I've been presenting at local meetups about Context Engineering, RAG, Skills, etc.. I even have a vbrownbag coming up on LinkedIn about this topic so I figured I would make a basic example that uses bedrock so I can use it in my talks or vbrownbags. Hopefully it's useful.
> the information an AI system needs to produce accurate ... outputs
I would have stuck a qualifier in there
I feel like AI is going to be doing all the fun stuff and I will just left organizing the data and docs it needs to generate code.
Putting engineering after a term doesnt make it engineering.
I don’t really think this reflects the current era of challenges?
The “enforcement layer” is the hardest and most important part, and is barely addressed.
- is the answer structurally / syntactically valid?
- is it appropriately grounded and evidenced?
- is it accurate? In what ways does it fall short?
Each of these should be triggering an agent to rework and resubmit etc. or failing that a disclosure to the user about how the answer falls short and should be reviewed / remediated.
This feels like it’s from the era of trying to oneshot a good enough answer.