diff --git a/prediction_market_agent/agents/known_outcome_agent/deploy.py b/prediction_market_agent/agents/known_outcome_agent/deploy.py
index bbc0992e..6c6e2775 100644
--- a/prediction_market_agent/agents/known_outcome_agent/deploy.py
+++ b/prediction_market_agent/agents/known_outcome_agent/deploy.py
@@ -37,20 +37,41 @@ def pick_markets(self, markets: list[AgentMarket]) -> list[AgentMarket]:
             # Assume very high probability markets are already known, and have
             # been correctly bet on, and therefore the value of betting on them
             # is low.
+            print(f"Looking at market {market.id=} {market.question=}")
             if not market_is_saturated(
                 market=market
             ) and has_question_event_happened_in_the_past(
                 model=self.model, question=market.question
             ):
-                answer = get_known_outcome(
-                    model=self.model,
-                    question=market.question,
-                    max_tries=3,
-                )
+                print(f"Predicting market {market.id=} {market.question=}")
+                try:
+                    answer = get_known_outcome(
+                        model=self.model,
+                        question=market.question,
+                        max_tries=3,
+                    )
+                except Exception as e:
+                    print(
+                        f"Error: Failed to predict market {market.id=} {market.question=}: {e}"
+                    )
+                    continue
                 if answer.has_known_outcome():
+                    print(
+                        f"Picking market {market.id=} {market.question=} with answer {answer.result=}"
+                    )
                     picked_markets.append(market)
                     self.markets_with_known_outcomes[market.id] = answer.result
 
+                    # Return as soon as we have picked a market, because otherwise it will take too long and we will run out of time in GCP Function (540s timeout)
+                    # TODO: After PMAT is updated in this repository, we can return `None` in `answer_binary_market` method and PMAT won't place the bet.
+                    # So we can move this logic out of `pick_markets` into `answer_binary_market`, and simply process as many bets as we have time for.
+                    return picked_markets
+
+            else:
+                print(
+                    f"Skipping market {market.id=} {market.question=}, because it is already saturated."
+                )
+
         return picked_markets
 
     def answer_binary_market(self, market: AgentMarket) -> bool:
diff --git a/prediction_market_agent/agents/known_outcome_agent/known_outcome_agent.py b/prediction_market_agent/agents/known_outcome_agent/known_outcome_agent.py
index e933e31b..1c86f68d 100644
--- a/prediction_market_agent/agents/known_outcome_agent/known_outcome_agent.py
+++ b/prediction_market_agent/agents/known_outcome_agent/known_outcome_agent.py
@@ -192,7 +192,9 @@ def get_known_outcome(model: str, question: str, max_tries: int) -> Answer:
         search_prompt = ChatPromptTemplate.from_template(
             template=GENERATE_SEARCH_QUERY_PROMPT
         ).format_messages(date_str=date_str, question=question)
+        print(f"Invoking LLM for {search_prompt=}")
         search_query = str(llm.invoke(search_prompt).content).strip('"')
+        print(f"Searchig for {search_query=}")
         search_results = web_search(query=search_query, max_results=5)
         if not search_results:
             raise ValueError("No search results found.")