diff --git a/streams/src/main/java/org/apache/kafka/streams/kstream/KStream.java b/streams/src/main/java/org/apache/kafka/streams/kstream/KStream.java
index 882f0550f6d..255ccb7c636 100644
--- a/streams/src/main/java/org/apache/kafka/streams/kstream/KStream.java
+++ b/streams/src/main/java/org/apache/kafka/streams/kstream/KStream.java
@@ -879,7 +879,10 @@ public interface KStream<K, V> {
      * A {@link Transformer} (provided by the given {@link TransformerSupplier}) is applied to each input record and
      * returns zero or one output record.
      * Thus, an input record {@code <K,V>} can be transformed into an output record {@code <K':V'>}.
-     * This is a stateful record-by-record operation (cf. {@link #map(KeyValueMapper) map()}).
+     * Attaching a state store makes this a stateful record-by-record operation (cf. {@link #map(KeyValueMapper) map()}).
+     * If you choose not to attach one, this operation is similar to the stateless {@link #map(KeyValueMapper) map()}
+     * but allows access to the {@code ProcessorContext} and record metadata.
+     * This is essentially mixing the Processor API into the DSL, and provides all the functionality of the PAPI.
      * Furthermore, via {@link org.apache.kafka.streams.processor.Punctuator#punctuate(long) Punctuator#punctuate()},
      * the processing progress can be observed and additional periodic actions can be performed.
      * <p>
@@ -970,7 +973,10 @@ public interface KStream<K, V> {
      * A {@link Transformer} (provided by the given {@link TransformerSupplier}) is applied to each input record and
      * returns zero or one output record.
      * Thus, an input record {@code <K,V>} can be transformed into an output record {@code <K':V'>}.
-     * This is a stateful record-by-record operation (cf. {@link #map(KeyValueMapper) map()}).
+     * Attaching a state store makes this a stateful record-by-record operation (cf. {@link #map(KeyValueMapper) map()}).
+     * If you choose not to attach one, this operation is similar to the stateless {@link #map(KeyValueMapper) map()}
+     * but allows access to the {@code ProcessorContext} and record metadata.
+     * This is essentially mixing the Processor API into the DSL, and provides all the functionality of the PAPI.
      * Furthermore, via {@link org.apache.kafka.streams.processor.Punctuator#punctuate(long) Punctuator#punctuate()},
      * the processing progress can be observed and additional periodic actions can be performed.
      * <p>
@@ -1063,8 +1069,9 @@ public interface KStream<K, V> {
      * A {@link Transformer} (provided by the given {@link TransformerSupplier}) is applied to each input record and
      * returns zero or more output records.
      * Thus, an input record {@code <K,V>} can be transformed into output records {@code <K':V'>, <K'':V''>, ...}.
-     * This is a stateful record-by-record operation (cf. {@link #flatMap(KeyValueMapper) flatMap()} for stateless
-     * record transformation).
+     * Attaching a state store makes this a stateful record-by-record operation (cf. {@link #flatMap(KeyValueMapper) flatMap()).
+     * If you choose not to attach one, this operation is similar to the stateless {@link #flatMap(KeyValueMapper) flatMap()
+     * but allows access to the {@code ProcessorContext} and record metadata.
      * Furthermore, via {@link org.apache.kafka.streams.processor.Punctuator#punctuate(long) Punctuator#punctuate()}
      * the processing progress can be observed and additional periodic actions can be performed.
      * <p>
@@ -1155,8 +1162,9 @@ public interface KStream<K, V> {
      * A {@link Transformer} (provided by the given {@link TransformerSupplier}) is applied to each input record and
      * returns zero or more output records.
      * Thus, an input record {@code <K,V>} can be transformed into output records {@code <K':V'>, <K'':V''>, ...}.
-     * This is a stateful record-by-record operation (cf. {@link #flatMap(KeyValueMapper) flatMap()} for stateless
-     * record transformation).
+     * Attaching a state store makes this a stateful record-by-record operation (cf. {@link #flatMap(KeyValueMapper) flatMap()}).
+     * If you choose not to attach one, this operation is similar to the stateless {@link #flatMap(KeyValueMapper) flatMap()}
+     * but allows access to the {@code ProcessorContext} and record metadata.
      * Furthermore, via {@link org.apache.kafka.streams.processor.Punctuator#punctuate(long) Punctuator#punctuate()}
      * the processing progress can be observed and additional periodic actions can be performed.
      * <p>
@@ -1248,7 +1256,9 @@ public interface KStream<K, V> {
      * A {@link ValueTransformer} (provided by the given {@link ValueTransformerSupplier}) is applied to each input
      * record value and computes a new value for it.
      * Thus, an input record {@code <K,V>} can be transformed into an output record {@code <K:V'>}.
-     * This is a stateful record-by-record operation (cf. {@link #mapValues(ValueMapper)}).
