You don't necessarily need to hire a Head of AI. But you probably need someone thinking like one.
AI is now becoming an organisational capability rather than an isolated IT project. In practice, someone needs a working view of what AI can realistically do, where it can create measurable value, what data it needs, what risks it introduces, which tools employees are already using, and how today's experiments become tomorrow's reliable systems.
Gaming Mechanics can provide that capability as an external Head of AI / AI Technology Adviser. We work alongside your leadership and technical teams to turn AI from a collection of experiments into a coherent capability.
Leads our AI practice and presents practical AI talks and workshops through Google Developer Groups Douglas.
AI audit
Understand how your organisation already uses AI, including unofficial or unmanaged use.
AI opportunity mapping
Identify processes where AI could save time, reduce cost, improve service or create new capabilities.
AI architecture
Determine whether each use case belongs on a public API, private cloud, local model, traditional software system or some combination.
AI governance
Create practical rules for acceptable AI use, data handling, human oversight, security and accountability.
AI roadmap
Prioritise projects by business value, feasibility, risk, and expected return.
Technology selection
Evaluate models, frameworks, APIs, local AI options and agent platforms without tying the strategy to a single vendor.
Implementation oversight
Help your internal team or development partner turn promising experiments into production systems.
Ongoing advice
AI changes quickly. We can remain involved as an external technical adviser as your organisation's AI capability develops.
AI is moving from answering questions to doing things.
The first generation of generative AI applications largely answered prompts. The next generation can reason about a goal, use tools, retrieve information, interact with systems and take actions. That changes the engineering problem.
The system around the model matters more than the model itself: tools, permissions, memory, data, orchestration, monitoring, security and human oversight. Gaming Mechanics designs and builds these systems.
We have practical experience with modern agent architectures, including Google's Agent Development Kit (ADK), model/tool orchestration, memory and personalisation, and production-oriented cloud architectures.
We don't build agents because agents are fashionable. We look for a process worth improving, then work out whether an agent is the right tool for it.
- 01investigate a customer query
- 02retrieve information from internal systems
- 03analyse documents
- 04check business rules
- 05create a draft response
- 06update a CRM
- 07prepare a report
- 08notify a member of staff
- 09or coordinate several specialised AI agents to complete a larger task
What surrounds the model
We are software engineers who understand AI, not an AI consultancy that learned to build software.
AI is becoming embedded into software. That means the organisations that benefit most will need more than prompt engineering.
We already design and build software systems. AI is another powerful capability we can integrate into those systems.
We've been exploring these questions in public.
Our approach to AI isn't purely theoretical. Gaming Mechanics' Founder & CTO, Felipe Ceotto, has presented practical AI talks and workshops through Google Developer Groups (GDG) Douglas.
ChatGPT, But in Your Shed
A hands-on introduction to running large language models locally, including a live demonstration of a ChatGPT-style application running against a locally hosted model. The session explored why organisations might want to run AI outside the cloud, different approaches to hosting local models, and what becomes possible when AI runs on infrastructure you control.
Read about the talk →Google AI Agents: Your Next Intern?
An introduction to Google's Agent Development Kit, exploring what AI agents are, how agentic systems differ from conventional LLM applications, multi-agent architectures, tool use, memory, personalisation and safety.
Read about the talk →Agent Development Kit (ADK) Workshop
A practical, hands-on workshop exploring how to design, build, evaluate and deploy AI agents using Google's Agent Development Kit.
Read about the workshop →Who Owns the Picture? AI Illustration, Public Domain, and the Ethics of Automated Creativity
A practical exploration of AI-generated creativity followed by a discussion around copyright, public-domain material, consent, artistic ownership and the ethical boundaries of automated creativity.
Read about the talk →These talks reflect an important part of our philosophy: AI is not just a technology problem. It's also a data, business, security, ethical and human problem.
The Agentic Shift
Our “Agentic Shift” series explores the move from passive LLM applications towards production-grade autonomous agents, including reasoning, tool use, secure APIs, orchestration, memory and observability.
Ready to work out what AI should actually do for your business?
You don't need another AI demo. You need to know where AI can help, what it will cost, what data it needs, what risks it introduces, and what to build next.
Gaming Mechanics can help you answer those questions and, when there is a genuine opportunity, build the system that follows.