How to choose an AI consulting agency in Italy
A practical guide to choosing an AI consulting agency: the right questions to ask, how to tell who delivers from who sells smoke, realistic costs and a checklist so you don’t get the first project wrong.
Claude, GPT or Gemini: which AI model to choose for your company
Claude, GPT or Gemini for your company? It depends on the use case, not the brand: a practical comparison on reasoning, coding, cost, privacy and why the best choice is often a multi-model approach.
GEO: getting cited by ChatGPT, Perplexity and AI Overviews
GEO is optimization for answer engines: how LLMs pick their sources and which concrete tactics we apply on aicircus.it to get found and cited, from content structure to llms.txt files.
What an AI agent really costs in a company
The real cost drivers of an AI project for SMEs: discovery, model, build, integration, infrastructure and maintenance, with realistic ranges and when a simple automation is enough.
AI for SMEs: 6 use cases that pay back in 90 days
Six concrete artificial intelligence applications for small and medium businesses, with realistic return figures within three months and an honest look at when it is not worth it.
Vibe coding: writing software with Claude Code
How we changed our development process by pairing Claude Code with senior developers. Timings, output, where it works and where it does not — no hype.
RAG for small companies: do you really need it?
When Retrieval Augmented Generation is the right answer, and when it is just another expensive way to say "we searched through your documents".
How to structure an internal AI Audit
The template we use for our AI Audits. Questions to ask the team, processes to map, how to estimate ROI without making salesperson promises.
Building a customer service agent that does no harm
Patterns and anti-patterns for front-line AI agents. When to let the AI talk to the end customer, and when to keep it only in support of the human team.
Multi-agent: when one model is not enough
Patterns for orchestrating multiple AI agents: pipelines, supervision, debate. When the complexity pays off and when a single prompt is enough.