diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml
new file mode 100644
index 0000000..9982c08
--- /dev/null
+++ b/.github/workflows/publish.yml
@@ -0,0 +1,26 @@
+name: Publish Python Package
+
+on:
+  push:
+    branches: ["main"]
+
+permissions:
+  contents: read
+
+jobs:
+  publish:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v4
+    - name: Install uv
+      uses: astral-sh/setup-uv@v4
+    - name: Set up Python
+      uses: actions/setup-python@v5
+      with:
+        python-version: '3.10'
+    - name: Install the project
+      run: uv sync --all-extras --dev
+    - name: Build package
+      run: uv build
+    - name: Publish package
+      uses: pypa/gh-action-pypi-publish@release/v1
\ No newline at end of file
diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..de8ec0b
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,164 @@
+.DS_Store
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/latest/usage/project/#working-with-version-control
+.pdm.toml
+.pdm-python
+.pdm-build/
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
\ No newline at end of file
diff --git a/.vscode/settings.json b/.vscode/settings.json
new file mode 100644
index 0000000..92db6ab
--- /dev/null
+++ b/.vscode/settings.json
@@ -0,0 +1,9 @@
+{
+  "[python]": {
+    "editor.codeActionsOnSave": {
+      "source.fixAll": "explicit",
+      "source.organizeImports": "explicit"
+    },
+    "editor.defaultFormatter": "charliermarsh.ruff"
+  }
+}
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..8690327
--- /dev/null
+++ b/README.md
@@ -0,0 +1,139 @@
+# Laminar Flow
+
+A lightweight task engine for building AI agents that prioritizes simplicity and flexibility.
+
+## Core Concept
+
+Unlike traditional node-based workflows, Laminar Flow uses a dynamic task queue system built on three simple principles:
+
+1. **Concurrent Execution** - Tasks run in parallel automatically
+2. **Dynamic Scheduling** - Tasks can schedule new tasks at runtime
+3. **Smart Dependencies** - Tasks can await results from previous operations
+
+Results of all tasks are stored in a thread-safe `Context`.
+
+This task-based architecture makes complex workflows surprisingly simple:
+
+✨ **What's Possible:**
+- [x] Parallel task execution without explicit threading code
+- [x] Self-modifying dynamic workflows and cycles
+- [x] Conditional branching and control flow
+- [x] Streaming of tasks execution
+- [x] Automatic state management and persistence
+
+Flow is extremely lightweight, clearly written and has not external dependencies for the engine.
+
+## Getting started
+
+### Basic Usage
+```python
+from concurrent.futures import ThreadPoolExecutor
+from lmnr_flow import Flow, TaskOutput
+
+flow = Flow(thread_pool_executor=ThreadPoolExecutor(max_workers=4))
+
+# Simple task that returns a result
+def my_task(context: Context) -> TaskOutput:
+    return TaskOutput(output="Hello World!", next=None)
+
+flow.add_task("greet", my_task)
+result = flow.run("greet")  # Returns {"greet": "Hello World!"}
+```
+
+### Task Chaining
+```python
+# Tasks can trigger other tasks
+def task1(context: Context) -> TaskOutput:
+    return TaskOutput(output="result1", next=["task2"])
+
+def task2(context: Context) -> TaskOutput:
+    # Access results from previous tasks
+    t1_result = context.get("task1")  # Gets "result1"
+    return TaskOutput(output="result2", next=None)
+
+flow.add_task("task1", task1)
+flow.add_task("task2", task2)
+flow.run("task1")  # Returns {"task2": "result2"}
+```
+
+### Parallel Execution
+```python
+def starter(context: Context) -> TaskOutput:
+    # Launch multiple tasks in parallel
+    return TaskOutput(output="started", next=["slow_task1", "slow_task2"])
+
+def slow_task1(context: Context) -> TaskOutput:
+    time.sleep(1)
+    return TaskOutput(output="result1", next=None)
+
+def slow_task2(context: Context) -> TaskOutput:
+    time.sleep(1)
+    return TaskOutput(output="result2", next=None)
+
+# Both slow_tasks execute in parallel, taking ~1 second total
+flow.add_task("starter", starter)
