HeyJaredSystem Design Classroom
A System Design Newsletter to help you build better software.
- Indexed issues, last 90 days
- 5
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- Sep 26, 2026
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- Jul 11, 2026
Latest issues
AI Agents Just Rediscovered the Dual-Write Problem (opens the original)
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This agentic case starts with a request no business owner wants, but still we should plan for: a customer asks an AI support agent for a refund.And the agent does exactly what it is told to do: it loads the order, it reads the refund policy, and it confirms that the request qualifies. Then it receives approval and calls the payment provider.The provider does its job too and creates the refund.But then, just before the agent records the result, the process ends up crashing.A few seconds later, th
The Most Dangerous Agent Memory Was Once Correct (opens the original)
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When I think about agent memory, I don’t think about a chatbot forgetting someone’s favorite color. I think about an agent applying information that was once correct.Imagine your e-commerce store reduced returns from 30 to 14 days for orders placed after September 1.A customer asks if an order that arrived yesterday can be returned in three weeks. The agent says yes. It found a real 30-day return policy, but missed that the policy had expired. Now the customer expects a return the store may reje
Your AI Agent Won’t Crash. It Will Happily Pay an Invoice Without Approval (opens the original)
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At some point, you’ll get the call from above:“We need an AI agent to handle [fill this with whatever you like].”A team I know reached out to me for help; they had an acquisition and needed to process invoices from several companies, each with different formats and approval policies.The idea was to replace 167+ if statements with specialized agents. I got it; the agents could decide which workflow applied.They already had logs, metrics, and distributed traces. By “traditional standards”, they we
Safe Database Rollback Starts Before Deployment (opens the original)
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Everybody explains how to migrate a database.Add a column. Create an index. Rename a field. Transform existing rows. Deploy the new application version.But few people are focused on what happens when the deployment fails after the migration has already changed production data.Imagine that version 2 of your application introduces a new database schema. The migration completes successfully, traffic reaches the new version, and users begin creating records using the new structure.Ten minutes later,
How to Survive the Recommendation Engine Question (opens the original)
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The fastest way to fail the recommendation engine question is to spend all your time designing the matching algorithm.That is the trap.Most engineers hear “recommendation engine” and immediately think about collaborative filtering, embeddings, similarity scores, ranking models, or machine learning.Those things matter.But they are not where the system design answer usually wins.The recommendation engine question is not asking whether you can invent the perfect algorithm in 45 minutes.It is asking
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