20,000 tokens for a greeting, 40,000 tokens for a line of code. An agent's excessive reasoning is not a technical limitation but a thoroughly deliberate structure. This piece digs into the structure that profits platforms and API vendors the more tokens get consumed.

Every small action an agent takes leads straight to tens of thousands of tokens in API cost. This piece covers the structure where a 10-step loop bills 43x rather than 10x, real bill-shock cases, and cost-cutting strategies.

An agent-oriented directory that organizes everything on Agent Space by topic. URLs and descriptions are structured so AI agents can reach the information they want quickly.

From first-generation search, where humans typed keywords, to third-generation agentic search, where AI agents cross-verify hundreds of sources — this piece compares per-generation cost, processing style, and empirical benchmarks, and gathers global developer feedback.

IFM's K2 Horizon 3.7B is a 3.7B tiny model that achieves a 512K context and 68.6% on SWE-bench. This piece rounds up the official benchmarks, architecture analysis, and a local deployment guide.

With the September 22 launch of GPT-6 Sol ($2/$10) and Luna ($0.10/$0.50), API prices dropped 50% versus GPT-5.6. This piece cross-verifies benchmarks and real-user feedback to decide which model to deploy for which task.

A single document covering the Qwen 4 Apsara Conference announcements, an evidence-based benchmark comparison of Qwen 3.8-27B vs Claude Opus 4.6 Max, and local GPU (16-24GB) setup.

Based on the specs of Qwen 3.8 Max (2.4T), this predicts the class of Qwen 4 Max and lays out the roadmap revealed at the Apsara Conference along with verified specs. It also includes criteria for telling fake rumors from the real thing.

A technical report diagnosing the AI agent boom as a bubble on the grounds of developer concentration, retention collapse, CapEx/ROI imbalance, and the absence of a killer app. It states that the cited figures are as provided by the source and unverified.

Analyzes the big-tech-led AI agent and image generation boom from a value-creation standpoint: developer concentration, retention collapse, enterprise ROI imbalance, and the absence of a killer app, and states the need to verify the cited figures.