graphwiz.ai

Tokenomics: Where AI Agents Actually Spend Their Tokens

Empirical analysis of token consumption in LLM-based multi-agent systems reveals that 59.4% of tokens go to code review, not generation — and a 2:1 input-to-output ratio exposes the 'communication tax' haunting agentic workflows.

tokenomicsai-agentsllmcode-reviewagentic-aicost-optimisation

Qwen3.6-35B-A3B: What the Numbers Actually Show

Alibaba released Qwen3.6-35B-A3B on 16 April 2026, the first open-weight model in the Qwen3.6 series. The benchmarks show real gains in agentic coding, but the architecture is unchanged from Qwen3.5 and the red flags warrant scrutiny.

qwenmoellmopen-sourceagentic-aicodingalibaba

Arcee AI Trinity-Large-Thinking: The $20M Open Model Chasing Claude

A 26-person startup spent $20M training a 400B MoE model on 2,048 B300 GPUs — and produced the strongest open reasoning model outside China. Trinity-Large-Thinking ranks #1 on τ²-Airline at 1/28th the cost of Claude Opus 4.6.

arcee-aitrinitymoeopen-sourceapache-2llmagentic-aireasoning

Prompting Techniques for Agentic AI

A practical guide to engineering prompts for autonomous AI systems that plan, act, and iterate toward goals.

aipromptingagentic-aillmai-agents

Qwen3.5-35B-A3B: Production Deployment on GB10 Grace Blackwell

Deploy Qwen's latest agentic coding model with vLLM on NVIDIA DGX Spark. Complete configuration for tool calling, extended context, and optimal performance on the GB10 Grace Blackwell Superchip.

qwenvllmllmself-hosteddockernvidianvidiaagentic-ai