Context Engineering: The Missing Piece in Agentic Systems
Context engineering is becoming essential as AI agents take on more software development work. An agent can plan, code, test, investigate incidents, trigger CI, and help deploy software.
Useful takeaways from this story.
Context engineering is becoming essential as AI agents take on more software development work.
An agent can plan, code, test, investigate incidents, trigger CI, and help deploy software.
Then the agent has to figure out which service we mean, who owns it, what repository it belongs to, whether it is healthy, what incidents are open, and whether a deployment is safe.
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The useful part
Context engineering is becoming essential as AI agents take on more software development work. An agent can plan, code, test, investigate incidents, trigger CI, and help deploy software. Then the agent has to figure out which service we mean, who owns it, what repository it belongs to, whether it is healthy, what incidents are open, and whether a deployment is safe.
How it works
- That is a lot of disconnected information to reconstruct every single time.
Details worth keeping
None of that matters if it is operating without the right information. We connect an LLM to a few tools, give it a good prompt, and expect magic.
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