+flow.add_task("slow_task1", slow_task1)
+flow.add_task("slow_task2", slow_task2)
+flow.run("starter")
+```
+
+### Streaming Results
+```python
+def streaming_task(context: Context) -> TaskOutput:
+    # Stream intermediate results
+    stream = context.get_stream()
+    for i in range(3):
+        stream.put(("streaming_task", f"interim_{i}"))
+    return TaskOutput(output="final", next=None)
+
+flow.add_task("streaming_task", streaming_task)
+
+# Get results as they arrive
+for task_id, output in flow.stream("streaming_task"):
+    print(f"{task_id}: {output}")
+    # Prints:
+    # streaming_task: interim_0
+    # streaming_task: interim_1
+    # streaming_task: interim_2
+    # streaming_task: final
+```
+
+### Dynamic Workflows
+```python
+def conditional_task(context: Context) -> TaskOutput:
+    count = context.get("count", 0)
+    
+    if count >= 3:
+        return TaskOutput(output="done", next=["finish"])
+    
+    context.set("count", count + 1)
+    return TaskOutput(output=f"iteration_{count}", next=["conditional_task"])
+
+# Task will loop 3 times before finishing
+flow.add_task("conditional_task", conditional_task)
+flow.add_task("finish", lambda ctx: TaskOutput("completed", None))
+flow.run("conditional_task")
+```
+
+### Input Parameters
+```python
+def parameterized_task(context: Context) -> TaskOutput:
+    name = context.get("user_name")
+    return TaskOutput(output=f"Hello {name}!", next=None)
+
+flow.add_task("greet", parameterized_task)
+result = flow.run("greet", inputs={"user_name": "Alice"})
+# Returns {"greet": "Hello Alice!"}
+```
+
+## Advanced Features
+
+- **Context Sharing**: All tasks share the same context, allowing for complex data flows
+- **Error Handling**: Exceptions in tasks are properly propagated
+- **Thread Safety**: All operations are thread-safe
+- **Minimal Dependencies**: Core engine has zero external dependencies
+
+## Roadmap
+- [ ] Add async
+- [ ] Serverless deployment
+- [ ] Timetravel UI
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..603fc6d
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,22 @@
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[project]
+name = "lmnr-flow"
+version = "0.1.0b1"
+description = "Lightweight task engine for building AI agents"
+readme = "README.md"
+requires-python = ">=3.10"
+
+dependencies = [
+    "lmnr>=0.4.43",
+    "pytest>=8.3.3",
+]
+
+[project.urls]
+"Homepage" = "https://github.com/lmnr-ai/flow"
+"Bug Tracker" = "https://github.com/lmnr-ai/flow/issues"
+
+[project.license]
+file = "LICENSE"
diff --git a/src/lmnr_flow/__init__.py b/src/lmnr_flow/__init__.py
new file mode 100644
index 0000000..b9f774a
--- /dev/null
+++ b/src/lmnr_flow/__init__.py
@@ -0,0 +1,3 @@
+from .context import Context
+from .flow import Flow, TaskOutput
+from .state import State
diff --git a/src/lmnr_flow/context.py b/src/lmnr_flow/context.py
new file mode 100644
index 0000000..9b6e170
--- /dev/null
+++ b/src/lmnr_flow/context.py
@@ -0,0 +1,47 @@
+from queue import Queue
+from typing import Any, Dict, Optional
+
+from .state import State
+
+
+class Context:
+    stream: Optional[Queue] = None
+
+    def __init__(self):
+        self.states = {}  # str -> State
+
+    def get(self, key: str) -> Any:
+        if key not in self.states:
+            raise Exception(f"Key {key} not found in context")
+
+        state = self.states[key]
+        output = state.get_value()
+
+        return output
+
+    def set(self, key: str, message: Any):
+        if key not in self.states:
+            state = State()
+            state.set_value(message)
+            self.states[key] = state
+        else:
+            state = self.states[key]
+            state.set_value(message)
+
+    def set_state(self, key: str, state: State):
+        self.states[key] = state
+
+    def set_stream(self, stream: Queue):
+        self.stream = stream
+
+    def get_stream(self) -> Queue:
+        if self.stream is None:
+            raise Exception("Stream is not set. Did you run .stream()?")
