Early-adopter costs on the DGX Spark
The DGX Spark offers a huge shared-memory workspace, but early adoption comes with missing dependencies, difficult setup and a stubborn software ecosystem.
Lynn Cole / Writing
Essays, thoughts, and technical notes.
The DGX Spark offers a huge shared-memory workspace, but early adoption comes with missing dependencies, difficult setup and a stubborn software ecosystem.
My prediction for local creative computing centers on efficiency: reasoning per gigabyte, better device architecture and smaller models that do more.
An early Antigravity review of limits, model behavior, coding competence and the difference between implementation and brainstorming.
The internet has changed from an information network into an advertising machine. I see a return toward lighter interfaces and an agent-mediated network.
Five years of building coding agents led from GPT-2 experiments through Klara to modern tools. Human intent and engineering discipline still shape the result.
A November 2025 field report on coding agents, their costs, failure modes and the tool I chose as my daily driver.
System prompts frame the exercise. Put instructions and context where their roles remain legible, and keep complex tasks small enough to reason through.
A prediction about the economics of AI factories: local models and cheaper edge hardware will eat the cloud.
A week with GLM 4.6 exposed a fluid creative process, strong QA and convincing mocks, alongside loops and destructive summarization.
After waiting for coding tools to improve, I returned to building agents around the memory and repository safety I still wanted.
Learning with AI-assisted generation can be a way into engineering. Build, question the output, document the process and discover what better means.
The high-converting landing page has a recognizable skeleton: reassurance, scarcity, a bigger promise and a murky order form. Here is why the template feels so familiar.