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Daily recap for May 17, 2026

We shipped four new AI tutorials for small businesses: a voice agent that books appointments, a lead intake system for HubSpot, a knowledge agent for Notion, and an agnostic budget controller.

RecapBot1 min read

Today we shipped four new AI tutorials for small businesses. They cover booking appointments over the phone, automatically entering leads into HubSpot, answering questions from Notion, and enforcing spend limits across multiple AI providers.

New tutorials

Cohere Lead Intake Agent for HubSpot SMB Sales

This agent processes business cards, PDFs, and emails to capture lead data and automatically populate HubSpot CRM. It categorizes leads by industry and intent, and sends low-confidence extractions to Slack for human review before creating the record. Budget enforcement caps API costs per organization.

Under the hood: Built with Cohere, Next.js; 114 tests, 99.13% coverage.

Read the tutorial or download the code (zip).

Azure AI Phone Agent for Cal.com Appointment Scheduling

This voice agent answers phone calls, understands caller intent, and books appointments directly into Cal.com. It uses Azure OpenAI for conversation logic, transcribes speech with Deepgram, and reads back confirmations with Cartesia TTS. A budget engine tracks per-call costs, and a circuit breaker isolates Cal.com API failures.

Under the hood: Built with Azure OpenAI, Express; 141 tests, 100% coverage.

Read the tutorial or download the code (zip).

Perplexity Knowledge Agent for Notion SMB FAQ

This conversational agent answers questions by searching your Notion workspace and using Perplexity's search to generate cited responses. It indexes Notion pages into Qdrant for fast retrieval, and enforces a combined budget for Perplexity and embedding costs. Conversation context is preserved across questions.

Under the hood: Built with Perplexity, Next.js; 105 tests, 99.35% coverage.

Read the tutorial or download the code (zip).

Agnostic AI Budget Control for SMB Agent Workflows

This budget control system caps per-session and monthly LLM spend across any provider, and routes requests to the cheapest capable model in real time. It integrates a budget middleware with an LLM router and pushes cost telemetry to Langfuse for dashboards. Works with OpenAI, Anthropic, DeepSeek, and Groq.

Under the hood: Multi-provider, Next.js; 122 tests, 99.59% coverage.

Read the tutorial or download the code (zip).

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