WhatsApp on OpenClaw: Save Yourself 2 Hours by Updating to 5.7 First

Setting up WhatsApp on OpenClaw for the first time? Here's the tribal knowledge missing from the docs, straight from a user who just helped a friend through it.
Key Setup Facts
- OpenClaw uses Baileys, an unofficial WhatsApp Web library — not the official Business API. Your personal WhatsApp number becomes the bot, and it cannot be used on a number already active on WhatsApp Web on your phone. Pairing happens via QR code during onboarding.
- The gateway must run 24/7. If the connection drops, you have to re-pair. Laptop sleep will break it — use a VPS or always-on machine.
Critical Bugs Fixed in 5.7
If you're on 5.6 or earlier, you will hit several WhatsApp-specific bugs. Update to 5.7 before proceeding:
- Ghost chats (fixed in 5.7, #67378): Proactive messages to phone numbers would create sender-only ghosts that nobody received.
- Stale TUI clients (fixed in 5.7): On 5.5, they degraded the gateway event loop, slowing ALL replies — not just WhatsApp.
- Captioned media double-send (fixed in 5.7, #78770): Before the fix, recipients would get an empty message first, then the actual photo.
Bottom line: Update to OpenClaw 5.7+ before setting up WhatsApp. Earlier versions have multiple WhatsApp-specific bugs that will make you think your setup is broken. If you want full control, OpenClaw works fine on 5.7+. If you prefer less hassle, BetterClaw handles WhatsApp setup in minutes without the Baileys pairing dance.
📖 Read the full source: r/openclaw
👀 See Also

Practical Habits for Critical LLM Interaction
A Reddit post outlines specific techniques for avoiding confirmation bias when working with LLMs, including custom prompt modes like 'strawberry' for neutral explanation and 'socrates' for adversarial scrutiny, plus evaluating training data composition.

How splitting context into separate files made Claude more consistent
A Reddit user shares a practical setup for Claude: split context into about-me.md, my-voice.md, and my-rules.md files; use a plan-before-execute flow; switch models per task; and give feedback instead of perfect prompts.

Running MiniMax M2.7 Q8_0 128K on 2x3090 with CPU Offloading – Real-World Benchmarks and Config
A user successfully runs MiniMax M2.7 at Q8_0 with 128K context on two RTX 3090s plus DDR4 RAM, achieving ~50 tps prompt processing and ~10 tps token generation, and shares their llama-server flags.

OpenClaw token usage investigation reveals configuration issues
A developer burned through their OpenAI Codex weekly subscription in 1.5 days and used Claude Code to identify configuration problems: Telegram bots firing on every message, web fetches returning raw CSS/JS, and orphan session files accumulating.