+     * Attaching a state store makes this a stateful record-by-record operation (cf. {@link #mapValues(ValueMapper) mapValues()}).
+     * If you choose not to attach one, this operation is similar to the stateless {@link #mapValues(ValueMapper) mapValues()}
+     * but allows access to the {@code ProcessorContext} and record metadata.
      * Furthermore, via {@link org.apache.kafka.streams.processor.Punctuator#punctuate(long)} the processing progress
      * can be observed and additional periodic actions can be performed.
      * <p>
@@ -1323,7 +1333,10 @@ public interface KStream<K, V> {
      * A {@link ValueTransformer} (provided by the given {@link ValueTransformerSupplier}) is applied to each input
      * record value and computes a new value for it.
      * Thus, an input record {@code <K,V>} can be transformed into an output record {@code <K:V'>}.
-     * This is a stateful record-by-record operation (cf. {@link #mapValues(ValueMapper)}).
+     * Attaching a state store makes this a stateful record-by-record operation (cf. {@link #mapValues(ValueMapper) mapValues()}).
+     * If you choose not to attach one, this operation is similar to the stateless {@link #mapValues(ValueMapper) mapValues()}
+     * but allows access to the {@code ProcessorContext} and record metadata.
+     * This is essentially mixing the Processor API into the DSL, and provides all the functionality of the PAPI.
      * Furthermore, via {@link org.apache.kafka.streams.processor.Punctuator#punctuate(long)} the processing progress
      * can be observed and additional periodic actions can be performed.
      * <p>
@@ -1401,7 +1414,10 @@ public interface KStream<K, V> {
      * A {@link ValueTransformerWithKey} (provided by the given {@link ValueTransformerWithKeySupplier}) is applied to
      * each input record value and computes a new value for it.
      * Thus, an input record {@code <K,V>} can be transformed into an output record {@code <K:V'>}.
-     * This is a stateful record-by-record operation (cf. {@link #mapValues(ValueMapperWithKey)}).
+     * Attaching a state store makes this a stateful record-by-record operation (cf. {@link #mapValues(ValueMapperWithKey) mapValues()}).
+     * If you choose not to attach one, this operation is similar to the stateless {@link #mapValues(ValueMapperWithKey) mapValues()}
+     * but allows access to the {@code ProcessorContext} and record metadata.
+     * This is essentially mixing the Processor API into the DSL, and provides all the functionality of the PAPI.
      * Furthermore, via {@link org.apache.kafka.streams.processor.Punctuator#punctuate(long)} the processing progress
      * can be observed and additional periodic actions can be performed.
      * <p>
@@ -1480,7 +1496,10 @@ public interface KStream<K, V> {
      * A {@link ValueTransformerWithKey} (provided by the given {@link ValueTransformerWithKeySupplier}) is applied to
      * each input record value and computes a new value for it.
      * Thus, an input record {@code <K,V>} can be transformed into an output record {@code <K:V'>}.
-     * This is a stateful record-by-record operation (cf. {@link #mapValues(ValueMapperWithKey)}).
+     * Attaching a state store makes this a stateful record-by-record operation (cf. {@link #mapValues(ValueMapperWithKey) mapValues()}).
+     * If you choose not to attach one, this operation is similar to the stateless {@link #mapValues(ValueMapperWithKey) mapValues()}
+     * but allows access to the {@code ProcessorContext} and record metadata.
+     * This is essentially mixing the Processor API into the DSL, and provides all the functionality of the PAPI.
      * Furthermore, via {@link org.apache.kafka.streams.processor.Punctuator#punctuate(long)} the processing progress
      * can be observed and additional periodic actions can be performed.
      * <p>
@@ -1561,7 +1580,10 @@ public interface KStream<K, V> {
      * A {@link ValueTransformer} (provided by the given {@link ValueTransformerSupplier}) is applied to each input
      * record value and computes zero or more new values.
      * Thus, an input record {@code <K,V>} can be transformed into output records {@code <K:V'>, <K:V''>, ...}.
-     * This is a stateful record-by-record operation (cf. {@link #mapValues(ValueMapper) mapValues()}).
+     * Attaching a state store makes this a stateful record-by-record operation (cf. {@link #mapValues(ValueMapper) mapValues()}).
+     * If you choose not to attach one, this operation is similar to the stateless {@link #mapValues(ValueMapper) mapValues()}
+     * but allows access to the {@code ProcessorContext} and record metadata.
+     * This is essentially mixing the Processor API into the DSL, and provides all the functionality of the PAPI.
      * Furthermore, via {@link org.apache.kafka.streams.processor.Punctuator#punctuate(long) Punctuator#punctuate()}
      * the processing progress can be observed and additional periodic actions can be performed.
      * <p>
@@ -1647,7 +1669,10 @@ public interface KStream<K, V> {
      * A {@link ValueTransformer} (provided by the given {@link ValueTransformerSupplier}) is applied to each input
      * record value and computes zero or more new values.
