Build AI Apps with Python: Safe AI Agents — Input Validation and Output Filtering | Episode 21

An unguarded agent is a liability. Add three safety layers: block bad input, redact sensitive output, control which tools run. We build guardrails for an AI agent from scratch. An input validator blocks dangerous keywords and enforces length limits. An output filter uses regex to redact SSNs, credit card numbers, and emails. A tool allowlist ensures only approved tools can execute. Four test cases prove each layer works — normal requests pass, blocked topics are rejected, sensitive data gets redacted, and unauthorized tools are denied. Student code: https://github.com/GoCelesteAI/build-ai-apps-python/tree/main/episode21 Every keystroke is shown on screen with 3-second pauses so you can follow along at your own pace. What You'll Learn: • Input validation with keyword blocklist • Length limit enforcement • Output filtering with regex patterns • Redacting SSNs, credit cards, and emails • Tool allowlist pattern • Three-step guarded agent pipeline • Testing guardrails with blocked and allowed inputs Key Takeaways: 1. Input guardrail blocks before Claude sees it — rejected requests never reach the API 2. Output guardrail redacts after Claude responds — sensitive data replaced with [REDACTED] 3. Tool allowlist controls what runs — only approved tools execute This is Episode 21 of Build AI Apps with Python in Neovim — Phase 4 (AI Agents). Taught by CelesteAI. Like & subscribe for more tutorials! #python #ai #guardrails #agentsafety #inputvalidation #outputfiltering #claudeapi #anthropic #neovim #programming #tutorial #machinelearning #artificialintelligence #coding #pythontutorial #buildaiapps #llm #genai #toolallowlist Tags python agent guardrails, ai safety python, input validation ai, output filtering, tool allowlist, claude api safety, anthropic sdk, agent guardrails python, ai tutorial 2026, build ai apps python, neovim tutorial, generative ai python, screenkey, code along, redact sensitive data