Why AI needs real infrastructure 🏗️
Article summary
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We are all fixated on large language models and autonomous agents right now. But code sitting in a repository is not an actual application. The real engineering grind is figuring out what runs these applications when the volume of code increases by orders of magnitude. Here is what we need to consider: Models are just the catalyst that shows what is possible. Applications require hosting, routing, databases, and deployment pipelines to function. Sprawling and manually configured infrastructure…
1Key Takeaways
- We are all fixated on large language models and autonomous agents right now.
- But code sitting in a repository is not an actual application.
- The real engineering grind is figuring out what runs these applications when the volume of code increases by orders of magnitude.
- Here is what we need to consider: Models are just the catalyst that shows what is possible.
2AIWedia Score
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — AI reports that we are all fixated on large language models and autonomous agents right now.
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