Parallel Tool Calling
Master concurrent tool execution to build faster, more efficient AI agents
Your Progress
0 / 5 completedThe Shared State Problem
When multiple tools run in parallel and modify the same data, race conditions can occur. The result depends on unpredictable timing — a recipe for bugs!
What is a Race Condition?
counter = 0 // Shared state
Thread 1
1. Read counter (0)
2. Add 1
3. Write back (1)
2. Add 1
3. Write back (1)
Thread 2
1. Read counter (0) ⚠️
2. Add 1
3. Write back (1) ⚠️
2. Add 1
3. Write back (1) ⚠️
⚠️ Expected: counter = 2 | Actual: counter = 1
Thread 2 read the old value before Thread 1 wrote its update!
Interactive: Race Condition Simulator
See how different synchronization strategies prevent race conditions
No Protection
Both threads modify shared state freely
Risk: HIGH
Locks/Mutexes
Only one thread can access at a time
Risk: LOW
Immutable Data
Never modify, always create new copies
Risk: NONE
Message Passing
Communicate via messages, not shared memory
Risk: NONE
Prevention Strategies
🔒
Locks/Mutexes
Only one thread can access the shared resource at a time. Others wait their turn.
lock.acquire() → modify_data() → lock.release()
🧊
Immutable Data
Never modify data. Always create new copies with changes.
new_data = old_data.copy() → new_data.modify()
📬
Message Passing
Share data by sending messages, not by accessing shared memory.
channel.send(data) → other_thread.receive()
⚛️
Atomic Operations
Operations that complete in a single, uninterruptible step.
counter.atomic_increment() // Read + modify + write as one