+        return self.stream
+
+    def to_dict(self) -> Dict[str, Any]:
+        return {key: state.get_value_with_lock() for key, state in self.states.items()}
+
+    def from_dict(self, dict: Dict[str, Any]):
+        for key, value in dict.items():
+            self.set(key, value)
diff --git a/src/lmnr_flow/flow.py b/src/lmnr_flow/flow.py
new file mode 100644
index 0000000..9f8013f
--- /dev/null
+++ b/src/lmnr_flow/flow.py
@@ -0,0 +1,196 @@
+import logging
+import traceback
+from concurrent.futures import ThreadPoolExecutor
+from dataclasses import dataclass
+from queue import Queue
+from threading import Lock
+from typing import Any, Callable, Dict, List, Optional, Union
+
+from lmnr import Laminar, observe
+
+from .context import Context
+from .state import State
+
+__ERROR__ = "__ERROR__"
+__OUTPUT__ = "__OUTPUT__"
+
+
+@dataclass
+class TaskOutput:
+    output: Any
+    next: Union[List[str], None]
+
+
+@dataclass
+class Task:
+    id: str
+    action: Callable[[Context], TaskOutput]
+
+
+class Flow:
+    def __init__(
+        self,
+        thread_pool_executor: ThreadPoolExecutor,
+        context: Optional[Context] = None,
+    ):
+        self.tasks = {}  # str -> Task
+        self.active_tasks = set()  # Set of str
+        self.context = context or Context()  # Global context
+        self.output_task_ids = set()  # Set of str
+        self._executor = thread_pool_executor
+
+        # Thread-safety locks
+        self.active_tasks_lock = Lock()
+        self.output_ids_lock = Lock()
+        self.logger = logging.getLogger(__name__)
+
+    def add_task(self, name: str, action: Callable[[Context], TaskOutput]):
+        self.context.set_state(name, State.empty())
+        self.tasks[name] = Task(name, action)
+        self.logger.info(f"Added task '{name}'")
+
+    def execute_task(
+        self, task: Task, task_queue: Queue, stream_queue: Optional[Queue] = None
+    ):
+        self.logger.info(f"Starting execution of task '{task.id}'")
+
+        try:
+            with Laminar.start_as_current_span(task.id, input=self.context.to_dict()):
+                result: TaskOutput = task.action(self.context)
+                Laminar.set_span_output(result)
+
+            # Set state to the output of the task
+            self.context.set(task.id, result.output)
+
+            # Push to stream queue if it exists
+            if stream_queue is not None:
+                stream_queue.put((task.id, result.output))
+
+            # If no next tasks specified, this is an output node
+            if not result.next or len(result.next) == 0:
+                self.logger.info(f"Task '{task.id}' completed as output node")
+                with self.output_ids_lock:
+                    self.output_task_ids.add(task.id)
+                    task_queue.put(__OUTPUT__)
+            else:
+                self.logger.debug(
+                    f"Task '{task.id}' scheduling next tasks: {result.next}"
+                )
+
+                with self.active_tasks_lock:
+                    for next_task_id in result.next:
+                        if next_task_id in self.tasks:
+                            if next_task_id not in self.active_tasks:
+                                task_queue.put(next_task_id)
+                        else:
+                            raise Exception(f"Task {next_task_id} not found")
+
+        except Exception as e:
+            self.context.set(
+                __ERROR__, {"error": str(e), "traceback": traceback.format_exc()}
+            )
+            with self.active_tasks_lock:
+                self.active_tasks.clear()
+
+            task_queue.put(__ERROR__)
+
+            raise e
+
+        finally:
+            self.logger.info(f"Completed execution of task '{task.id}'")
+            with self.active_tasks_lock:
+                self.active_tasks.remove(task.id)
+
+    @observe(name="flow.run")
+    def run(
+        self, start_task_id: str, inputs: Optional[Dict[str, Any]] = None
+    ) -> Dict[str, Any]:
+        self.logger.info(f"Starting engine run with initial task: {start_task_id}")
+        # thread-safe queue of task ids
+        task_queue = Queue()
