses on Muse Code and Meta's bet. Also, don't miss our guide on secure generative AI implementation.
Source: The New Stack. ForgeNEX Analysis.
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