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AI Era Action Guide
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AI Era Action Guide

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4 recent articles
AI Era Action Guide
AI Era Action Guide
Apr 24, 2026 · Artificial Intelligence

DeepSeek-V4 Launches with 1M Token Context and Leading Open-Source Agent – A Chinese AI Milestone

DeepSeek has unveiled the V4 preview, offering two open‑source large language models—Pro (1.6 T parameters) and Flash (284 B)—both supporting 1 million‑token context, sparse‑attention efficiency gains, top‑ranked Agent capabilities, and competitive reasoning performance, marking a major milestone for Chinese AI.

1M token contextAgentDeepSeek
0 likes · 5 min read
DeepSeek-V4 Launches with 1M Token Context and Leading Open-Source Agent – A Chinese AI Milestone
AI Era Action Guide
AI Era Action Guide
Apr 23, 2026 · Artificial Intelligence

Why Enterprise AI Coding Can’t Be a One‑Person Project

The article explains that while AI tools like Vibe Coding can accelerate code generation, successful enterprise adoption requires multi‑role collaboration, rigorous requirement definition, code review, testing, and ops oversight to avoid security, performance, and responsibility pitfalls.

AIBest PracticesCode Review
0 likes · 14 min read
Why Enterprise AI Coding Can’t Be a One‑Person Project
AI Era Action Guide
AI Era Action Guide
Apr 22, 2026 · Industry Insights

When "Vibe" Becomes a Productivity Force: How Vibe Coding Redefines Software Development

The article explores Vibe Coding—a new AI‑driven human‑machine collaboration paradigm—by recounting a real‑world case, outlining its historical evolution, analyzing three underlying drivers, detailing a three‑step workflow, showcasing diverse use cases, recommending tools, and forecasting its impact on software development and the tech industry.

AI programmingLow‑codeVibe Coding
0 likes · 13 min read
When "Vibe" Becomes a Productivity Force: How Vibe Coding Redefines Software Development
AI Era Action Guide
AI Era Action Guide
Apr 21, 2026 · Industry Insights

How to Use IBM Processing Mining to Uncover Complex Multi‑Agent Collaboration Workflows

The article explains how multi‑agent AI systems create hidden bottlenecks and abnormal paths in customer‑service workflows, demonstrates how IBM Processing Mining automatically discovers end‑to‑end processes, quantifies performance, identifies variants and root causes, and provides concrete optimization steps that deliver measurable business value.

AI workflowIBMbusiness optimization
0 likes · 21 min read
How to Use IBM Processing Mining to Uncover Complex Multi‑Agent Collaboration Workflows