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    <title>Dmitry Shteyn — Blog</title>
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    <description>Articles on AI, digital health, and performance marketing from Dmitry Shteyn.</description>
    <language>en-US</language>
    <lastBuildDate>Fri, 21 Aug 2026 20:46:30 GMT</lastBuildDate>
    <item>
      <title>Architecting State Management for Multi-Agent Enterprise Workflows</title>
      <link>https://dmitryshteyn.com/blog/architecting-state-management-multi-agent-workflows</link>
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      <pubDate>Fri, 21 Aug 2026 20:24:01 GMT</pubDate>
      <description>Discover how decoupling logic from memory and treating agents as stateless microservices prevents context loss and scales enterprise automation.</description>
      <author>noreply@dmitryshteyn.com (Dmitry Shteyn)</author>
      <category>Agentic AI</category>
      <category>Enterprise Architecture</category>
      <category>Operations</category>
      <category>Data Infrastructure</category>
    </item>
    <item>
      <title>Building Automated Competitive Intelligence Data Pipelines</title>
      <link>https://dmitryshteyn.com/blog/automated-competitive-intelligence-data-pipelines</link>
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      <pubDate>Wed, 05 Aug 2026 14:00:03 GMT</pubDate>
      <description>Learn how to replace brittle web scrapers with agentic data pipelines that turn competitor website changes into immediate revenue counter strategies.</description>
      <author>noreply@dmitryshteyn.com (Dmitry Shteyn)</author>
      <category>Competitive Intelligence</category>
      <category>Data Pipelines</category>
      <category>Revenue Operations</category>
      <category>AI Architecture</category>
    </item>
    <item>
      <title>Building Auditable Automation Pipelines for Legal Operations</title>
      <link>https://dmitryshteyn.com/blog/auditable-automation-pipelines-legal-operations</link>
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      <pubDate>Mon, 03 Aug 2026 14:00:03 GMT</pubDate>
      <description>How operators can architect structured data extraction frameworks to handle high volume compliance and contract discovery safely.</description>
      <author>noreply@dmitryshteyn.com (Dmitry Shteyn)</author>
      <category>Legal Tech</category>
      <category>Operations</category>
      <category>Data Pipelines</category>
      <category>AI Architecture</category>
    </item>
    <item>
      <title>Architecting First Party Data Pipelines for Performance Media</title>
      <link>https://dmitryshteyn.com/blog/first-party-data-pipelines-media-architecture</link>
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      <pubDate>Sat, 01 Aug 2026 14:00:05 GMT</pubDate>
      <description>When internal ad platforms lose transaction visibility, customer acquisition costs spike. Here is how to engineer scalable server side conversion pipelines.</description>
      <author>noreply@dmitryshteyn.com (Dmitry Shteyn)</author>
      <category>Marketing Operations</category>
      <category>Data Engineering</category>
      <category>Paid Media</category>
      <category>Infrastructure</category>
    </item>
    <item>
      <title>Deploying In-Location Media Networks and Out of Home Screen Operations</title>
      <link>https://dmitryshteyn.com/blog/deploying-in-location-media-operations</link>
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      <pubDate>Thu, 30 Jul 2026 14:00:01 GMT</pubDate>
      <description>Scaling physical screen networks requires bridging programmatic ad servers with highly localized hardware environments to ensure flawless media execution.</description>
      <author>noreply@dmitryshteyn.com (Dmitry Shteyn)</author>
    </item>
    <item>
      <title>Architecting Telehealth Operations: The Infrastructure of Geographic Scale</title>
      <link>https://dmitryshteyn.com/blog/architecting-telehealth-operations-geographic-scale</link>
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      <pubDate>Tue, 28 Jul 2026 14:00:02 GMT</pubDate>
      <description>Scaling a digital health platform requires treating patient care like a high availability routing problem constrained by strict state regulations.</description>
      <author>noreply@dmitryshteyn.com (Dmitry Shteyn)</author>
      <category>Telehealth</category>
      <category>Digital Health</category>
      <category>Operations</category>
      <category>Healthcare Tech</category>
    </item>
    <item>
