Map workflows, automate E2E tests, and ship faster with QA Wolf (Sponsored)QA Wolf’s AI agent maps and tests your app’s most complex user flows. It turns your prompts into real Playwright and Appium code that runs 12x faster and more reliably than other computer-use agents. What sets our AI apart:
This week’s system design refresher:
RAGs vs AgentsAsk an LLM about your company's data and it will guess. The two patterns that fix this are RAG and agents, and they solve different problems. RAGs: RAGs combine LLMs with retrieval to ground answers in 4 steps.
One retrieval. One generation. Cheap, predictable, and easy to debug. Agents: Agents wrap LLMs in a reasoning loop with tools to take action.
More flexible. More tokens. Harder to debug because errors drift across steps. The rule of thumb: Use RAG when the answer lives in your documents. Use an agent when the answer requires action on other systems. Over to you: When do you prefer RAG over agent? Build with Claude Code: New Cohort LaunchWe’re launching a new 2 day intensive, cohort based course called Build with Claude Code, taught by John Kim, who has trained hundreds of engineers at Meta to use Claude Code in real production workflows. The course starts soon on May 28. |