<?xml version="1.0" encoding="UTF-8"?>
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  <title>The Edges of the Map</title>
  <subtitle>Essays on intelligence, geography, technology, and the strange places where they overlap.</subtitle>
  <link href="https://bluelensanalytics.com/feed.xml" rel="self"/>
  <link href="https://bluelensanalytics.com/blog/"/>
  <id>https://bluelensanalytics.com/blog/</id>
  <updated>2026-06-29T12:00:00Z</updated>
  <author><name>Christopher L. Coffey</name><uri>https://bluelensanalytics.com/about</uri></author>
  <icon>https://bluelensanalytics.com/images/BlueLens_Analytics_Logo_300x300.png</icon>
  <entry>
    <title>Inference at the Source — Optical</title>
    <link href="https://bluelensanalytics.com/blog/posts/inference-at-the-source-optical.html"/>
    <id>https://bluelensanalytics.com/blog/posts/inference-at-the-source-optical.html</id>
    <published>2026-06-29T12:00:00Z</published>
    <updated>2026-06-29T12:00:00Z</updated>
    <summary>The decade since 2015 did not change optical Earth observation by building better cameras. It built cameras that can be used together. The correction that made them comparable, NASA's Harmonized Landsat and Sentinel-2 product chief among it, became the training data for the foundation models now moving into orbit, where that same correction is hardest to reproduce.</summary>
    <category term="Earth Observation"/>
    <category term="GEOINT"/>
    <category term="Onboard AI"/>
    <category term="Optical Imagery"/>
    <category term="Foundation Models"/>
    <category term="Edge Computing"/>
  </entry>
  <entry>
    <title>It's Getting Hot in Here</title>
    <link href="https://bluelensanalytics.com/blog/posts/hot-in-here.html"/>
    <id>https://bluelensanalytics.com/blog/posts/hot-in-here.html</id>
    <published>2026-06-24T12:00:00Z</published>
    <updated>2026-06-24T12:00:00Z</updated>
    <summary>At eight in the morning, off-grid in the Carolina Sandhills, an electric kettle and a half-built battery bank humbled me with the same lesson a nation's grid learned the hard way in Spain. A morning on hubris, energy storage, timing, and the only honest response to being put back down to scale.</summary>
    <category term="Energy Storage"/>
    <category term="Off-Grid Solar"/>
    <category term="Renewables"/>
    <category term="Grid Resilience"/>
  </entry>
  <entry>
    <title>Sustainable War, Tested on Humans — Ukraine</title>
    <link href="https://bluelensanalytics.com/blog/posts/sustainable-war-tested-on-humans-ukraine.html"/>
    <id>https://bluelensanalytics.com/blog/posts/sustainable-war-tested-on-humans-ukraine.html</id>
    <published>2026-06-21T12:00:00Z</published>
    <updated>2026-06-21T12:00:00Z</updated>
    <summary>The defining output of the war in Ukraine is not a shifted front line but a combat-proven capacity for autonomous lethal force, fielded by the millions and built to finish the kill when the human is gone. The proving ground for a weapon no law governs.</summary>
    <category term="Ukraine"/>
    <category term="Conflict Analysis"/>
    <category term="GEOINT"/>
    <category term="Autonomous Weapons"/>
    <category term="Geopolitics"/>
  </entry>
  <entry>
    <title>Sustainable War, Tested on Humans — Haiti</title>
    <link href="https://bluelensanalytics.com/blog/posts/sustainable-war-tested-on-humans.html"/>
    <id>https://bluelensanalytics.com/blog/posts/sustainable-war-tested-on-humans.html</id>
    <published>2026-06-17T12:00:00Z</published>
    <updated>2026-06-17T12:00:00Z</updated>
    <summary>By early 2026, the forces deployed to protect Haiti's population had become the leading cause of casualties among it. War reorganized as a self-financing enterprise.</summary>
    <category term="Haiti"/>
    <category term="Conflict Analysis"/>
    <category term="GEOINT"/>
    <category term="PMC"/>
    <category term="Geopolitics"/>
  </entry>
  <entry>
    <title>The Robot War That Never Happened</title>
    <link href="https://bluelensanalytics.com/blog/posts/robot-war-that-never-happened.html"/>
    <id>https://bluelensanalytics.com/blog/posts/robot-war-that-never-happened.html</id>
    <published>2026-06-15T12:00:00Z</published>
    <updated>2026-06-15T12:00:00Z</updated>
    <summary>A fictional graduate paper imagined from 2035. AI won the economy and lost the culture, and every quote, survey, and source here is invented.</summary>
    <category term="AI"/>
    <category term="Speculative"/>
    <category term="Society"/>
    <category term="Trust"/>
    <category term="Philosophy"/>
  </entry>
  <entry>
    <title>What the Hammer Truss Knows</title>
