<｜begin▁of▁sentence｜>### Instruction:
Imagine you're managing a complex construction project, where you've subcontracted an engineer to develop a software component that interacts with your scheduling system. As you're aware, in construction, every small detail matters, and everything needs to be up to code and specifications. The same precision is required in the software component you're integrating. 

You need to ensure your engineer crafts a function where the materials, represented by variables, have to be of certain grades (data types). To enforce this, they should use `graspologic.preconditions.check_argument_types` in their Python code to guarantee that the inputs (function arguments) meet the blueprint's standards (type specifications). This check should confirm that each 'material' is appropriate before any construction (function processing) continues. 

Could you illustrate how this 'safety check' could be implemented? Let's say we're scripting an algorithm that schedules equipment deliveries, and we need to validate that the inputs, such as the number of trucks (an integer) and delivery dates (a datetime object), are in the correct 'material' class before we proceed with the operation. This ensures our scheduling aligns accurately with the overall construction timeline.
### Response:
```python
from graspologic.preconditions import check_argument_types

def function_with_type_checks(argument):
    # Ensure that 'argument' is an instance of list
    check_argument_types(argument, list, 'Argument must be of type list')
    # Process the 'argument' knowing it is a list
    # Your code here

# Example usage:
try:
    function_with_type_checks([1, 2, 3])  # This should pass the check
    function_with_type_checks('not a list')  # This should raise a TypeError
except TypeError as e:
    print(e)
```
<|EOT|>
