<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>Deepractice Blog</title>
    <link>https://deepractice.ai</link>
    <description>Exploring AI engineering, prompt engineering, and cognitive systems</description>
    <language>en-US</language>
    <lastBuildDate>Fri, 12 Jun 2026 16:02:00 GMT</lastBuildDate>
    <atom:link href="https://deepractice.ai/feed-en.xml" rel="self" type="application/rss+xml"/>
    
    <item>
      <title><![CDATA[Deepractice Agent Cloud Production Function]]></title>
      <link>https://deepractice.ai/en/blog/agent-cloud-production-function/</link>
      <guid isPermaLink="true">https://deepractice.ai/en/blog/agent-cloud-production-function/</guid>
      <description><![CDATA[How much value can you get from investing in AI? Based on a Yale University paper, we propose a new production function framework for measuring AaaS (Agent as a Service) value. The 2025 market reality: value creation is shifting from the model layer to the agent layer.]]></description>
      <pubDate>Sat, 03 Jan 2026 00:00:00 GMT</pubDate>
      <category>Frontier Insights</category>
      <category>Business</category>
    </item>
    <item>
      <title><![CDATA[The Hidden Variable in T2V Velocity: Realization Probability]]></title>
      <link>https://deepractice.ai/en/blog/t2v-velocity-certainty/</link>
      <guid isPermaLink="true">https://deepractice.ai/en/blog/t2v-velocity-certainty/</guid>
      <description><![CDATA[Sean's T2V Velocity formula precisely captures the fundamental contradiction in AI commercialization, but it might be missing a key variable—realization probability. Programmers aren't unwilling to pay; they're uncertain what 100k tokens will ultimately deliver.]]></description>
      <pubDate>Sat, 03 Jan 2026 00:00:00 GMT</pubDate>
      <category>Frontier Insights</category>
      <category>Business</category>
    </item>
    <item>
      <title><![CDATA[T2V Velocity: An AI-Native Business Metric]]></title>
      <link>https://deepractice.ai/en/blog/t2v-velocity/</link>
      <guid isPermaLink="true">https://deepractice.ai/en/blog/t2v-velocity/</guid>
      <description><![CDATA[Token consumption ≠ business value. The T2V of a viral short video is 160,000x that of code refactoring. This isn't a decimal point difference—it's a business model difference. Customers don't pay for tokens; they pay for closed loops.]]></description>
      <pubDate>Fri, 02 Jan 2026 00:00:00 GMT</pubDate>
      <category>Frontier Insights</category>
      <category>Business</category>
    </item>
    <item>
      <title><![CDATA[Why the Best Interface in the AI Era Is No Interface]]></title>
      <link>https://deepractice.ai/en/blog/no-interface/</link>
      <guid isPermaLink="true">https://deepractice.ai/en/blog/no-interface/</guid>
      <description><![CDATA[In the AI era, the best interface is no interface. It's not about humans learning machine language, but machines understanding human intent. This isn't just a technology trend—it's a redefinition of human-machine relationships.]]></description>
      <pubDate>Mon, 06 Oct 2025 00:00:00 GMT</pubDate>
      <category>Product Thinking</category>
    </item>
    <item>
      <title><![CDATA[Why Your AI Collaboration Keeps Going Off Track: Redesigning AI Tasks with State Machines]]></title>
      <link>https://deepractice.ai/en/blog/ai-task-state-machine/</link>
      <guid isPermaLink="true">https://deepractice.ai/en/blog/ai-task-state-machine/</guid>
      <description><![CDATA[Redesign AI collaboration using state machine thinking. By defining initial state, target state, context space, and 5 core elements, solve AI task problems like context loss, goal drift, and verification failures. Transform AI collaboration from luck-based to predictable.]]></description>
      <pubDate>Wed, 01 Oct 2025 00:00:00 GMT</pubDate>
      <category>Engineering Practice</category>
    </item>
    <item>
      <title><![CDATA[Hierarchical Architecture of Cognitive Systems: From Memory to the Emergence of Consciousness]]></title>
      <link>https://deepractice.ai/en/blog/cognitive-hierarchy/</link>
      <guid isPermaLink="true">https://deepractice.ai/en/blog/cognitive-hierarchy/</guid>
