Guides from the studio

AI automation uses language models to handle the unstructured parts of business work alongside rule-based automation. What it is, where it fails, what it costs.

An AI agent is a language model with a goal, tools and rules. How the reason–act–observe loop works, where agents fail, and how to deploy one safely.

A practical guide to AI automation for small and mid-sized businesses: which tasks to automate first, how to measure the return, and what it costs.

What an AI calling agent is, what it can and cannot do today, how it connects to your booking or CRM system, what it costs to run, and how to introduce one.

How AI software is built in practice: retrieval, tools, evaluation, guardrails and monitoring around the model, from pilot to production, and how to choose a partner.

When custom software beats off-the-shelf, what a project involves, realistic costs and timelines, and the questions to ask a software company before signing.

A practical method for automating a business: map the work, rank the tasks, choose rules versus AI versus people, build or buy, launch with a checkpoint, measure.

CRM manages the customer relationship; ERP runs the operation. The differences, the overlap, when you need one, both, or a custom system, and how they connect.

The decisions behind a SaaS platform in the order they matter: tenancy, auth, billing, roles, stack and operations, with real costs, from a studio that runs one.

How to choose restaurant POS software: speed at the till, offline resilience, QR ordering, kitchen display, inventory, integrations, multi-venue reporting, cost.

The AI that helps a restaurant today: voice agents for reservations, WhatsApp ordering, prep forecasting, invoice-to-inventory, reviews and plain-language reports.