Why Cost Per Task Beats Cost Per Token
Discover why cost per completed task is a better AI metric than cost per token in 2026, and how to compare models the right way. Read the full guide.
Writing about the craft of prompting, the shape of agents, and the small engineering decisions that make models useful in real work.
Discover why cost per completed task is a better AI metric than cost per token in 2026, and how to compare models the right way. Read the full guide.
Discover why AI routing is now a core product layer, and how a multi-model gateway improves cost, uptime, quality, and control. Read the full guide.
prompt engineeringDiscover why the Mercor breach mattered more than model context, and what Anthropic's Claude Mythos exposure reveals about AI system risk. Read on.
ai newsDiscover how Opus 4.7, DeepSeek V4, and Qwen 3.6 Plus handle 1M-token recall and multi-hop reasoning. See where each model breaks. Read on.
ai toolsDiscover what Mythos solving the 32-step Last Ones cyber range really means for AI security, autonomy, and risk. Read the full guide.
ai newsDiscover which coding benchmark best predicts production quality across SWE-Bench Pro, Terminal-Bench 2.0, and SciCode. See examples inside.
ai toolsDiscover why Anthropic restricts Mythos while OpenAI ships broadly, and what this split reveals about AI strategy in 2026. Read the full guide.
ai toolsDiscover how Alibaba and Moonshot are dividing China's AI stack between closed flagships and open mids. See what it means for builders. Try free.
ai toolsDiscover why Qwen3.6-27B beat Qwen3.5-397B by improving efficiency, architecture, and training instead of just scaling MoE. Read the full guide.
ai toolsDiscover why Qwen benchmark wins don't settle the GPT-5.5 vs Claude Opus 4.7 debate, and what real testing reveals instead. Read the full guide.
ai toolsLearn how MCP turned Gemini Deep Research into an enterprise pipeline with better tools, governance, and deployment patterns. Read the full guide.
prompt engineeringLearn how to use Claude task budgets and xhigh effort to control reasoning spend in long-running agents without killing quality. See examples inside.
prompt engineering