    <link href="https://bluelensanalytics.com/blog/posts/what-the-hammer-truss-knows.html"/>
    <id>https://bluelensanalytics.com/blog/posts/what-the-hammer-truss-knows.html</id>
    <published>2026-06-12T12:00:00Z</published>
    <updated>2026-06-12T12:00:00Z</updated>
    <summary>There is a white oak on my property in the Sandhills of North Carolina that is becoming a roof. A medieval roof structure carrying a photovoltaic array, and a better framework for AI architecture than most of what is getting published.</summary>
    <category term="AI"/>
    <category term="Systems Architecture"/>
    <category term="Software Design"/>
    <category term="Craft"/>
    <category term="AURORA"/>
    <category term="SAR"/>
  </entry>
  <entry>
    <title>Inference at the Source</title>
    <link href="https://bluelensanalytics.com/blog/posts/inference-at-the-source.html"/>
    <id>https://bluelensanalytics.com/blog/posts/inference-at-the-source.html</id>
    <published>2026-06-01T12:00:00Z</published>
    <updated>2026-06-01T12:00:00Z</updated>
    <summary>Between 2019 and 2026 the Earth observation pipeline broke its decades-old shape. Inference moved off the ground and onto the spacecraft, and the field's defining unsolved problem is no longer whether a model can run in orbit, but whether its output can be trusted once it lands.</summary>
    <category term="Onboard AI"/>
    <category term="SAR"/>
    <category term="Earth Observation"/>
    <category term="GEOINT"/>
    <category term="Orbital Edge Computing"/>
  </entry>
  <entry>
    <title>Consultant in the Next Room</title>
    <link href="https://bluelensanalytics.com/blog/posts/consultant-in-the-next-room.html"/>
    <id>https://bluelensanalytics.com/blog/posts/consultant-in-the-next-room.html</id>
    <published>2026-05-23T12:00:00Z</published>
    <updated>2026-05-23T12:00:00Z</updated>
    <summary>Two years of real workflow. The consultant pattern, the air gap, and why the discipline that worked in 2024 still holds.</summary>
    <category term="GIS"/>
    <category term="LLMs"/>
    <category term="PyQGIS"/>
    <category term="SAR"/>
    <category term="Remote Sensing"/>
  </entry>
  <entry>
    <title>AI Needs a Theory of Mind, Not Just More Compute</title>
    <link href="https://bluelensanalytics.com/blog/posts/ai-needs-a-theory-of-mind.html"/>
    <id>https://bluelensanalytics.com/blog/posts/ai-needs-a-theory-of-mind.html</id>
    <published>2026-05-18T12:00:00Z</published>
    <updated>2026-05-18T12:00:00Z</updated>
    <summary>AI systems can only process the world through structures already imposed on it. That is where Kant becomes unexpectedly useful.</summary>
    <category term="AI"/>
    <category term="Philosophy"/>
    <category term="Epistemology"/>
    <category term="Alignment"/>
  </entry>
  <entry>
    <title>The Model Triages. The Analyst Still Decides.</title>
    <link href="https://bluelensanalytics.com/blog/posts/model-triages-analyst-still-decides.html"/>
    <id>https://bluelensanalytics.com/blog/posts/model-triages-analyst-still-decides.html</id>
    <published>2026-05-14T12:00:00Z</published>
    <updated>2026-05-14T12:00:00Z</updated>
    <summary>The standard pitch in geospatial AI right now is some version of 'deep learning makes your analysts more efficient.' After 30+ years of looking at imagery, I think the framing is off.</summary>
    <category term="AI"/>
    <category term="GEOINT"/>
    <category term="Deep Learning"/>
    <category term="Computer Vision"/>
    <category term="Human in the Loop"/>
  </entry>
  <entry>
    <title>Diogenes, Plato, and Chicken Hurling</title>
    <link href="https://bluelensanalytics.com/blog/posts/diogenes-plato-chicken-hurling.html"/>
    <id>https://bluelensanalytics.com/blog/posts/diogenes-plato-chicken-hurling.html</id>
    <published>2026-05-10T12:00:00Z</published>
    <updated>2026-05-10T12:00:00Z</updated>
    <summary>In the last piece I closed with a line about Diogenes throwing a plucked chicken at Plato. It was a throwaway image, but it has been sitting with me since.</summary>
    <category term="AI"/>
    <category term="LLMs"/>
    <category term="Philosophy"/>
    <category term="Human in the Loop"/>
    <category term="AI Alignment"/>
    <category term="Red Teaming"/>
  </entry>
  <entry>
    <title>Sycophantic AI and The Smiths</title>
    <link href="https://bluelensanalytics.com/blog/posts/sycophantic-ai-and-the-smiths.html"/>
    <id>https://bluelensanalytics.com/blog/posts/sycophantic-ai-and-the-smiths.html</id>
    <published>2026-05-08T12:00:00Z</published>
    <updated>2026-05-08T12:00:00Z</updated>
