Enterprise engineering teams are converging on a common architecture for AI-assisted software development, with Coinbase, Shopify, and Ramp each building an internal coding agent for their developers. None of those house-built agents have replaced commercial tools such as Claude Code, Codex, or Cursor, making this less a build-versus-buy decision and more an architectural one. The layer these companies chose to own is not the large language model but the agent harness—the execution environment providing context, permissions, workflow orchestration, tool access, and verification. Frontier models from Anthropic, OpenAI, and Google continue to provide the reasoning engine, while enterprises increasingly own everything around it. LangChain acknowledged this architecture has become repeatable by open-sourcing Open SWE, describing it as the public implementation of the same pattern already deployed internally at Stripe, Ramp, and Coinbase. Although Forge, River, and Inspect were developed independently, they solve remarkably similar problems. Coinbase’s Forge integrates Slack, GitHub, and Linear into a workflow that can convert a bug report into a pull request with minimal developer intervention. Shopify’s River operates on a reproducible engineering environment backed by a company-wide monorepo, durable execution sessions, sandboxed environments, credential management, and reusable engineering skills. Shopify reports that River now participates in one out of every eight merged pull requests. Ramp’s Inspect executes inside sandboxed virtual machines that closely mirror developers’ local environments, integrating with Dat