      <description><![CDATA[Starting from the code design of the Monogent cognitive system, exploring the nature of memory, emotion, and consciousness. Intelligence isn't a program running in the brain—it's the brain's network itself. Understanding intelligence requires not just technical knowledge but cross-disciplinary thinking.]]></description>
      <pubDate>Mon, 22 Sep 2025 00:00:00 GMT</pubDate>
      <category>Cognitive Science</category>
    </item>
    <item>
      <title><![CDATA[Why Should We Learn from Human Cognitive Systems?]]></title>
      <link>https://deepractice.ai/en/blog/learning-from-human-cognition/</link>
      <guid isPermaLink="true">https://deepractice.ai/en/blog/learning-from-human-cognition/</guid>
      <description><![CDATA[Exploring why human cognitive systems are the ideal reference for building AI individual cognitive systems. From functional, testing, and implementation perspectives, we analyze how to systematically construct AI cognitive systems through structural analysis, functional mapping, and gap benchmarking.]]></description>
      <pubDate>Fri, 25 Jul 2025 00:00:00 GMT</pubDate>
      <category>Cognitive Science</category>
    </item>
    <item>
      <title><![CDATA[Why Can't Semantics Be Computed?]]></title>
      <link>https://deepractice.ai/en/blog/why-semantics-cannot-be-computed/</link>
      <guid isPermaLink="true">https://deepractice.ai/en/blog/why-semantics-cannot-be-computed/</guid>
      <description><![CDATA[A deep exploration of the philosophical essence of semantic non-computability. Starting from the five key properties of semantics, we argue that experientiality is the core of semantics, and its uniqueness and temporality fundamentally fail to meet Turing computability requirements.]]></description>
      <pubDate>Tue, 22 Jul 2025 00:00:00 GMT</pubDate>
      <category>Cognitive Science</category>
    </item>
    <item>
      <title><![CDATA[Why RAG Isn't All You Need for AI Memory]]></title>
      <link>https://deepractice.ai/en/blog/why-rag-cannot-be-used-for-ai-memory/</link>
      <guid isPermaLink="true">https://deepractice.ai/en/blog/why-rag-cannot-be-used-for-ai-memory/</guid>
      <description><![CDATA[RAG is a retrieval method that sacrifices information precision for broader matching space. This article analyzes why RAG is unsuitable for AI memory from philosophical and technical perspectives, and introduces the Monogent individual cognitive system concept.]]></description>
      <pubDate>Sun, 20 Jul 2025 00:00:00 GMT</pubDate>
      <category>Cognitive Science</category>
    </item>
    <item>
      <title><![CDATA[Solving MCP's Project Path Problem: An AI-Driven Environment Management Approach]]></title>
      <link>https://deepractice.ai/en/blog/mcp-environment-positioning/</link>
      <guid isPermaLink="true">https://deepractice.ai/en/blog/mcp-environment-positioning/</guid>
      <description><![CDATA[MCP ecosystem faces a critical challenge: project path detection. This article introduces an innovative AI-driven solution that achieves 100% accurate project environment positioning by shifting from system guessing to AI-informed path management.]]></description>
      <pubDate>Thu, 26 Jun 2025 00:00:00 GMT</pubDate>
      <category>Engineering</category>
    </item>
    <item>
      <title><![CDATA[CDT: A Cross-Dimensional Terminology Method for Precise AI Prompt Engineering]]></title>
      <link>https://deepractice.ai/en/blog/cross-dimensional-terminology/</link>
      <guid isPermaLink="true">https://deepractice.ai/en/blog/cross-dimensional-terminology/</guid>
      <description><![CDATA[CDT (Cross-Dimensional Terminology) is a systematic approach to defining AI prompts through cross-cultural, cross-temporal, and cross-domain validation. Learn how to dramatically improve AI comprehension accuracy by eliminating ambiguity in your prompts.]]></description>
      <pubDate>Thu, 24 Apr 2025 00:00:00 GMT</pubDate>
      <category>Engineering</category>
    </item>
    <item>
      <title><![CDATA[AI's 'Memory Fragments': Exploring the Amnesia Problem in Large Language Models]]></title>
      <link>https://deepractice.ai/en/blog/ai-memory-fragments/</link>
      <guid isPermaLink="true">https://deepractice.ai/en/blog/ai-memory-fragments/</guid>
