Building AI infrastructure, in plain language.
Short, image-led notes on shipping AI features that stay running.
- ·5 min read
AI automation for small business: where to start
A practical guide to picking the first AI automation that pays for itself — for founders and small teams without a dedicated ops department.
- ·6 min read
n8n vs Make vs Zapier: how to choose in 2026
Honest trade-offs between n8n, Make, and Zapier for real production workflows — pricing, control, AI support, and when to outgrow them.
- ·5 min read
How to build an AI chatbot for your website
A clear blueprint for shipping a useful AI chatbot on your site — data sources, guardrails, model choice, and the metrics that matter.
- ·6 min read
10 AI workflow automation examples that actually ship
Real, useful AI workflow automations across sales, support, ops, and content — with the trigger, tools, and outcome for each.
- ·6 min read
OpenAI API integration guide for production apps
How to integrate the OpenAI API into a real product — keys, rate limits, retries, cost control, streaming, and the gotchas docs gloss over.
- ·3 min read
Shipping an AI agent in two weeks
A no-drama playbook for getting a useful AI agent into production fast — scope, guardrails, and the boring infra around it.
- ·5 min read
Shipping a SaaS MVP with AI in 30 days
A realistic 30-day plan for taking an AI SaaS idea from blank page to paying users — scope, stack, and the cuts you have to make.
- ·4 min read
RAG that actually answers
Most RAG systems retrieve plausible chunks and produce confident nonsense. Here's what changes that.
- ·5 min read
AI agents for customer support that don't make customers angry
How to deploy an AI support agent that actually helps — scoping, escalation design, tone, and the metrics that prove it's working.
- ·3 min read
When workflow tools stop scaling
Visual builders are great until they aren't. Signals it's time to graduate parts of your stack to real code.
- ·6 min read
Vector database comparison: pgvector, Pinecone, Qdrant, Weaviate
How to choose a vector database in 2026 — pgvector vs Pinecone vs Qdrant vs Weaviate, with honest trade-offs for production AI apps.
- ·4 min read
Designing an AI-ready data layer
Before you bolt an LLM onto your app, get the data underneath it into a shape models can actually use.
- ·5 min read
Automate lead qualification with AI (without breaking your funnel)
A field-tested blueprint for AI lead qualification — enrichment, scoring, routing, and human-in-the-loop checks that protect conversion.
- ·3 min read
Evals before launch
If you can't measure your AI feature, you can't safely ship it. A pragmatic guide to evals for small teams.
- ·5 min read
FastAPI vs Node.js for AI backends
An honest comparison of FastAPI and Node.js for building AI backends — performance, ecosystem, streaming, and team fit.
- ·4 min read
AI app architecture cheat sheet
The handful of components every production AI app ends up with, and how they fit together.