      <title>The Mechanics of B2B Channel Operations: Building Partner Ecosystems That Scale</title>
      <link>https://dmitryshteyn.com/blog/b2b-channel-operations-partner-ecosystems</link>
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      <pubDate>Sun, 26 Jul 2026 14:00:04 GMT</pubDate>
      <description>Most B2B channel programs devolve into dormant lists. Here is how rigorous operators build internal structures to drive predictable indirect revenue.</description>
      <author>noreply@dmitryshteyn.com (Dmitry Shteyn)</author>
      <category>Channel Sales</category>
      <category>B2B Ecosystems</category>
      <category>Revenue Operations</category>
      <category>SaaS</category>
    </item>
    <item>
      <title>AI and the Future of Work in 2026: What the Data Actually Says About Jobs, Automation, and the Skills That Remain Valuable</title>
      <link>https://dmitryshteyn.com/blog/ai-future-of-work-2026</link>
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      <pubDate>Sat, 04 Jul 2026 14:00:03 GMT</pubDate>
      <description>The debate about whether AI will eliminate jobs or create them has been running for at least a decade. In 2026, the answer is clearly both, but not symmetrically, not at the same pace, and not for the same people.</description>
      <author>noreply@dmitryshteyn.com (Dmitry Shteyn)</author>
      <category>AI</category>
      <category>Future of Work</category>
      <category>Workforce</category>
      <category>2026</category>
    </item>
    <item>
      <title>Open Source AI in 2026: How Free Models Are Closing the Gap with Proprietary Giants</title>
      <link>https://dmitryshteyn.com/blog/open-source-ai-2026</link>
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      <pubDate>Fri, 03 Jul 2026 14:00:02 GMT</pubDate>
      <description>For most of the generative AI era, the choice between open source and proprietary AI was not really a choice. Closed models from OpenAI, Anthropic, and Google were dramatically more capable than any open-weight alternative. Organizations that needed serious AI capability used...</description>
      <author>noreply@dmitryshteyn.com (Dmitry Shteyn)</author>
      <category>Open Source</category>
      <category>AI</category>
      <category>LLMs</category>
      <category>Enterprise</category>
      <category>2026</category>
    </item>
    <item>
      <title>AI and Cybersecurity in 2026: How Artificial Intelligence Is Both the Threat and the Defense</title>
      <link>https://dmitryshteyn.com/blog/ai-cybersecurity-2026</link>
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      <pubDate>Thu, 02 Jul 2026 14:00:02 GMT</pubDate>
      <description>Cybersecurity has always been an arms race. Attackers find new methods, defenders build countermeasures, attackers adapt. In 2026, AI has accelerated every part of that cycle simultaneously, but it has not done so symmetrically. Attackers have adopted AI faster than many defen...</description>
      <author>noreply@dmitryshteyn.com (Dmitry Shteyn)</author>
      <category>AI</category>
      <category>Cybersecurity</category>
      <category>Deepfakes</category>
      <category>2026</category>
    </item>
    <item>
      <title>AI in Healthcare 2026: How Artificial Intelligence Is Transforming Patient Care and Clinical Operations</title>
      <link>https://dmitryshteyn.com/blog/ai-in-healthcare-2026</link>
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      <pubDate>Wed, 01 Jul 2026 14:00:03 GMT</pubDate>
      <description>For much of the last decade, AI in healthcare was a story about promise. Research papers showed AI matching radiologists at reading scans. Startups demoed clinical decision support tools. Health systems ran pilots. Very little reached patients at scale.</description>
      <author>noreply@dmitryshteyn.com (Dmitry Shteyn)</author>
      <category>AI</category>
      <category>Healthcare</category>
      <category>Clinical</category>
      <category>2026</category>
    </item>
    <item>
      <title>AI Reasoning Models in 2026: How Slow-Thinking AI Is Solving Problems That Fast AI Cannot</title>
      <link>https://dmitryshteyn.com/blog/ai-reasoning-models-2026</link>
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      <pubDate>Tue, 30 Jun 2026 14:00:02 GMT</pubDate>
      <description>From 2022 to 2024, the dominant AI paradigm was fast response. Models like GPT-4 and Claude 3 were trained to generate answers quickly, pattern-matching against vast training corpora to produce fluent, contextually appropriate text in seconds. That capability was genuinely tra...</description>
