OpenClaw 5.4 Adds /steer and /side Commands: Redirect Agent Mid-Task Without Losing Context
OpenClaw 5.4 introduces two new commands that solve a common pain point: /steer and /side. These let you redirect an agent's current task direction or ask an unrelated question without losing the existing context or starting a new session.
What They Do
/steer— Redirects the agent's current task direction without starting a new session. If your agent is going down the wrong path on a research task, you can steer it without losing all the context it already gathered./side— Starts a side conversation within the same session. Ask a quick unrelated question without derailing the main task. The agent maintains both threads independently.
Before these commands, options were limited: interrupt the agent (losing context) or wait until it finishes (potentially wasting tokens on the wrong direction). These commands preserve context and save tokens.
Auto-Reply Queue Changes
The auto-reply queue has also been updated. Reset-triggered /new and /reset are now treated as interrupt runs. When you hit /new, the agent stops existing work immediately instead of queuing your fresh start behind whatever it's currently doing. This makes daily usage less frustrating—the gap between 'cool demo' and 'usable daily tool' is made of exactly these kinds of fixes.
Who It's For
Developers using OpenClaw AI coding agents who need mid-task redirection without context loss. This is directly useful for research, debugging, or any multi-step task where the agent's initial direction needs course correction.
📖 Read the full source: r/openclaw
👀 See Also
Hacker News AI Discussion Shifts from Demos to Tooling Focus
Recent Hacker News discussions about AI are moving from one-off demos to durable tools like price tracking, verification, memory, evaluation, and workflow integration. This signals a shift toward operationalization where communities stop rewarding novelty-first posts.
Qwen3-30B-A3B vs Qwen3.5-35B-A3B Performance Comparison on RTX 5090
A head-to-head benchmark of Qwen3-30B-A3B and Qwen3.5-35B-A3B on an RTX 5090 shows the 30B model is 35% faster in generation, while the 3.5 model handles long context better with flat token scaling versus the 30B's 21% degradation.
AI Is Too Expensive: Hyperscalers Need $3 Trillion to Break Even
Hyperscalers have invested over $800B in AI capex, with $1T more planned for 2027. Microsoft alone spent ~$100B on OpenAI infrastructure, yet AI revenue covers only ~20% of its capex.
Anthropic Separates Programmatic Usage from Claude Subscriptions: New Credit Pool Arrives June 15
Starting June 15, Claude subscriptions get a dedicated monthly credit for programmatic use (Agent SDK, claude -p, Claude Code GitHub Actions). Interactive credits no longer subsidize programmatic calls; after the pool runs out, users pay full API rates.