Author here. This is a personal weekend project that grew into a working WhatsApp bot. It replies as me to two allowlisted contacts (myself + one friend who knew about the experiment). The interesting part is not the agent framework but the retrieval I eventually got the best results with: every reply gets generated by Claude after pulling 8 of my real past replies to that specific contact, filtered by recency.
Built on Hermes Agent + Baileys + Chroma + nomic-embed-text-v2-moe + Claude Sonnet 4.6 via Azure AI Foundry. About 2 hours of work plus an hour debugging a WhatsApp multi-device LID issue. Total runtime cost: ~$0.005 per reply.
The bot is not running on a dedicated number. It is hooked to my primary WhatsApp, which is a ban risk I accepted in exchange for being able to test with real contacts. The killswitch (Telegram command that empties the allowlist and restarts the gateway) takes about 10 seconds. There is also
a hard kill: unlink the device from WhatsApp on the phone, ~5 seconds, severs the bridge session entirely.
probably all AI slop but I find it hilarious in the blog post they actually posture like they would know how to fine tune a model to sound like them given that what they actually did is something that you could one shot with claude if you knew what you were doing.
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[ 4.0 ms ] story [ 13.4 ms ] threadBuilt on Hermes Agent + Baileys + Chroma + nomic-embed-text-v2-moe + Claude Sonnet 4.6 via Azure AI Foundry. About 2 hours of work plus an hour debugging a WhatsApp multi-device LID issue. Total runtime cost: ~$0.005 per reply.
The bot is not running on a dedicated number. It is hooked to my primary WhatsApp, which is a ban risk I accepted in exchange for being able to test with real contacts. The killswitch (Telegram command that empties the allowlist and restarts the gateway) takes about 10 seconds. There is also a hard kill: unlink the device from WhatsApp on the phone, ~5 seconds, severs the bridge session entirely.
Happy to answer questions.