diff --git a/chatmastermind/ais/openai.py b/chatmastermind/ais/openai.py
index 74438b8..ffbfa7a 100644
--- a/chatmastermind/ais/openai.py
+++ b/chatmastermind/ais/openai.py
@@ -17,8 +17,9 @@ class OpenAI(AI):
     The OpenAI AI client.
     """
 
-    def __init__(self, name: str, config: OpenAIConfig) -> None:
-        self.name = name
+    def __init__(self, config: OpenAIConfig) -> None:
+        self.ai_type = config.ai_type
+        self.name = config.name
         self.config = config
 
     def request(self,
@@ -31,8 +32,7 @@ class OpenAI(AI):
         chat history. The nr. of requested answers corresponds to the
         nr. of messages in the 'AIResponse'.
         """
-        # FIXME: use real 'system' message (store in OpenAIConfig)
-        oai_chat = self.openai_chat(chat, "system", question)
+        oai_chat = self.openai_chat(chat, self.config.system, question)
         response = openai.ChatCompletion.create(
             model=self.config.model,
             messages=oai_chat,
diff --git a/chatmastermind/configuration.py b/chatmastermind/configuration.py
index 0780604..39d9a46 100644
--- a/chatmastermind/configuration.py
+++ b/chatmastermind/configuration.py
@@ -1,16 +1,26 @@
 import yaml
-from typing import Type, TypeVar, Any
-from dataclasses import dataclass, asdict
+from pathlib import Path
+from typing import Type, TypeVar, Any, Optional
+from dataclasses import dataclass, asdict, field
 
 ConfigInst = TypeVar('ConfigInst', bound='Config')
+AIConfigInst = TypeVar('AIConfigInst', bound='AIConfig')
 OpenAIConfigInst = TypeVar('OpenAIConfigInst', bound='OpenAIConfig')
 
 
+supported_ais: list[str] = ['openai']
+
+
+class ConfigError(Exception):
+    pass
+
+
 @dataclass
 class AIConfig:
     """
     The base class of all AI configurations.
     """
+    ai_type: str
     name: str
 
 
@@ -19,13 +29,18 @@ class OpenAIConfig(AIConfig):
     """
     The OpenAI section of the configuration file.
     """
-    api_key: str
-    model: str
-    temperature: float
-    max_tokens: int
-    top_p: float
-    frequency_penalty: float
-    presence_penalty: float
+    # all members have default values, so we can easily create
+    # a default configuration
+    ai_type: str = 'openai'
+    name: str = 'openai_1'
+    system: str = 'You are an assistant'
+    api_key: str = '0123456789'
+    model: str = 'gpt-3.5'
+    temperature: float = 1.0
+    max_tokens: int = 4000
+    top_p: float = 1.0
+    frequency_penalty: float = 0.0
+    presence_penalty: float = 0.0
 
     @classmethod
     def from_dict(cls: Type[OpenAIConfigInst], source: dict[str, Any]) -> OpenAIConfigInst:
@@ -33,7 +48,9 @@ class OpenAIConfig(AIConfig):
         Create OpenAIConfig from a dict.
         """
         return cls(
-            name='OpenAI',
+            ai_type='openai',
+            name=str(source['name']),
+            system=str(source['system']),
             api_key=str(source['api_key']),
             model=str(source['model']),
             max_tokens=int(source['max_tokens']),
@@ -43,36 +60,79 @@ class OpenAIConfig(AIConfig):
             presence_penalty=float(source['presence_penalty'])
         )
 
+    def as_dict(self) -> dict[str, Any]:
+        return asdict(self)
+
+
+def ai_type_instance(ai_type: str, conf_dict: Optional[dict[str, Any]] = None) -> AIConfig:
+    """
+    Creates an AIConfig instance of the given type.
+    """
+    if ai_type.lower() == 'openai':
+        if conf_dict is None:
+            return OpenAIConfig()
+        else:
+            return OpenAIConfig.from_dict(conf_dict)
+    else:
+        raise ConfigError(f"AI type '{ai_type}' is not supported")
+
+
+def create_default_ai_configs() -> dict[str, AIConfig]:
+    """
+    Create a dict containing default configurations for all supported AIs.
+    """
+    return {ai_type_instance(ai_type).name: ai_type_instance(ai_type) for ai_type in supported_ais}
+
 
 @dataclass
 class Config:
     """
     The configuration file structure.
     """
-    system: str
-    db: str
-    openai: OpenAIConfig
+    # all members have default values, so we can easily create
+    # a default configuration
+    db: str = './db/'
+    ais: dict[str, AIConfig] = field(default_factory=create_default_ai_configs)
 
     @classmethod
     def from_dict(cls: Type[ConfigInst], source: dict[str, Any]) -> ConfigInst:
         """
         Create Config from a dict.
         """
+        # create the correct AI type instances
+        ais: dict[str, AIConfig] = {}
+        for name, conf in source['ais'].items():
+            ai_conf = ai_type_instance(conf['type'], conf)
+            ais[name] = ai_conf
         return cls(
-            system=str(source['system']),
             db=str(source['db']),
-            openai=OpenAIConfig.from_dict(source['openai'])
+            ais=ais
         )
 
+    @classmethod
+    def create_default(self, file_path: Path) -> None:
+        """
+        Creates a default Config in the given file.
+        """
+        conf = Config()
+        conf.to_file(file_path)
+
     @classmethod
     def from_file(cls: Type[ConfigInst], path: str) -> ConfigInst:
         with open(path, 'r') as f:
             source = yaml.load(f, Loader=yaml.FullLoader)
+        # add the AI name to the config (for easy internal access)
+        for name, conf in source['ais'].items():
+            conf['name'] = name
         return cls.from_dict(source)
 
-    def to_file(self, path: str) -> None:
-        with open(path, 'w') as f:
-            yaml.dump(asdict(self), f, sort_keys=False)
+    def to_file(self, file_path: Path) -> None:
+        # remove the AI name from the config (for a cleaner format)
+        data = self.as_dict()
+        for ai_name, ai_conf in data['ais'].items():
+            del (ai_conf['name'])
+        with open(file_path, 'w') as f:
+            yaml.dump(data, f, sort_keys=False)
 
     def as_dict(self) -> dict[str, Any]:
         return asdict(self)