+        futures = set()
+
+        task_queue.put(start_task_id)
+
+        if inputs:
+            for key, value in inputs.items():
+                self.context.set(key, value)
+
+        # Main execution loop
+        while True:
+            # block until there is a task to spawn
+            task_id = task_queue.get()
+
+            if task_id == __ERROR__:
+                # Cancel all pending futures on error
+                for f in futures:
+                    f.cancel()
+
+                err = self.context.get(__ERROR__)
+                raise Exception(err)
+
+            if task_id == __OUTPUT__:
+                with self.active_tasks_lock:
+                    if len(self.active_tasks) == 0:
+                        break
+                continue
+
+            with self.active_tasks_lock:
+                self.active_tasks.add(task_id)
+
+            task = self.tasks[task_id]
+            future = self._executor.submit(self.execute_task, task, task_queue)
+            futures.add(future)
+
+        # Return values of the output nodes
+        # task_id -> value of the task
+        return {task_id: self.context.get(task_id) for task_id in self.output_task_ids}
+
+    @observe(name="flow.stream")
+    def stream(self, start_task_id: str):
+        print("stream")
+        task_queue = Queue()
+        stream_queue = Queue()
+        futures = set()
+
+        self.context.set_stream(stream_queue)
+
+        def run_engine():
+            task_queue.put(start_task_id)
+            while True:
+                task_id = task_queue.get()
+
+                if task_id == __ERROR__:
+                    for f in futures:
+                        f.cancel()
+                    stream_queue.put((None, None))  # Signal completion
+                    break
+
+                if task_id == __OUTPUT__:
+                    with self.active_tasks_lock:
+                        if len(self.active_tasks) == 0:
+                            stream_queue.put((None, None))  # Signal completion
+                            break
+                    continue
+
+                task = self.tasks[task_id]
+
+                with self.active_tasks_lock:
+                    self.active_tasks.add(task_id)
+
+                future = self._executor.submit(
+                    self.execute_task, task, task_queue, stream_queue
+                )
+                futures.add(future)
+
+        self._executor.submit(run_engine)
+
+        # Yield results from stream queue
+        while True:
+            task_id, output = stream_queue.get()
+            if task_id is None:  # Check for completion signal
+                break
+            yield task_id, output
+
+    def get_context(self) -> Context:
+        return self.context
diff --git a/src/lmnr_flow/state.py b/src/lmnr_flow/state.py
new file mode 100644
index 0000000..e5ccf1c
--- /dev/null
+++ b/src/lmnr_flow/state.py
@@ -0,0 +1,30 @@
+from threading import Lock, Semaphore
+from typing import Any, Optional
+
+
+class State:
+    def __init__(self, value: Optional[Any] = None):
+        self._value = value
+        self.semaphore = Semaphore(0)
+        self._lock = Lock()
+
+    # acquiring semaphore first, then returning the message
+    def get_value(self) -> Optional[Any]:
+        self.semaphore.acquire()
+        output = self._value
+        self.semaphore.release()
+        return output
+
+    def get_value_with_lock(self) -> Optional[Any]:
+        with self._lock:
+            return self._value
+
+    def set_value(self, value: Optional[Any]):
+        with self._lock:
+            self._value = value
+        # adding single permit after value is set
+        self.semaphore.release()
+
+    @classmethod
+    def empty(cls) -> "State":
+        return cls(None)
diff --git a/tests/__init__.py b/tests/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/test_flow.py b/tests/test_flow.py
new file mode 100644
index 0000000..3ad106b
--- /dev/null
+++ b/tests/test_flow.py
@@ -0,0 +1,293 @@
+import time
+from concurrent.futures import ThreadPoolExecutor
+from unittest.mock import patch
+
+import pytest
+from lmnr.openllmetry_sdk.tracing.tracing import TracerWrapper
