Update 2016-09-17-optimizer.md

_posts/commands/2016-09-17-optimizer.md

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 [optimizer](/command/optimizer) creates an object with a pre-compiled low-level numerical format which can be used to efficiently solve a series of similar problems (reduces YALMP analysis and compilation overhead)
 
+**Warning:** Never start your model development using optimizer constructs. Always start with a standard model based on calls to [optimize](/command/optimize), and then when everything works as expected, adjust you model to use [optimizer](/command/optimizer) instead, if you think this will improve simulation performance. Debugging models in the [optimizer](/command/optimizer) world is much harder, and [optimizer](/command/optimizer) skips many sanity checks and simply assumes you know what you are doing and the the model can be solved, once parameters are fixed, by the selected solver.
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+{: .notice--info}
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 See the post [updated optimizer](/optimizerupdates) for recent extensions and improvements.
 
 ## Syntax
@@ -20,8 +25,6 @@ P = optimizer(Con,Obj,Options,Parameters,WantedVariables)
 
 ## Examples
 
-First a word of warning: Never start your model development using optimizer constructs. Always start with a standard model based on calls to [optimize](/command/optimize), and then when everything works as expected, adjust you model to use [optimizer](/command/optimizer) instead, if you think this will improve simulation performance. Debugging models in the [optimizer](/command/optimizer) world is much harder and not recommended.
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 [optimizer](/command/optimizer) is used to simplify and speed up code where  almost the same model is setup and solved repeatedly.
 
 As a start, we create a trivial linear programming model where a scalar decision variable \\(x\\) is bounded from below by some value \\(a+1\\). We create an optimizer object where the bound \\(a\\) is considered a parameter, and we are interested in the minimizing argument of \\(x^2\\) as the parameter \\(a\\) varies.