In the AI era, defining problems is often more important than solving them; here we explore AI's contradictions, boundaries, and possibilities.
In March 2026, OpenRouter recorded 9.55 trillion tokens consumed weekly, with Chinese models occupying six of the top‑10 slots, Qwen surpassing 1 billion downloads, and cost advantages that let domestic LLMs outpace U.S. counterparts in both performance and price.
Analyzing 168 OpenClaw projects from TrustMRR, the article reveals a $3.18 million total revenue where 42% earn nothing, two projects capture 57% of earnings, and most participants profit by selling services, tutorials, or token‑based courses rather than improving enterprise efficiency.
The article analyzes how AI agents that operate directly via APIs are eroding the UI‑centric SaaS model, reshaping developer roles, collapsing seat‑based pricing, and shifting value toward infrastructure and deep‑vertical solutions while highlighting transitional friction and future opportunities.
The article explains that the term “Agent development” hides a fundamental split between Agent Frameworks, which give developers building blocks to assemble their own agents, and Agent Harnesses, which provide ready‑to‑run agents, and shows how this distinction affects decisions, maintenance, and troubleshooting.
Pi is a lightweight, terminal‑based AI coding agent that focuses on a minimal set of core capabilities—read, edit, bash, and multi‑model support—while exposing a tree‑structured conversation history and an extensible TypeScript plugin system, contrasting sharply with feature‑heavy competitors.
The article examines whether the success of AI agents stems from ever‑stronger large language models or from the surrounding harness—context management, tool orchestration, and reliability engineering—by comparing viewpoints, empirical evaluations, and practical guidance for developers.
This guide explains the SKILL.md open standard, its four core characteristics, directory layout, gating and lifecycle controls, testing with the Evals framework, market adoption stats, and future self‑evolving agent capabilities, providing step‑by‑step instructions for creating, installing, and iterating Skills across multiple AI platforms.
Over 19 days OpenClaw shipped 10 releases comprising 100 changes—38% new features, 24% security fixes, 12% breaking changes, 18% bug fixes and 8% infrastructure updates—accompanied by detailed CVE analyses, architecture evolution insights and a step‑by‑step upgrade checklist for operators.
The article analyzes how AI‑generated code is proliferating faster than human reviewers can handle, presenting data on PR volume and security risks, contrasting arguments for abandoning code review with proposals for a balanced, risk‑aware review process.
The article explains LLM inference stages, how KV‑cache and vLLM's Paged Attention enable cross‑request prompt caching, and shares practical guidelines for prompt ordering, immutable caching, and robust tool design that together shape efficient and reliable AI agent architectures.
