PlayAgit / Notes for builders
Build. Play. Explore.
A technology blog covering game development, AI, automation, and industry news — notes from what we actually build and run.
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Docker Announces AI, Security and Development Sessions at WeAreDevelopers
Docker announces partner and customer sessions on practical AI, security and development at WeAreDevelopers, plus opportunities to connect with featured teams.
Latest from the workbench
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Google Open-Sourced a Quality Agent and Docker Shipped MicroVMs — the Number Going Stale Inside Agent Memory Is Still a Side Project’s Job
Three announcements this cycle point at the same problem from different angles: what happens to an agent when nobody is watching it.
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The Vision Log, Part 3: Four Wrong Diagnoses Before the Real One
Four diagnoses measured and discarded before the real reason a research pipeline held most of its topics: how its queries were built.
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The Vision Log, Part 0: What Vision Is, and the Wish It Was Built From
An agent that changes its own source code, its six original goals, and the honest standing of each – including the one that does not exist at all.
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One Search, Three Repositories: A Maintainer’s Link List, a Godot Playbook, and a C# Utility Collection You Compile Instead of Read
Search GitHub for “game development resources” and the results do not sort themselves by what they are.
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GPT-6 Astra Game Demos and 119 Operator Runs: What the Records Actually Show
GPT-6 Astra game repositories describe runnable demos. Vision’s 119 operator runs record timing, errors and changes, with an incomplete error breakdown.
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Inside playagit’s GitHub/CodeQL Research Pipeline: Evidence Gaps and Draft Outcomes
playagit’s GitHub/CodeQL research covered 36 runs, 446 claims, and 24 reviewed drafts. Examine the recorded evidence gaps, fixes, and publication outcomes.
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Agentic Delivery Gates and the Publication Count Our Records Do Not Explain
Agentic frameworks document gates and reviews. Playagit’s 166 pipeline runs show recorded decisions and a publication breakdown that does not reconcile.
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Google Research Describes Deep Learning for Mapping Methane Emissions from Space
Google Research describes a deep learning model for mapping global methane emissions from space. Explore the claim and the validation questions it leaves open.
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Grease Pencil Was Built to Draw Inside the 3D Scene, and One Public Project Uses It as a Screen-Space Shading Pass
According to its own repository description, the project a-johanson/blender-screen-space-hatch-lines creates screen-space shading effects in Blender using Grease Pencil version 3 [primary source: the project’s own repository description; the behaviour itself is not independently corroborated here, and no code was run for this article].