AI Agent on E7Coding

Agent Skills: Packaging Senior Engineering Discipline Into AI Coding Agents

Joy — Sat, 11 Jul 2026 10:30:00 +0800

AI coding agents have a common failure mode: they default to the shortest path. Ask one to add a feature, and it often starts coding immediately, skipping specs, tests, security review, and the practices that make software reliable. Addy Osmani’s Agent Skills aims to fix exactly that: package senior engineers’ production workflows, quality gates, and judgment into skills that agents can follow consistently, covering every stage from idea to launch.

GPT-5.6 Sol, Terra, and Luna: OpenAI Splits Agentic Coding Into Three Tiers

Joy — Fri, 10 Jul 2026 09:00:00 +0800

OpenAI previewed the GPT-5.6 family: Sol, Terra, and Luna.

The most important part is not just “another stronger model.” It is that OpenAI is explicitly splitting agentic coding models into three tiers: one frontier model, one everyday balanced model, and one fast low-cost model.

What Is A2A: How Different Agents Discover, Communicate, and Collaborate

Joy — Wed, 01 Jul 2026 15:40:00 +0800

A2A stands for Agent2Agent Protocol.

It is not about how a model calls tools. It is about how different agents discover each other, exchange messages, and collaborate on tasks.

As organizations begin deploying multiple agents internally, a practical problem quickly appears: a sales agent, support agent, finance agent, legal agent, and engineering agent may come from different teams, vendors, and frameworks. They cannot only operate inside their own systems. They also need to delegate work, pass context, and return results to one another.

What Is MCP: A Stable Way for Agents to Connect Tools and Context

Joy — Wed, 01 Jul 2026 15:30:00 +0800

MCP stands for Model Context Protocol.

Its role is clear: it provides an open protocol for connecting AI applications to external systems. Those systems may be local files, databases, search engines, business APIs, design tools, knowledge bases, or predefined prompts and workflows.

Claude Sonnet 5: A More Agentic Sonnet Model

Joy — Wed, 01 Jul 2026 09:20:00 +0800

Anthropic released Claude Sonnet 5.

The keyword for this upgrade is not “better chat.” It is more agentic: better at making plans, calling tools, using browsers and terminals, and pushing multi-step tasks forward instead of stopping halfway.

Five Archetypes of Future Product Teams: From Job Functions to Value Functions

Joy — Tue, 30 Jun 2026 13:00:00 +0800

I recently saw an interesting tweet: as engineering, product, design, data science, and other functions begin to merge into more hybrid roles, will future teams stop defining people by job titles and instead define them by how they create value?

Claude Skills vs. Agents: What Is the Difference and How Should You Choose?

Joy — Tue, 16 Jun 2026 16:15:00 +0800

When extending Claude, Skills and Agents are easy to confuse. Both look like ways to make Claude able to do more, but underneath they are very different. Remember the fundamental difference in one word: context. A Skill puts instructions into your current conversation. An Agent works in an isolated context and returns only the conclusion.

Helping Claude Use MCP Well: Six Prompting Tips and One Core Principle

Joy — Tue, 16 Jun 2026 15:50:00 +0800

After connecting Claude to MCP (Model Context Protocol), it can read project files, search code, and run commands. But many people find that even after setup, Claude still misses the point. The reason is simple: MCP gives Claude capability, not context. Claude must call tools before it can see your project. How you ask directly affects whether it calls the right tools and gives useful answers. This article covers six prompting tips and one core principle.

Why Multi-Agent Parallel Development Works: Git Worktree Isolation and Coordinated Merging

Joy — Tue, 16 Jun 2026 15:40:00 +0800

When you want multiple AI agents to work on the same codebase at the same time, the first wall you hit is that they share one working directory and overwrite each other’s files. Git Worktree + coordinator/worker mode exists to solve this. This article explains the principles, why it works, and where the benefits come from.

Getting Started with AI Agent Development: From Concepts to a Minimal Tool-Using Agent

Joy — Tue, 16 Jun 2026 15:00:00 +0800

AI agent development means building a system that can perceive, reason, plan, call tools, and execute tasks to achieve a goal. In one sentence: traditional AI, such as a normal chatbot, answers one question at a time; an AI agent is more like a digital worker. Give it a high-level goal, such as “analyze this company’s financial report and turn it into a 10-slide deck,” and it can break the work into steps, gather information, run code, call APIs, and deliver the result.