AI Coding Assistants

Today's Stories

1. 1

   11 agency reviews to know about: Coca-Cola, Levi's, Copilot, IBM, Intuit

   11 agency reviews to know about: Coca-Cola, Levi's, Copilot, IBM, Intuit

2. 2

   Resona Group Working on Corporate Transformation. Creating Value Through Human-AI Collaboration with AI Agents Using Copilot Studio

   Resona Group Working on Corporate Transformation. Creating Value Through Human-AI Collaboration with AI Agents Using Copilot Studio

3. 3

   Anthropic breaks down AI coding loops into 4 types for Claude Code users

   Anthropic published a guide titled "Getting started with loops" on June 30, 2026, explaining how Claude Code's loop feature works across four distinct patterns: turn-based, goal-based, time-based, and proactive loops. The guide organizes each loop by what triggers it, when it stops, what primitive it uses, and what comes after. AI agents often get stuck repeating tasks without clear stopping points. By naming and contrasting these four loop types, Anthropic helps developers and AI teams design more predictable automation—each pattern suits different workflows (e.g., turn-based for human-driven feedback, goal-based for autonomous targets, time-based for scheduled checks, proactive for human-directed agent behavior). This clarity reduces confusion about when and how to apply loops in Claude Code.

   The guide emphasizes the difference between /loop (local, runs on your PC) and /schedule (cloud-based, runs as a background service). Developers can also use "Routines" in Claude Desktop to automate loop execution. The distinction between these two command types and the proactive loop design may help teams avoid costly repeated token consumption and better manage agent workload.

4. 4

   Zhipu AI launches ZCode to rival Claude Code with 1M-token context

   Zhipu AI (Z.ai) released ZCode, a code-writing agent built on its GLM-5.2 model, offering natural-language code generation, debugging, testing, and Git integration. New customers get a free five-day trial with up to 5 million tokens per day; subscribers receive about 1.5 times more quota through July 2026. GLM-5.2, shipped in June 2026 under an MIT license, has attracted developers seeking an alternative to pricier Western models like Claude Opus. A Snowflake comparison across 103 tasks showed GLM-5.2 and Opus 4.7 nearly tied after three attempts, suggesting Z.ai's offering could appeal to teams looking to reduce AI infrastructure costs.

   ZCode's 1M-token context window is designed to handle multi-step programming tasks without losing context. The agent can be controlled remotely via Feishu, WeChat, or a smartphone, expanding access beyond web-based workflows.

5. 5

   Economist maps AI worldviews via values survey; enterprise RFPs still ignore them

   The Economist ran 25 frontier AI models through the World Values Survey—a questionnaire that has tracked moral beliefs across 100 countries since 1981—and plotted them on two axes: traditional-to-secular and survival-focused-to-self-expression. Models clustered in unexpected ways: Gemini 3.1 Flash Lite and Qwen 3.6 Flash sit as neighbors in self-expression; GPT-4o and DeepSeek R1 are near-twins despite training in different cities; DeepSeek R1 and DeepSeek V4 Flash, from the same lab, lie at opposite ends of the secular-to-traditional axis. Current enterprise procurement checklists score price, latency, context window, and benchmark scores—but not worldview. For code generation and technical tasks, worldview is irrelevant. Once a model is used for business decisions in a specific market—marketing copy, user-behavior predictions, customer-support tone—its embedded values become a live input that must match the target demographic's expectations. The variance in the survey results suggests that choosing a model without considering its worldview may create a mismatch between the AI's responses and customer values.

   The post-training choices (such as alignment to UN principles, as Anthropic does with Claude) appear to override shared base training data. Common Crawl, which makes up 46% English, gives models a college-educated American online voice by default, yet different companies then reshape that foundation in divergent directions. How enterprises begin to incorporate worldview into procurement—or whether they ignore it—will determine whether AI alignment strategy becomes a procurement checkbox.

6. 6

   Reddit asks: what AI agents actually work for you?

   A Reddit user asked the community to share real-world AI agents they've built or used—not polished demos, but practical tools that save time or automate manual work. Examples mentioned include customer support, appointment scheduling, sales follow-ups, coding assistants, personal productivity, phone call automation, and research workflows. The post highlights a gap between AI agent hype and practical deployment. Many agents are showcased as videos but may not deliver real value in day-to-day work, making it useful for business leaders to hear which use cases have genuinely worked and which ones fell short of expectations.

   The discussion surfaces which agent categories deliver genuine time savings versus which ones remain experimental, helping clarify where AI agents are ready for real business adoption today.