+from opentelemetry.sdk.trace import TracerProvider
+from opentelemetry.sdk.trace.export import ConsoleSpanExporter, SimpleSpanProcessor
+
+from src.lmnr_flow.flow import Flow, TaskOutput
+
+
+@pytest.fixture(autouse=True)
+def setup_tracer():
+    # Create and set the tracer provider
+    tracer_provider = TracerProvider()
+    # Optional: Add console exporter to see the traces in the console
+    tracer_provider.add_span_processor(SimpleSpanProcessor(ConsoleSpanExporter()))
+    
+    # Set the tracer provider for the wrapper
+    wrapper = TracerWrapper()
+    wrapper.tracer_provider = tracer_provider
+    
+    yield
+    
+    # Cleanup after tests
+    wrapper.tracer_provider = None
+
+
+@pytest.fixture(autouse=True)
+def mock_tracer():
+    with patch('lmnr.openllmetry_sdk.tracing.tracing.TracerWrapper.get_tracer'):
+        yield
+
+
+@pytest.fixture(autouse=True)
+def mock_start_as_current_span():
+    class MockContextManager:
+        def __init__(self, func, input=None):
+            self.func = func
+            
+        def __enter__(self):
+            return self.func
+            
+        def __exit__(self, exc_type, exc_val, exc_tb):
+            pass
+    
+    with patch('lmnr.Laminar.start_as_current_span', side_effect=MockContextManager):
+        yield
+
+
+@pytest.fixture
+def thread_pool():
+    with ThreadPoolExecutor(max_workers=2) as executor:
+        yield executor
+
+
+@pytest.fixture
+def flow(thread_pool):
+    return Flow(thread_pool)
+
+
+def test_simple_task_execution(flow):
+    # Test single task that returns no next tasks
+    def action(ctx):
+        return TaskOutput("result", None)
+
+    flow.add_task("task1", action)
+    result = flow.run("task1")
+
+    assert result == {"task1": "result"}
+    assert flow.context.get("task1") == "result"
+
+
+def test_sequential_tasks(flow):
+    # Test chain of tasks
+    def task1(ctx):
+        return TaskOutput("result1", ["task2"])
+
+    def task2(ctx):
+        assert ctx.get("task1") == "result1"
+        return TaskOutput("result2", None)
+
+    flow.add_task("task1", task1)
+    flow.add_task("task2", task2)
+
+    result = flow.run("task1")
+    assert result == {"task2": "result2"}
+
+
+def test_parallel_tasks(flow):
+    # Test tasks running in parallel
+    def task1(ctx):
+        return TaskOutput("result1", ["task2", "task3"])
+
+    def task2(ctx):
+        return TaskOutput("result2", None)
+
+    def task3(ctx):
+        return TaskOutput("result3", None)
+
+    flow.add_task("task1", task1)
+    flow.add_task("task2", task2)
+    flow.add_task("task3", task3)
+
+    result = flow.run("task1")
+    assert result == {"task2": "result2", "task3": "result3"}
+
+
+def test_error_handling(flow):
+    # Test error propagation
+    def failing_task(ctx):
+        raise ValueError("Task failed")
+
+    flow.add_task("failing", failing_task)
+
+    with pytest.raises(Exception) as exc_info:
+        flow.run("failing")
+
+    assert "Task failed" in str(exc_info.value)
+
+
+def test_streaming(flow):
+    # Test streaming functionality
+    def task1(ctx):
+        return TaskOutput("result1", ["task2"])
+
+    def task2(ctx):
+        return TaskOutput("result2", None)
+
+    flow.add_task("task1", task1)
+    flow.add_task("task2", task2)
+
+    results = []
+    for task_id, output in flow.stream("task1"):
+        results.append((task_id, output))
+
+    assert len(results) == 2
+    assert ("task1", "result1") in results
+    assert ("task2", "result2") in results
+
+
+def test_streaming_within_task(flow):
+    def task1(ctx):
+        for i in range(3):
+            ctx.get_stream().put(("task1", i))
+        return TaskOutput("result1", None)
+
+    flow.add_task("task1", task1)
+
+    results = []
+
+    for task_id, output in flow.stream("task1"):
+        results.append((task_id, output))
+
+    assert len(results) == 4
+    assert ("task1", 0) in results
+    assert ("task1", 1) in results
+    assert ("task1", 2) in results
+    assert ("task1", "result1") in results
+
+
+def test_context_sharing(flow):
+    # Test context sharing between tasks
+    def task1(ctx):
