Guides and honest comparisons for AI automation.
Practical writing on n8n, Zapier, Make, applied LLM products, and conversational AI in production. Written from live systems, not demos.
Latest articles
What is an AI automation engineer
An AI automation engineer builds production systems that combine LLMs, workflow tools like n8n, and business data. Here is what the role covers and when to hire one.
Open article →n8n vs Zapier vs Make in 2026
Honest comparison of n8n, Zapier and Make for real production automation in 2026. Ownership, cost at scale, AI features, and when each one is the right call.
Open article →Why n8n workflows fail silently, and how to catch it before your client does
n8n does not tell you when a workflow fails quietly. Here are the five failure modes that skip the error output, and the monitoring setup that catches them anyway.
Open article →Using Claude to triage support tickets before a human ever sees them
How Claude fits into a support ticket triage pipeline: classify, draft, route, and log, with a human review gate before anything reaches a customer.
Open article →How an AI voice agent handles outbound debt collection calls end to end
A technical walkthrough of an outbound voice AI collections system: lead ingestion, calling windows, voicemail branching, SMS fallback, and DTMF payment capture.
Open article →Turning a phone call into a Shopify order with voice AI
How a voice AI agent takes a phone order and creates it directly in Shopify through the GraphQL API, with DTMF confirmation on the numbers that matter.
Open article →Why conversational routing beats a phone tree menu
A voice AI receptionist that asks what a caller needs instead of forcing them through a menu, routes to the right department, and resolves simple queries itself.
Open article →Building and testing a voice AI agent across languages
The practical challenges of shipping a voice AI agent that works reliably in more than one language, from an eligibility screening build in the energy sector.
Open article →Why we don't call it 'voice AI' to every client
Why an after hours call assistant for a local services business gets called an 'AI call assistant', not 'voice AI', and why that framing decision matters for trust.
Open article →The difference between a LinkedIn bot and a LinkedIn automation that actually converts
Most LinkedIn automation gets accounts flagged or cannot hold a real conversation once someone replies. Here is what separates a bot from a system that converts.
Open article →How to automate LinkedIn engagement without it feeling automated
The two stage design behind a LinkedIn engagement engine: genuine comments first, a soft pitch only after someone replies, capped so no one gets spammed.
Open article →Running social content for multiple brands from one automation
The brand profile pattern that lets one automation generate and publish platform specific content for several businesses across LinkedIn, Facebook and Instagram.
Open article →The five table data model behind an AI email follow up system
How a five table schema, leads, contacts, conversations, messages, events, powers contextual AI email follow up at scale without losing thread history.
Open article →Where to keep a human in the loop when automating deal sourcing
Sourcing, qualification and LOI drafting can run automated. Every outbound financial commitment still needs a human approval gate. Here is the design pattern.
Open article →AI receptionist vs a custom voice AI agent, honestly
Every AI receptionist tool on the market is a self serve monthly bot. Here is when that is enough, and when a custom built voice agent is the right call instead.
Open article →Vapi vs ElevenLabs plus Twilio, honestly
Honest comparison of Vapi and the ElevenLabs plus Twilio stack for production voice AI. Latency, cost per minute, voice quality, and when each one is the right call.
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