    <summary>Yesterday I wrote a piece called AI Isn't Just Computer Science, arguing that frontier AI systems are quietly pulling older disciplines back into the conversation. A friend picked it up and turned a quiet blog post into something more interesting.</summary>
    <category term="AI"/>
    <category term="Machine Learning"/>
    <category term="LLMs"/>
    <category term="Responsible AI"/>
    <category term="AI Alignment"/>
    <category term="RLHF"/>
    <category term="Philosophy of AI"/>
  </entry>
  <entry>
    <title>AI Isn't Just Computer Science…</title>
    <link href="https://bluelensanalytics.com/blog/posts/ai-isnt-just-computer-science.html"/>
    <id>https://bluelensanalytics.com/blog/posts/ai-isnt-just-computer-science.html</id>
    <published>2026-05-07T12:00:00Z</published>
    <updated>2026-05-07T12:00:00Z</updated>
    <summary>Over the past few weeks, while reviewing work around IRAC-style legal reasoning frameworks for AI systems, I kept finding myself thinking about something larger.</summary>
    <category term="AI"/>
    <category term="Machine Learning"/>
    <category term="Philosophy of AI"/>
    <category term="Legal Reasoning"/>
    <category term="Library Science"/>
    <category term="Engineering Leadership"/>
  </entry>
  <entry>
    <title>Building a Production SAR Pipeline with ESA SNAP</title>
    <link href="https://bluelensanalytics.com/blog/posts/building-production-sar-pipeline-snap.html"/>
    <id>https://bluelensanalytics.com/blog/posts/building-production-sar-pipeline-snap.html</id>
    <published>2026-04-06T12:00:00Z</published>
    <updated>2026-04-06T12:00:00Z</updated>
    <summary>I've been running ESA SNAP as my primary SAR preprocessing engine for some time now. Not as an academic exercise but as the actual workhorse of production pipelines I deliver to clients.</summary>
    <category term="SAR"/>
    <category term="ESA Sentinel"/>
    <category term="Copernicus"/>
    <category term="SNAP"/>
    <category term="GEOINT"/>
    <category term="Remote Sensing"/>
    <category term="Python"/>
  </entry>
  <entry>
    <title>The Honest Case for Large Language Models in GIS Workflows (And Where They Will Absolutely Burn You)</title>
    <link href="https://bluelensanalytics.com/blog/posts/honest-case-llms-gis-workflows.html"/>
    <id>https://bluelensanalytics.com/blog/posts/honest-case-llms-gis-workflows.html</id>
    <published>2026-03-26T12:00:00Z</published>
    <updated>2026-03-26T12:00:00Z</updated>
    <summary>I've been doing geospatial work for over thirty years. The last several have involved serious integration of large language models into professional GIS workflows. Not as a curiosity. As a practical tool I rely on at BlueLens Analytics.</summary>
    <category term="LLMs"/>
    <category term="GIS"/>
    <category term="GeoPandas"/>
    <category term="PyQGIS"/>
    <category term="Workflow Design"/>
    <category term="GEOINT"/>
    <category term="Python"/>
  </entry>
  <entry>
    <title>Why BlueLens Analytics Runs Entirely on Open-Source Tools, and Why That's Not Going to Change</title>
    <link href="https://bluelensanalytics.com/blog/posts/independent-by-design.html"/>
    <id>https://bluelensanalytics.com/blog/posts/independent-by-design.html</id>
    <published>2026-03-23T12:00:00Z</published>
    <updated>2026-03-23T12:00:00Z</updated>
    <summary>Back in 2015, I was making the case inside NGA for QGIS. The argument I kept making was simple: the tools are as good, the data doesn't care what software reads it, and dependency on a single commercial vendor is a strategic liability.</summary>
    <category term="Open Source"/>
    <category term="QGIS"/>
    <category term="PostGIS"/>
    <category term="ESA Copernicus"/>
    <category term="Sentinel-1"/>
    <category term="GEOINT"/>
    <category term="Cost Engineering"/>
  </entry>
  <entry>
    <title>Seeing Through the Storm</title>
    <link href="https://bluelensanalytics.com/blog/posts/seeing-through-the-storm.html"/>
    <id>https://bluelensanalytics.com/blog/posts/seeing-through-the-storm.html</id>
    <published>2026-03-23T12:00:00Z</published>
    <updated>2026-03-23T12:00:00Z</updated>
    <summary>How synthetic aperture radar and a fully open-source processing pipeline are changing disaster response, and what Hurricane Helene revealed about the gap between data availability and data use.</summary>
    <category term="SAR"/>
    <category term="Sentinel-1"/>
    <category term="Disaster Response"/>
    <category term="Hurricane Helene"/>
    <category term="Open-Source GIS"/>
    <category term="SNAP"/>
    <category term="pyroSAR"/>
    <category term="QGIS"/>
  </entry>
</feed>
