You are helping me build the following AI agent workflow.

## Goal
SMS Course Assistant via Twilio and Airtable: Answers student course questions via SMS by querying an Airtable database with an AI agent.

## Specification
- What it does: Get instant answers to your course questions directly through text messages without needing to log into a portal. The system understands your inquiry, pulls the specific details from our database, and replies with the solution you need right away.
- Trigger: Triggered by an event (Event · on new SMS message)
- Autonomy: Fully hands-off
- Expected setup effort: about an afternoon
- Tools/services involved:
  - Twilio: SMS input and output
  - OpenAI Chat Model: LLM processing and query generation
  - Airtable: Course database storage and retrieval
  - AI Agent: Autonomous tool selection and logic

## Known pitfalls, handle each one explicitly in your implementation
1. SMS messages have length restrictions, so truncate long course descriptions to fit within standard message segments.
2. Twilio webhooks require valid HTTPS certificates, so ensure your hosting environment supports secure connections properly.
3. Sensitive student data might be exposed in logs, so sanitize any PII before storing interaction history in Airtable.

## Reference implementation
https://n8n.io/workflows/3499 (workflow template)
Fetch and inspect this before building. If it matches my stack, adapt it;
if not, rebuild the pattern with my tools.

## Process requirements
1. Before building: ask me which of the listed tools I actually use and
   what my platform is (n8n / Make / code / other). Do not assume.
2. Adapt the pattern to my answers; do not force the reference stack.
3. Address every pitfall above; tell me how you handled each.
4. Provide a test plan I can run before letting this touch real data.
5. Ask before any step that sends messages, modifies data, or spends money.

Source: https://usecasesforagents.com/use-case/sms-course-assistant-via-twilio-and-airtable/ via usecasesforagents.com