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Building AI Agents on an LAC Small-Business Budget

Created by Adrian Dunkley | maestrosai.com | ceo@maestrosai.com | Fair Use

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Pick your path

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No-code path

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Options

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What you can and can’t do

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A 60-minute no-code build

1. Open ChatGPT, click “Create a GPT”.
2. Paste a goal and style guide in Spanish (use the template from design.md).
3. Upload your menu, hours, FAQs, and delivery zones as knowledge files.
4. Add 5 example conversations under “Conversation Starters”.
5. Test with 10 real customer messages. Fix the instruction on any miss.
6. Share the link with your staff. Done.

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Low-code path

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Options

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The typical low-code agent

1. Trigger: WhatsApp message received, email arrived, row added to a sheet.
2. LLM call: Pass the message to Claude or GPT with a system prompt.
3. Decide: Parse the LLM output. Branch on the intent.
4. Tool step: Call WhatsApp Business API, Sheets, HubSpot, a payment API.
5. Reply or log.
6. Loop or stop.

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Sample pricing for an LAC SMB

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A low-code starter: WhatsApp booking agent in n8n

1. Connect WhatsApp Business API to n8n as a trigger.
2. Pass the incoming message to a Claude Haiku 4.5 node with a booking-specific system prompt.
3. If the LLM returns intent “BOOK”, call a Google Calendar node to check availability.
4. If free, call a Stripe (or PayPal) node to generate a payment link.
5. Send the link back via WhatsApp.
6. On payment webhook, add the booking to the calendar and send confirmation.
7. If the LLM returns intent “OTHER”, forward the message to the owner’s phone.

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Code path

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SDKs and frameworks in 2026

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When to use which

• Claude Agent SDK: if the agent needs long-running tasks, computer use, or skills. Default choice for most business agents.
• OpenAI Agents SDK: if you’re already on OpenAI, want their Responses API, or need multi-agent handoffs.
• LangGraph: if you want provider-agnostic code and explicit control over state and branching.
• CrewAI: if you want to prototype a multi-role team (researcher + writer + reviewer) in an afternoon.

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Hosting options for LAC

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A minimal Claude Agent SDK example

from anthropic import Anthropic
from anthropic.lib.agents import Agent, tool

client = Anthropic()

@tool
def check_calendar(date: str) -> str:
    """Return available slots for a given date."""
    return "10:00, 14:00, 16:00"

@tool
def send_whatsapp(to: str, message: str) -> str:
    """Send a WhatsApp message via the Business API."""
    return "sent"

agent = Agent(
    model="claude-sonnet-4-6",
    system="You book tour reservations for a Jamaican tour operator. "
           "Reply in the customer's language. Always confirm before booking.",
    tools=[check_calendar, send_whatsapp],
    max_steps=15,
)

response = agent.run("Hi, do you have spots for 2 on Saturday at noon?")
print(response.final_message)

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Cost math the LAC business owner should do

1. Hours saved per week = H
2. Your hourly value in USD = V
3. Monthly platform + API cost = C
4. Monthly savings = H * 4 * V
5. Keep only if: monthly savings > 3 * C

• Savings: 8 * 4 * 25 = $800/mo.
• Cost: $45/mo.
• Ratio: 17x. Build it.

• Savings: 1 * 4 * 8 = $32/mo.
• Cost: $40/mo.
• Ratio: 0.8x. Skip it. Use a free Custom GPT instead.

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Security, privacy, and compliance basics

• Never let the agent execute actions without a confirmation step for anything that sends money, deletes data, or contacts customers.
• Log every tool call for 30 days minimum. This is your audit trail if a customer disputes a booking or a charge.
• Mask PII in logs sent to third-party platforms.
• Comply with local data-protection law. See governance/README.md.
• Document the agent: what it does, what it can’t, and who to contact when it goes wrong.

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Graduating from one path to the next

• No-code to low-code: you hit “I wish this could talk to my WhatsApp” or “I need this to run at 2am”.
• Low-code to code: you hit “I need a custom tool the platform doesn’t offer” or “data can’t leave my country”.

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Next step