Topic: Applications
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The AI Compute Stack: Why Chips Decide the Race
AI capability is downstream of hardware. Understanding the compute stack — accelerators, memory, packaging, power — explains most of the industry’s strategic…
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Tool Use and MCP: How AI Connects to the Real World
Tool use is how a model stops merely talking and starts doing. MCP is the standard that stopped every integration from being…
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Fine-Tuning vs RAG vs Prompting: Choosing the Right Approach
Three ways to make a model do what you want, routinely confused with each other. The deciding question is whether your problem…
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RAG Explained: Giving AI Access to Knowledge It Was Never Trained On
Retrieval-augmented generation looks up relevant information and hands it to the model at question time. Large context windows were supposed to kill…
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AI Agents Explained: What They Are and What They Can Actually Do
An agent is a model given tools and a goal, running in a loop until the job is done. The honest picture…
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ChatGPT released
The interface, not the model, is what changed public understanding of what these systems could do.
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Agents reach production
Narrow, verifiable agent workflows begin shipping in enterprise software.
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Agents move from demos to workflows
Enterprise deployments of AI agents are shifting from pilots to production, concentrated in narrow, well-instrumented tasks rather than general assistance.