Author’s note: Using DeepSeek’s super-agent design as a starting point, this article breaks down how to assign models to routers and workers in a multi-agent system—and how cache-read tokens affect architecture costs. When building a multi-agent coding system, most people give the strongest model to the “commander” and cheaper models to the agents doing the…
Author’s note: Using Microsoft Copilot’s publicly described synthetic enterprise environment as an example, this article breaks down its three-layer approach—synthetic environments, automated query generation, and quality checks—and offers evaluation set building steps and a checklist for small and midsize teams. When an enterprise AI assistant or knowledge application is getting ready to launch, the people…
Author’s note: Before choosing a third-party AI subscription or API access provider, use the eight-point checklist in this article to check account security, order status, refund rules, support channels, invoicing, and payment. Then compare prices. Many users and teams in China want to use ChatGPT Plus and Large Language Model APIs, but find official payment…
Author’s note: An Agent can read web pages and turn what it finds into a list, but it gives you “leads you can choose to follow,” not “evidence you can quote directly.” This article uses a public account of an Agent session to explain four things writers need to verify themselves after the Agent gathers…
Author’s note: Starting with the principle “ask a person only when deleting data, spending money, or changing direction,” this article breaks down three dimensions for setting human decision boundaries in Agent automation systems, designing approval channels, and dividing verification work with CI. When an Agent goes from “chatting with you” to “working for you,” the…
Author’s note: This article explains the causes of AI API 429, 401, and 500 errors and how to handle them. It covers which errors to retry, which require configuration fixes, and when to use exponential backoff, multi-model fallback, and circuit breakers. If you’ve worked with Large Language Models in production, you may have seen a…
Author’s note: This article draws three agent security priorities from the Cisco customer case study to help enterprise teams distinguish malicious attacks from agents that “mean well but do the wrong thing”—and translate that distinction into monitoring and control design. Once agents are in production, security teams face more than just external attacks. An agent…
Author’s note: This article breaks down the Token bill for long-running Agent tasks, explains why input Tokens account for most of the usage, and shows how to structure context to improve prefix cache reuse. Many teams discover a problem only after integrating multi-step Agents into their products and checking the bill at the end of…
Author’s note: This article is for developers already using Agents in their work. It explains what context, reference materials, and checkable acceptance criteria to prepare before handing off a task—and which decisions still need human oversight. Using Agents can boost output, but it can also leave you more exhausted. On November 3, 2026, a developer…
Author’s note: Drawing on official demos and third-party tests by Zhidx and TOKRACE, this article examines LongCat-2.5’s real-world capabilities in screenshot-to-webpage conversion, interactive pages, and 3D generation, along with typical failures and the limits of what can be accepted for delivery. Meituan officially released LongCat-2.5 on 2026-11-02, highlighting Visual Coding as one of its key…