+        ctx.set("shared", "shared_value")
+        return TaskOutput("result1", ["task2"])
+
+    def task2(ctx):
+        assert ctx.get("shared") == "shared_value"
+        return TaskOutput("result2", None)
+
+    flow.add_task("task1", task1)
+    flow.add_task("task2", task2)
+
+    result = flow.run("task1")
+    assert result == {"task2": "result2"}
+
+
+def test_invalid_task_reference(flow):
+    # Test referencing non-existent task
+    def task1(ctx):
+        return TaskOutput("result1", ["non_existent_task"])
+
+    flow.add_task("task1", task1)
+
+    with pytest.raises(Exception) as exc_info:
+        flow.run("task1")
+
+    assert "Task non_existent_task not found" in str(exc_info.value)
+
+
+def test_actual_parallel_execution(flow):
+    # Test that tasks actually run in parallel by checking execution time
+    def task1(ctx):
+        return TaskOutput("result1", ["slow_task1", "slow_task2"])
+
+    def slow_task1(ctx):
+        time.sleep(0.5)  # Sleep for 500ms
+        return TaskOutput("slow_result1", None)
+
+    def slow_task2(ctx):
+        time.sleep(0.5)  # Sleep for 500ms
+        return TaskOutput("slow_result2", None)
+
+    flow.add_task("task1", task1)
+    flow.add_task("slow_task1", slow_task1)
+    flow.add_task("slow_task2", slow_task2)
+
+    start_time = time.time()
+    result = flow.run("task1")
+    execution_time = time.time() - start_time
+
+    # If tasks run sequentially, it would take > 1 second
+    # If parallel, it should take ~0.5 seconds (plus small overhead)
+    assert execution_time < 0.8  # Allow some overhead but ensure parallel execution
+    assert result == {"slow_task1": "slow_result1", "slow_task2": "slow_result2"}
+
+
+def test_run_with_inputs(flow):
+    # Test running tasks with initial inputs
+    def task1(ctx):
+        assert ctx.get("input1") == "value1"
+        assert ctx.get("input2") == "value2"
+        return TaskOutput("result1", ["task2"])
+
+    def task2(ctx):
+        # Verify inputs are still accessible in subsequent tasks
+        assert ctx.get("input1") == "value1"
+        assert ctx.get("input2") == "value2"
+        return TaskOutput("result2", None)
+
+    flow.add_task("task1", task1)
+    flow.add_task("task2", task2)
+
+    inputs = {"input1": "value1", "input2": "value2"}
+
+    result = flow.run("task1", inputs=inputs)
+    assert result == {"task2": "result2"}
+
+
+def test_correct_order_of_execution(flow):
+    # Test that tasks are executed in the correct order
+    def task1(ctx):
+        return TaskOutput("result1", ["task2", "task3"])
+
+    def task2(ctx):
+        t1 = ctx.get("task1")
+        return TaskOutput(t1 + "result2", ["task4"])
+
+    def task3(ctx):
+        t1 = ctx.get("task1")
+        return TaskOutput(t1 + "result3", ["task4"])
+
+    def task4(ctx):
+        t2 = ctx.get("task2")
+        t3 = ctx.get("task3")
+
+        return TaskOutput(t2 + t3, None)
+
+    flow.add_task("task1", task1)
+    flow.add_task("task2", task2)
+    flow.add_task("task3", task3)
+    flow.add_task("task4", task4)
+
+    result = flow.run("task1")
+    assert result == {"task4": "result1result2result1result3"}
+
+
+def test_cycle(flow):
+    # Test that cycles are detected and handled
+    def task1(ctx):
+        c = ctx.get("count")
+
+        if c == 3:
+            return TaskOutput("result1", ["task3"])
+
+        return TaskOutput("result1", ["task2"])
+
+    def task2(ctx):
+        c = ctx.get("count")
+        ctx.set("count", c + 1)
+        return TaskOutput("result2", ["task1"])
+
+    def task3(ctx):
+        return TaskOutput("final", None)
+
+    flow.add_task("task1", task1)
+    flow.add_task("task2", task2)
+    flow.add_task("task3", task3)
+
+    result = flow.run("task1", inputs={"count": 0})
+    assert result == {"task3": "final"}
diff --git a/uv.lock b/uv.lock
new file mode 100644
index 0000000..4cb02e8
--- /dev/null
+++ b/uv.lock
@@ -0,0 +1,1244 @@
+version = 1
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+    { name = "aiosignal" },
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+    { name = "attrs" },
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