OpenClaw 2.0 brings several changes that affect how teams adopt and run the platform. The biggest practical concern is deployment scope: the new version works well for a single operator or a small team but is not designed for multi‑tenant SaaS offerings. If you need to serve multiple isolated customers, you must run a separate gateway instance per tenant rather than sharing one gateway.
Setup now starts from credentials you already have on the machine. The guided installer will look for verified Codex, ChatGPT or Claude CLI sign‑ins, accept an API key, trigger a provider sign‑in, or detect locally installed Ollama or LM Studio models. It validates that the chosen model can answer a live probe before persisting the selection, which reduces the chance of saving a broken configuration. For fresh OpenAI setups the default model is GPT‑5.6, while local inference now uses a managed llama‑server with Gemma 4 as the RAM‑gated default and a 64K context window.
The browser‑based Control UI is now the primary interaction surface. In simulated tests the rebuild cut JavaScript requests from 140 to 45 and startup time from roughly 1.6 seconds to 575 milliseconds. Docked panels provide a file editor (read‑only for create/delete), a git‑backed Changes panel, a browser panel for inspection and annotation, and a full‑screen web terminal. Approval requests stay inside the conversation that triggered them, and the /btw command opens a side chat to keep the main transcript clean.
Sessions and transcripts have moved to SQLite. Rolling back to an earlier file‑based release requires restoring archived transcript artifacts first; any sessions created after the migration will not appear in older versions. Taking a verified backup before upgrading is strongly recommended.
Shared cloud sessions enable true multiplayer work, allowing a second participant to join or take over live work with full context. However, the documentation explicitly states that these sessions are not a security boundary and do not provide tenant isolation. For scenarios that require strong separation, you must deploy separate gateways or rely on OS‑level user isolation.
Security posture remains centered on the gateway binding to loopback by default and unknown direct‑message senders receiving a pairing code. Model choice is highlighted as the first line of defense against prompt injection, with recent attack data showing low success rates against Claude Opus 4.5 but higher rates against Gemini 2.5 Pro. Adaptive human attackers still exceed 80 % success against state‑of‑the‑art defenses, so tool policy, execution approvals, and sandboxing remain essential enforcement layers.
To adopt OpenClaw 2.0 smoothly: verify your deployment model matches the single‑operator/team limitation, run the guided setup to reuse existing credentials, back up your SQLite store before any rollback, and enforce strict tool policies and approval workflows to mitigate prompt‑injection risk.
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