If you are building apps with LLMs, you already know the pain: generation takes seconds, and users hate waiting.
Today, I fixed the latency of my AI Financial Agent by implementing the Asynchronous Worker Pattern** using Amazon SQS.
The Problem
My AWS Lambda was running synchronously:
Fetch Bank Data -> Run Heavy AI Prompt -> Generate Email -> Return UI Data.
This caused 5+ second load times and occasional API timeouts.
The Solution
I split my Python lambda_handler to detect the event source.
If the request comes from API Gateway (React Frontend), it bypasses the heavy AI email generation completely and returns the dashboard data instantly.
If the request comes from my EventBridge daily cronjob, it acts as a Fan-Out orchestrator:
Scans DynamoDB and queues the heavy work
for user in users:
sqs.send_message(
QueueUrl=SQS_QUEUE_URL,
MessageBody=json.dumps({"task": "daily_report", "user_id": user['user_id']})
)
Then, SQS automatically invokes the Lambda in the background to handle the heavy Bedrock processing and SES email delivery.
By decoupling the architecture, UI latency dropped by over 70%. Stop making your users wait for background tasks! Have you implemented SQS in your serverless apps yet?
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