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// GLAD LABS · AI / HARDWARE / GAMING
Explore the frontier.
Deep dives into AI, hardware, and the edges where they meet. Locally-published, human-reviewed, free to read.
Automating AI Content Workflows
Most AI content tools follow a predictable pattern: they take a prompt, generate a wall of mediocre text, and call it "automation." For solo operators and indie publishers, this isn't helpful.
// GLAD LABS · RECENT
Recent posts.
Qwen3-VL Integration Gotchas
If you are integrating vision-language models into an automated pipeline, you've likely seen the specs for the Qwen family. Between the…
The Operational Cost of Manual Content
Most discussions about AI content focus on speed or creativity. They miss the actual operational bottleneck: the human loop. Traditional…
Single-GPU VRAM Budgeting and Stability
If you are running local LLMs, you know that VRAM is the only currency that matters. Whether you're on an RTX 3090 or the newer RTX 5090,…
Preventing Schema Drift in CI Pipelines
You know the feeling: a deployment goes through without a single error in the logs. Your dashboards are green. But then you notice your…
Resolving GlitchTip Memory Allocation Errors
When your error tracking starts throwing its own errors, you have a problem. We recently encountered a series of stability issues with our…
Why KV Cache Quantization Matters for Long-Context LLM Inference on Consumer GPUs
If you have tried running LLMs locally, you know that VRAM is the only currency that matters. Whether you are using an RTX 3090 or a newer…
// GLAD LABS · ARCHIVE
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