AEC 3D Viewers: What 32 Tools Chose, and a 5x Speed Gap

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Over the past year I built five different 3D viewers for AEC work - routing, structural review, tunnel sections, a Revit perspective tool, a spreadsheet-to-3D viewer. Before I trusted my own instincts about how to build them, I did two things: I profiled all five on the same GPU, and I studied how 32 other AEC 3D tools - Autodesk Forma, Speckle, TestFit, xeokit, Bentley iTwin, and more - solve the same problem. This post is both halves: what the industry chose, and then what my own measurements showed. The short version is that rendering is a commodity, and the interesting decisions are everywhere else. Part 1 - What 32 AEC viewers actually chose I expected a mess of proprietary engines. Instead the choices collapse into six patterns, and the deciding question is never "which renderer is best" - it is "what is our actual moat." Pattern Who Why Outcome A. Off-the-shelf web engine (three.js / Babylon) Forma, Speckle, That Open, VIM, Snaptrude "Rendering is a ...

Parsing 149 GB of JSON Without Loading It Into Memory

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 Part 9 of a series — a Dynamo tunnel geometry that was already finished, a 39-sheet Excel workbook it had never been wired to, the web viewer built to referee the two, and the Revit add-in at the end of it. When the work stopped, it had left 149 GB of snapshots on a desktop drive. The obvious next task was to delete them. This post is about what happened when I tried to establish that deleting them was safe — which turned out to be a longer job than the deletion, and ended with a different answer than the one I started with. What 45 days physically left behind Part of what 45 days left behind: the reference images pulled out of the workbook, on one contact sheet with each source size printed underneath. 57 MB of this, against 149 GB of snapshots. A single verification artefact: source tunnel section with the production candidate drawn over it, and the raw scale conflict stated in the header. Hundreds of files like this one are what the reports directory actually is. Fi...

AI Clarifying Questions: A Template From Seven Real Ones

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 Part 8 of a series — a Dynamo tunnel geometry that was already finished, a 39-sheet Excel workbook it had never been wired to, the web viewer built to referee the two, and the Revit add-in at the end of it. On 14 July the AI stopped guessing and wrote a list of things it could not decide. Seven questions, thirteen evidence crops, one document. The answers came back the same night, and one of them — a single sentence about a block of concrete nobody had bothered to name — collapsed three other questions and cleared a month of round trips before dawn. Part 4 summarised those seven questions in a table. That table is the most compressed thing in the whole series, and compression hid the interesting part. The answer to Q2 did not arrive because the engineer suddenly became more forthcoming. It arrived because the question had a shape that made it cheap to answer. This part goes through all seven — the wording, the interim handling, why the machine could not settle it alone, what ...