AI projects

Role
Developer
Year
2026
Stack
MCP, LLM agents, TypeScript
Status
In progress

Four LLM agents I'm building on top of Vallon, a system beauty centers already use every day.

Vallon MCP Server: how it works

  1. The customer asks their assistant for an appointment.
  2. The assistant calls Vallon's MCP tools to find free times.
  3. The customer picks a time and the booking is created in Vallon.
  4. The center sees it on the iPad like any other booking.

Stack: MCP (TypeScript SDK), Vallon booking API, OAuth

AI Support Agent: how it works

  1. A center owner asks a question.
  2. The agent searches the product documentation and answers with the source.
  3. For a technical issue, it asks which steps led to it.
  4. It opens a ticket with what the team needs to reproduce the issue.

Stack: RAG with a vector database, Claude Agent SDK, evals with LLM-as-judge

WhatsApp Booking Agent: how it works

  1. A customer messages the center on WhatsApp.
  2. The agent checks availability in Vallon.
  3. It books the time and confirms in the same chat.
  4. Anything it can't handle goes to the center's staff.

Stack: WhatsApp Cloud API, LLM tool use, Vallon API

Customer data is handled under Saudi Arabia's Personal Data Protection Law.

SOP Agents: how it works

  1. Each procedure is written as clear steps.
  2. Code moves the customer from one stage to the next.
  3. Inside each stage, an agent follows the procedure.
  4. A team member approves the key steps.

Stack: State machine in code, LLM agents, human approval steps

Currently studying

  • RAG and vector databases
  • LangChain
  • LangGraph
  • Hugging Face
  • QLoRA fine-tuning
  • Claude Agent SDK
  • Evals with LLM-as-judge
  • Langfuse, DeepEval, promptfoo
  • Agent security
  • AWS Bedrock AgentCore

I'll add course projects here as I finish them.

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