JetBrains AI

Strengths first. Air's core bet is that you keep your editors and swap the intelligence behind them, and the implementation is unusually complete for a first-generation product. Agent choice is real: Claude Agent, Codex, Junie, Copilot, OpenCode and anything ACP-compatible all run from the same surface, and you can switch provider subscriptions mid-session, mid-task. That matters when one agent stalls — you don't restart, you change the agent. Second, the review loop is well designed. You open diffs directly from an agent session, validate them with IDE tools, and comment on specific lines for the agent to act on, which is closer to a code review than to a chat window. Third, Air Context's semantic indexing means agents start with project understanding rather than scanning everything, which JetBrains pitches as lower exploration overhead and lower cost in production-scale repositories. Fourth, the org story is the differentiator: Air Governance gives per-team and per-individual model and agent permissions, flexible spend limits, and BYOK from Amazon Bedrock, OpenAI, Anthropic or any other provider — add the key once and every developer gets access. Air Teams adds shared projects in dedicated cloud environments with VM sizing, internet access controls, secret management, MCP servers configured once for the team, and automations triggered by merges, branches, PRs, issues and commits. Where it's weaker: this is a configuration surface, not a one-click product. You're expected to bring a provider subscription, an API key, or a base URL, or to meter usage through JetBrains AI credits billed at public API rates. Agent runs consume credits — the vendor's own automations panel shows per-run spend ranging from roughly 0.31 to 18.46 credits across a handful of seconds — so cost is metered, not flat, and heavy automation users will notice. Cloud agent runs are rolling out gradually: JetBrains says they're available for some customers in IDEs and the browser today, with rollout to the rest over coming months, so parity across IDE, browser, CLI and mobile isn't there yet. And the whole thing is worth much less if your team isn't on JetBrains IDEs. Where it fits: Java, Kotlin, Python and .NET shops already on IntelliJ IDEA, PyCharm, WebStorm or Rider; platform teams that want shared MCP servers and per-project cloud environments; regulated orgs that need BYOK and org-wide agent permissions. Where it doesn't: VS Code-first teams, buyers who want one default agent chosen for them, and anyone who won't configure providers, keys, agent connections and MCP servers. On cost efficiency, JetBrains' own July 2026 research found terse 'caveman' prompts cut agent token usage by roughly 65% — a useful signal that agent running cost, not licence price, is the number to watch here.