Originally published on Towards AI.
First: What Problem Does AsyncIO Solve?
Adding async and await to your code doesn't make it asynchronous. It makes it eligible to be asynchronous. There's a big difference and it bites almost everyone the first time.
The article explains that AsyncIO is designed to improve performance for I/O-bound workloads by using cooperative multitasking: while tasks are waiting, the event loop can run other pending work rather than blocking a single thread. It walks through how the event loop schedules coroutines and why yielding only happens at proper await points. It also clarifies common failure modes—using sequential awaits when concurrency is needed, accidentally blocking the event loop with synchronous libraries or CPU-heavy work, forgetting to actually run the event loop, and mixing sync/async incorrectly. Through a real FastAPI “before vs after” example and a mental model, the piece shows that async/await are signaling mechanisms, not speed buttons, and real parallelism requires launching multiple coroutines concurrently (e.g., with asyncio.gather or create_task).
Read the full blog for free on Medium.
Published via Towards AI
Towards AI Academy
We Build Enterprise-Grade AI. We'll Teach You to Master It Too.
15 engineers. 100,000+ students. Towards AI Academy teaches what actually survives production.
Start free — no commitment:
→ 6-Day Agentic AI Engineering Email Guide — one practical lesson per day
→ Agents Architecture Cheatsheet — 3 years of architecture decisions in 6 pages
Our courses:
→ AI Engineering Certification — 90+ lessons from project selection to deployed product. The most comprehensive practical LLM course out there.
→ Agent Engineering Course — Hands on with production agent architectures, memory, routing, and eval frameworks — built from real enterprise engagements.
→ AI for Work — Understand, evaluate, and apply AI for complex work tasks.
Note: Article content contains the views of the contributing authors and not Towards AI.