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09:21

A harness for every task: dynamic workflows in Claude Code

Claude Code 动态工作流：让 AI 自动编写任务专用的编排脚本

Anthropic engineer Thariq Shihipar details dynamic workflows in Claude Code, where Claude auto-generates custom JavaScript harnesses to orchestrate multiple subagents. It explains how this overcomes single-context-window failures like agentic laziness, self-preferential bias, and goal drift. Common patterns such as classify-and-act, fan-out-and-synthesize, adversarial verification, and tournament are illustrated with concrete use cases from migrations and deep research to root-cause analysis. The post candidly advises that workflows are token-heavy and not needed for routine coding, offering practical tips on token budgets, saving workflows as skills, and pairing with /goal and /loop.

x.com · 15 min · Agent Architecture · Agents · Ai Tooling · Claude Code · Orchestration
06:00

Turn Claude into a Consistent Assistant with CLAUDE.md: 21 Essential Instructions

用21条指令写好 CLAUDE.md，让 Claude 记住你的偏好不再从零开始

Every new Claude session starts with zero memory, forcing you to re-explain preferences and correct the same mistakes. CLAUDE.md is a persistent instruction file that Claude automatically reads, providing context, voice, and behavioral rules from the very first message. This guide presents 21 practical instructions grouped into communication style, behavior constraints, personal context, session memory, and developer-specific safeguards. Each instruction includes the rationale and a ready-to-use snippet. By creating a CLAUDE.md file with even a few of these rules, you can dramatically improve output consistency and save hours each week. Ideal for engineers, writers, and anyone who uses Claude professionally.

x.com · 15 min · AI · LLM
06:00

The Kimi K2.6 Blueprint: One-Person Agency at $80k/Month

Kimi K2.6 代理蓝图：一人团队的 8 万美元月收入公式

This thread presents a blueprint for a one-person AI agency using Kimi K2.6, claiming to replace an entire dev team. It details the model's MoE architecture (1T params, 32B activated), SWE-Bench score of 65.8, and the Agent Swarm that runs 300 sub-agents in parallel. It also covers the tech stack (Kimi API, CLI, Swarm, MCP servers, n8n), service offerings (lead gen, knowledge bases, support automation), pricing, client acquisition via job listing monitoring, and a cost model projecting $500/month overhead and $72k+ monthly profit. The content leans heavily promotional, with unverified revenue figures.

x.com · 7 min · Agents · AI · LLM
06:00

The third era of AI software development

Cursor 踏入 AI 编程第三纪元：云端 Agent 独立作业，内部 35% PR 来自机器

Cursor reflects on three eras of AI-assisted coding: from Tab autocomplete, to synchronous agents, to cloud agents autonomously handling hour-long tasks. Internally, 35% of merged PRs now come from these agents, and agent users have surpassed Tab users. The developer's role shifts to problem definition, setting review criteria, and parallel orchestration. Agents return reviewable artifacts—logs, videos, previews—rather than diffs.

x.com · 4 min · Agents · AI