      <description><![CDATA[A deep dive into the memory fragmentation problem in large language models. From static keys to dynamic algorithms to meta-information embedding mechanisms, we reveal the nature of AI amnesia and its solutions, inspiring new approaches to AI Agent system design.]]></description>
      <pubDate>Thu, 10 Apr 2025 00:00:00 GMT</pubDate>
      <category>Cognitive Science</category>
    </item>
    <item>
      <title><![CDATA[OES Framework: A Docker-Inspired Approach to AI Workflow Management]]></title>
      <link>https://deepractice.ai/en/blog/oes-framework/</link>
      <guid isPermaLink="true">https://deepractice.ai/en/blog/oes-framework/</guid>
      <description><![CDATA[OES (Objective-Environment-Success Criteria) is a containerized framework for AI workflows. Learn how to prevent task drift, context loss, and inconsistent outputs by structuring AI tasks like Docker containers.]]></description>
      <pubDate>Tue, 08 Apr 2025 00:00:00 GMT</pubDate>
      <category>Engineering</category>
    </item>
    <item>
      <title><![CDATA[DPML: A Structured Prompt Markup Language for AI Engineering]]></title>
      <link>https://deepractice.ai/en/blog/dpml-design/</link>
      <guid isPermaLink="true">https://deepractice.ai/en/blog/dpml-design/</guid>
      <description><![CDATA[DPML (Deepractice Prompt Markup Language) is an XML-style markup language designed for AI prompt engineering. Learn how to create structured, extensible, and maintainable prompt systems using modular design principles.]]></description>
      <pubDate>Wed, 02 Apr 2025 00:00:00 GMT</pubDate>
      <category>Engineering</category>
    </item>
    <item>
      <title><![CDATA[The Path to AGI: Collective Intelligence Through AI Organization]]></title>
      <link>https://deepractice.ai/en/blog/agi-path-ai-organization/</link>
      <guid isPermaLink="true">https://deepractice.ai/en/blog/agi-path-ai-organization/</guid>
      <description><![CDATA[Exploring a viable path to AGI through AI organization. Instead of creating a single super-intelligent AI, we propose building collective consciousness through organized AI societies—combining management, specialist, reflective, memory, and exploration AI agents.]]></description>
      <pubDate>Mon, 31 Mar 2025 00:00:00 GMT</pubDate>
      <category>Frontier Insights</category>
    </item>
    <item>
      <title><![CDATA[The 4P Theory: A Systematic Framework for AI Engineering]]></title>
      <link>https://deepractice.ai/en/blog/4p-theory/</link>
      <guid isPermaLink="true">https://deepractice.ai/en/blog/4p-theory/</guid>
      <description><![CDATA[The Deepractice 4P Theory provides a complete value chain from abstract patterns to deployed products. Learn how to bridge the gap between prompt design patterns and real-world AI applications through four progressive stages.]]></description>
      <pubDate>Mon, 24 Mar 2025 00:00:00 GMT</pubDate>
      <category>Frontier Insights</category>
    </item>
    <item>
      <title><![CDATA[Prompt Design Patterns: From Cognitive Framework to Practical System]]></title>
      <link>https://deepractice.ai/en/blog/prompt-design-patterns/</link>
      <guid isPermaLink="true">https://deepractice.ai/en/blog/prompt-design-patterns/</guid>
      <description><![CDATA[Move beyond traditional prompt engineering with a comprehensive intelligent interaction system. Learn ten core prompt types (RRP, PDP, ESP, TMP, TVP, KTP, and more) and how to combine them for production-ready AI applications.]]></description>
      <pubDate>Sun, 23 Mar 2025 00:00:00 GMT</pubDate>
      <category>Frontier Insights</category>
    </item>
    <item>
      <title><![CDATA[The Cognitive Prompt Paradigm: A Seven-Dimensional Framework for AI Interaction]]></title>
      <link>https://deepractice.ai/en/blog/cognitive-prompt-paradigm/</link>
      <guid isPermaLink="true">https://deepractice.ai/en/blog/cognitive-prompt-paradigm/</guid>
      <description><![CDATA[Master AI interaction through a systematic seven-dimensional prompt framework. Learn how to combine Role Responsibility, Protocol Description, Execute Specification, and other prompt types to build professional, precise, and adaptive AI assistants.]]></description>
      <pubDate>Thu, 20 Mar 2025 00:00:00 GMT</pubDate>
      <category>Frontier Insights</category>
    </item>
  </channel>
</rss>