      * Thus, an input record {@code <K,V>} can be transformed into output records {@code <K:V'>, <K:V''>, ...}.
-     * This is a stateful record-by-record operation (cf. {@link #mapValues(ValueMapper) mapValues()}).
+     * Attaching a state store makes this a stateful record-by-record operation (cf. {@link #mapValues(ValueMapper) mapValues()}).
+     * If you choose not to attach one, this operation is similar to the stateless {@link #mapValues(ValueMapper) mapValues()}
+     * but allows access to the {@code ProcessorContext} and record metadata.
+     * This is essentially mixing the Processor API into the DSL, and provides all the functionality of the PAPI.
      * Furthermore, via {@link org.apache.kafka.streams.processor.Punctuator#punctuate(long) Punctuator#punctuate()}
      * the processing progress can be observed and additional periodic actions can be performed.
      * <p>
@@ -1735,7 +1760,10 @@ public interface KStream<K, V> {
      * A {@link ValueTransformerWithKey} (provided by the given {@link ValueTransformerWithKeySupplier}) is applied to
      * each input record value and computes zero or more new values.
      * Thus, an input record {@code <K,V>} can be transformed into output records {@code <K:V'>, <K:V''>, ...}.
-     * This is a stateful record-by-record operation (cf. {@link #flatMapValues(ValueMapperWithKey) flatMapValues()}).
+     * Attaching a state store makes this a stateful record-by-record operation (cf. {@link #flatMapValues(ValueMapperWithKey) flatMapValues()}).
+     * If you choose not to attach one, this operation is similar to the stateless {@link #flatMapValues(ValueMapperWithKey) flatMapValues()}
+     * but allows access to the {@code ProcessorContext} and record metadata.
+     * This is essentially mixing the Processor API into the DSL, and provides all the functionality of the PAPI.
      * Furthermore, via {@link org.apache.kafka.streams.processor.Punctuator#punctuate(long)} the processing progress can
      * be observed and additional periodic actions can be performed.
      * <p>
@@ -1822,7 +1850,10 @@ public interface KStream<K, V> {
      * A {@link ValueTransformerWithKey} (provided by the given {@link ValueTransformerWithKeySupplier}) is applied to
      * each input record value and computes zero or more new values.
      * Thus, an input record {@code <K,V>} can be transformed into output records {@code <K:V'>, <K:V''>, ...}.
-     * This is a stateful record-by-record operation (cf. {@link #flatMapValues(ValueMapperWithKey) flatMapValues()}).
+     * Attaching a state store makes this a stateful record-by-record operation (cf. {@link #flatMapValues(ValueMapperWithKey) flatMapValues()}).
+     * If you choose not to attach one, this operation is similar to the stateless {@link #flatMapValues(ValueMapperWithKey) flatMapValues()}
+     * but allows access to the {@code ProcessorContext} and record metadata.
+     * This is essentially mixing the Processor API into the DSL, and provides all the functionality of the PAPI.
      * Furthermore, via {@link org.apache.kafka.streams.processor.Punctuator#punctuate(long)} the processing progress can
      * be observed and additional periodic actions can be performed.
      * <p>
@@ -1908,7 +1939,10 @@ public interface KStream<K, V> {
     /**
      * Process all records in this stream, one record at a time, by applying a {@link Processor} (provided by the given
      * {@link ProcessorSupplier}).
-     * This is a stateful record-by-record operation (cf. {@link #foreach(ForeachAction)}).
+     * Attaching a state store makes this a stateful record-by-record operation (cf. {@link #foreach(ForeachAction)}).
+     * If you choose not to attach one, this operation is similar to the stateless {@link #foreach(ForeachAction)}
+     * but allows access to the {@code ProcessorContext} and record metadata.
+     * This is essentially mixing the Processor API into the DSL, and provides all the functionality of the PAPI.
      * Furthermore, via {@link org.apache.kafka.streams.processor.Punctuator#punctuate(long)} the processing progress
      * can be observed and additional periodic actions can be performed.
      * Note that this is a terminal operation that returns void.
@@ -1967,7 +2001,10 @@ public interface KStream<K, V> {
     /**
      * Process all records in this stream, one record at a time, by applying a {@link Processor} (provided by the given
      * {@link ProcessorSupplier}).
-     * This is a stateful record-by-record operation (cf. {@link #foreach(ForeachAction)}).
+     * Attaching a state store makes this a stateful record-by-record operation (cf. {@link #foreach(ForeachAction)}).
+     * If you choose not to attach one, this operation is similar to the stateless {@link #foreach(ForeachAction)}
+     * but allows access to the {@code ProcessorContext} and record metadata.
+     * This is essentially mixing the Processor API into the DSL, and provides all the functionality of the PAPI.
      * Furthermore, via {@link org.apache.kafka.streams.processor.Punctuator#punctuate(long)} the processing progress
      * can be observed and additional periodic actions can be performed.
      * Note that this is a terminal operation that returns void.