diff --git a/lib/crewai/src/crewai/agent/planning_config.py b/lib/crewai/src/crewai/agent/planning_config.py
index 088b0e1cd..d30b0eb46 100644
--- a/lib/crewai/src/crewai/agent/planning_config.py
+++ b/lib/crewai/src/crewai/agent/planning_config.py
@@ -1,9 +1,11 @@
 from __future__ import annotations
 
-from typing import Any, Literal
+from typing import Literal
 
 from pydantic import BaseModel, Field
 
+from crewai.llms.base_llm import BaseLLM
+
 
 class PlanningConfig(BaseModel):
     """Configuration for agent planning/reasoning before task execution.
@@ -128,7 +130,7 @@ class PlanningConfig(BaseModel):
             "whether to continue or replan. None means no per-step timeout."
         ),
     )
-    llm: str | Any | None = Field(
+    llm: str | BaseLLM | None = Field(
         default=None,
         description="LLM to use for planning. Uses agent's LLM if None.",
     )
diff --git a/lib/crewai/src/crewai/agents/planner_observer.py b/lib/crewai/src/crewai/agents/planner_observer.py
index 9a6351b06..8be1c7368 100644
--- a/lib/crewai/src/crewai/agents/planner_observer.py
+++ b/lib/crewai/src/crewai/agents/planner_observer.py
@@ -22,6 +22,7 @@ from crewai.events.types.observation_events import (
     StepObservationFailedEvent,
     StepObservationStartedEvent,
 )
+from crewai.utilities.agent_utils import extract_task_section
 from crewai.utilities.i18n import I18N, get_i18n
 from crewai.utilities.llm_utils import create_llm
 from crewai.utilities.planning_types import StepObservation, TodoItem
@@ -192,22 +193,6 @@ class PlannerObserver:
                 needs_full_replan=False,
             )
 
-    def _extract_task_section(self, text: str) -> str:
-        """Extract the ## Task body from a structured enriched instruction.
-
-        Falls back to the full text (capped at 2000 chars) for plain inputs.
-        """
-        for marker in ("\n## Task\n", "\n## Task:", "## Task\n"):
-            idx = text.find(marker)
-            if idx >= 0:
-                start = idx + len(marker)
-                for end_marker in ("\n---\n", "\n## "):
-                    end = text.find(end_marker, start)
-                    if end > 0:
-                        return text[start:end].strip()
-                return text[start : start + 2000].strip()
-        return text[:2000] if len(text) > 2000 else text
-
     def apply_refinements(
         self,
         observation: StepObservation,
@@ -231,7 +216,9 @@ class PlannerObserver:
         todo_by_step: dict[int, TodoItem] = {t.step_number: t for t in remaining_todos}
         for refinement in observation.suggested_refinements:
             if refinement.step_number in todo_by_step and refinement.new_description:
-                todo_by_step[refinement.step_number].description = refinement.new_description
+                todo_by_step[
+                    refinement.step_number
+                ].description = refinement.new_description
 
         return remaining_todos
 
@@ -256,7 +243,7 @@ class PlannerObserver:
             # Standalone kickoff path — no Task object, but we have the raw input.
             # Extract just the ## Task section so the observer sees the actual goal,
             # not the full enriched instruction with env/tools/verification noise.
-            task_desc = self._extract_task_section(self.kickoff_input)
+            task_desc = extract_task_section(self.kickoff_input)
             task_goal = "Complete the task successfully"
 
         system_prompt = self._i18n.retrieve("planning", "observation_system_prompt")
@@ -329,7 +316,9 @@ class PlannerObserver:
             if text.startswith("```"):
                 lines = text.split("\n")
                 # Strip first and last lines (``` markers)
-                inner = "\n".join(lines[1:-1] if lines[-1].strip() == "```" else lines[1:])
+                inner = "\n".join(
+                    lines[1:-1] if lines[-1].strip() == "```" else lines[1:]
+                )
                 try:
                     return StepObservation.model_validate_json(inner.strip())
                 except Exception:  # noqa: S110
@@ -345,12 +334,12 @@ class PlannerObserver:
         # Last resort — log what we got so it's diagnosable
         logger.warning(
             "Could not parse observation response (type=%s). "
-            "Falling back to default success observation. Preview: %.200s",
+            "Falling back to default failure observation. Preview: %.200s",
             type(response).__name__,
             str(response),
         )
         return StepObservation(
-            step_completed_successfully=True,
+            step_completed_successfully=False,
             key_information_learned=str(response) if response else "",
-            remaining_plan_still_valid=True,
+            remaining_plan_still_valid=False,
         )
diff --git a/lib/crewai/src/crewai/agents/step_executor.py b/lib/crewai/src/crewai/agents/step_executor.py
index 5dfb05f11..38baad7b9 100644
--- a/lib/crewai/src/crewai/agents/step_executor.py
+++ b/lib/crewai/src/crewai/agents/step_executor.py
@@ -32,6 +32,7 @@ from crewai.utilities.agent_utils import (
     check_native_tool_support,
     enforce_rpm_limit,
     execute_single_native_tool_call,
+    extract_task_section,
     format_message_for_llm,
     is_tool_call_list,
     process_llm_response,
@@ -235,35 +236,6 @@ class StepExecutor:
             tools_section=tools_section,
         )
 