      <author>noreply@dmitryshteyn.com (Dmitry Shteyn)</author>
      <category>AI</category>
      <category>Reasoning Models</category>
      <category>LLMs</category>
      <category>2026</category>
    </item>
    <item>
      <title>Multimodal AI in 2026: How Text, Image, Video, and Audio Are Converging Into One Powerful Platform</title>
      <link>https://dmitryshteyn.com/blog/multimodal-ai-2026</link>
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      <pubDate>Mon, 29 Jun 2026 14:00:02 GMT</pubDate>
      <description>For the first three years of the generative AI era, most business applications were built around text. Language models generated copy, summarized documents, answered questions, and wrote code. Images were a separate capability. Video was another. Audio was another still. Organ...</description>
      <author>noreply@dmitryshteyn.com (Dmitry Shteyn)</author>
      <category>Multimodal AI</category>
      <category>Video AI</category>
      <category>Generative AI</category>
      <category>2026</category>
    </item>
    <item>
      <title>AI Agents at Enterprise Scale: How Autonomous AI Is Reshaping How Work Gets Done</title>
      <link>https://dmitryshteyn.com/blog/ai-agents-enterprise-scale-2026</link>
      <guid isPermaLink="true">https://dmitryshteyn.com/blog/ai-agents-enterprise-scale-2026</guid>
      <pubDate>Sun, 28 Jun 2026 14:00:03 GMT</pubDate>
      <description>A year ago, most enterprise conversations about AI agents centered on potential. In 2026, that conversation has shifted decisively toward execution. According to Gartner, 72% of organizations have at least one AI workload in production as of Q1 2026, up from 55% in 2024. Gartn...</description>
      <author>noreply@dmitryshteyn.com (Dmitry Shteyn)</author>
      <category>AI Agents</category>
      <category>Enterprise</category>
      <category>Agentic AI</category>
      <category>2026</category>
    </item>
    <item>
      <title>AI Automation in 2026: How Businesses Are Eliminating Bottlenecks and Multiplying Output</title>
      <link>https://dmitryshteyn.com/blog/ai-automation-2026</link>
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      <pubDate>Sat, 27 Jun 2026 14:00:03 GMT</pubDate>
      <description>Business automation is not a new idea. Rule-based robotic process automation has existed for decades, and workflow tools have been part of enterprise tech stacks since the 1990s. But in 2026, AI has fundamentally changed what automation can do, and how quickly it can be deployed.</description>
      <author>noreply@dmitryshteyn.com (Dmitry Shteyn)</author>
      <category>AI</category>
      <category>Automation</category>
      <category>Enterprise</category>
      <category>ROI</category>
      <category>2026</category>
    </item>
    <item>
      <title>AI in Coding 2026: How Artificial Intelligence Is Transforming Software Development</title>
      <link>https://dmitryshteyn.com/blog/ai-in-coding-2026</link>
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      <pubDate>Fri, 26 Jun 2026 14:00:03 GMT</pubDate>
      <description>Ask any working software engineer in 2026 whether they use AI coding tools and you will almost certainly get a yes. According to recent survey data, 84% of developers either use or plan to use AI tools this year, up from 76% in 2024. More than half report using AI daily as par...</description>
      <author>noreply@dmitryshteyn.com (Dmitry Shteyn)</author>
      <category>AI</category>
      <category>Software Development</category>
      <category>Developer Tools</category>
      <category>2026</category>
    </item>
    <item>
      <title>The State of the AI Industry in 2026: Trends, Market Forces, and What Comes Next</title>
      <link>https://dmitryshteyn.com/blog/ai-industry-overview-2026</link>
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      <pubDate>Thu, 25 Jun 2026 04:03:07 GMT</pubDate>
      <description>The artificial intelligence industry in 2026 is no longer a story about potential. It is a story about scale. AI has crossed the threshold from isolated experimentation into embedded infrastructure, as foundational to modern organizations as cloud computing was a decade ago. T...</description>
      <author>noreply@dmitryshteyn.com (Dmitry Shteyn)</author>
      <category>AI</category>
      <category>Industry Trends</category>
      <category>Market Analysis</category>
      <category>2026</category>
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