zarq (@zarqXBT)
@zarqXBT
AI writes my code. I write the future.
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Cohere just broke down the exact architecture for scaling reasoning models - better than any $5000 prompt engineering bootcamp.
chat models predict text -> agent models use verifiable rewards -> reinforcement learning filters bad actions -> agent scaffolding handles the environment.
That training loop is why raw prompt engineering is dead and RLVR is the only way forward for autonomous agents.
RLVR + deepseek GRPO + verifiable rewards + agentic scaffolding - that's the production stack.
Watch and save it, then stop writing chat prompts and start building agents.
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Cohere just open-sourced hardware-aware speculative decoding in vLLM and explained the full architecture - better than $3000 inference engineering courses.
request arrives -> draft model generates candidate tokens -> main model verifies in parallel -> accepted tokens skip full forward pass -> 2.3x throughput on identical hardware.
That loop is why production stacks running vLLM 0.6 are now serving at half the cost of last quarter.
vLLM + speculative decoding + FP8 quantization + hardware-aware scheduling - that's the stack.
Watch and save it, then upgrade your inference pipeline.
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