-    def _extract_task_section(self, task_description: str) -> str:
-        """Extract the most relevant portion of the task description.
-
-        For structured descriptions (e.g. harbor_agent-style with ## Task
-        and ## Instructions sections), extracts just the task body so the
-        executor sees the requirements without duplicating tool/verification
-        instructions that are already in the system prompt.
-
-        For plain descriptions, returns the full text (up to 2000 chars).
-        """
-        # Try to extract between "## Task" and the next "---" separator
-        # or next "##" heading — this isolates the task spec from env/tool noise.
-        for marker in ("\n## Task\n", "\n## Task:", "## Task\n"):
-            idx = task_description.find(marker)
-            if idx >= 0:
-                start = idx + len(marker)
-                # End at the first horizontal rule or next top-level ## section
-                for end_marker in ("\n---\n", "\n## "):
-                    end = task_description.find(end_marker, start)
-                    if end > 0:
-                        return task_description[start:end].strip()
-                # No end marker — take up to 2000 chars
-                return task_description[start : start + 2000].strip()
-
-        # No structured format — use the full description, reasonably truncated
-        if len(task_description) > 2000:
-            return task_description[:2000] + "\n... [truncated]"
-        return task_description
-
     def _build_user_prompt(self, todo: TodoItem, context: StepExecutionContext) -> str:
         """Build the user prompt for this specific step."""
         parts: list[str] = []
@@ -273,7 +245,7 @@ class StepExecutor:
         # We extract only the task body (not tool instructions or verification
         # sections) to avoid duplicating directives already in the system prompt.
         if context.task_description:
-            task_section = self._extract_task_section(context.task_description)
+            task_section = extract_task_section(context.task_description)
             if task_section:
                 parts.append(
                     self._i18n.retrieve(
diff --git a/lib/crewai/src/crewai/utilities/agent_utils.py b/lib/crewai/src/crewai/utilities/agent_utils.py
index 7e52e733f..5de1be0c6 100644
--- a/lib/crewai/src/crewai/utilities/agent_utils.py
+++ b/lib/crewai/src/crewai/utilities/agent_utils.py
@@ -214,6 +214,30 @@ def convert_tools_to_openai_schema(
     return openai_tools, available_functions, tool_name_mapping
 
 
+def extract_task_section(text: str) -> str:
+    """Extract the ## Task body from a structured enriched instruction.
+
+    For structured descriptions (e.g. with ## Task and ## Instructions sections),
+    extracts just the task body so the caller sees the requirements without
+    duplicating tool/verification instructions.
+
+    Falls back to the full text (up to 2000 chars, with a truncation marker)
+    for plain inputs.
+    """
+    for marker in ("\n## Task\n", "\n## Task:", "## Task\n"):
+        idx = text.find(marker)
+        if idx >= 0:
+            start = idx + len(marker)
+            for end_marker in ("\n---\n", "\n## "):
+                end = text.find(end_marker, start)
+                if end > 0:
+                    return text[start:end].strip()
+            return text[start : start + 2000].strip()
+    if len(text) > 2000:
+        return text[:2000] + "\n... [truncated]"
+    return text
+
+
 def has_reached_max_iterations(iterations: int, max_iterations: int) -> bool:
     """Check if the maximum number of iterations has been reached.
 
diff --git a/lib/crewai/src/crewai/utilities/step_execution_context.py b/lib/crewai/src/crewai/utilities/step_execution_context.py
index 170427948..39e3acd92 100644
--- a/lib/crewai/src/crewai/utilities/step_execution_context.py
+++ b/lib/crewai/src/crewai/utilities/step_execution_context.py
@@ -41,7 +41,7 @@ class StepExecutionContext:
         return self.dependency_results.get(step_number)
 
 
-@dataclass
+@dataclass(frozen=True)
 class StepResult:
     """Result returned by a StepExecutor after executing a single todo.
 
diff --git a/lib/crewai/tests/agents/test_agent_executor.py b/lib/crewai/tests/agents/test_agent_executor.py
index 7fe1855fe..97bd4003f 100644
--- a/lib/crewai/tests/agents/test_agent_executor.py
+++ b/lib/crewai/tests/agents/test_agent_executor.py
@@ -1658,15 +1658,15 @@ class TestObserverResponseParsing:
         assert result.replan_reason == "step timed out"
 
     def test_parse_unparseable_falls_back_gracefully(self):
-        """Totally unparseable response falls back to default."""
+        """Totally unparseable response falls back to default failure."""
         from crewai.agents.planner_observer import PlannerObserver
         from crewai.utilities.planning_types import StepObservation
 
         result = PlannerObserver._parse_observation_response(12345)
 
         assert isinstance(result, StepObservation)
-        assert result.step_completed_successfully is True
-        assert result.remaining_plan_still_valid is True
+        assert result.step_completed_successfully is False
+        assert result.remaining_plan_still_valid is False
 
     def test_observe_parses_json_string_from_llm(self):
         """End-to-end: observer.observe() correctly parses a JSON string from llm.call()."""