TrainingNew
AI Agents for Teams
AI Agents for Teams is our premium 2-day training where we build working AI agents for your team. By 2026 agents have hit production — Claude Computer Use drives desktops, ChatGPT Agent completes web tasks, custom agents integrate via MCP. Day 1 is agent strategy and tool mapping; Day 2 we build at least one working agent for your workflow alongside you.
Tools
Claude Computer Use
ChatGPT Agent
Claude Code
OpenAI Codex
MCP
Devin
Manus
n8n + AI
Cline
Who it's for
This training fits if…
- Tech leaders (CTO, VP Engineering, IT directors) evaluating agent architecture
- Product owners and CEOs wanting agents in specific workflows
- Internal-tools and platform teams building their own agents
- Non-technical leaders evaluating agent ROI (Day 1 only)
Outcomes
What you take away.
- Understand agent architecture (loop, tool use, verifier, eval) and when to choose what
- Know the 2026 landscape: Claude Computer Use, ChatGPT Agent, Devin, Manus, Cline
- Identify at least 3 agent opportunities in your company with ROI estimates
- Build a working agent with us (MCP server + agent loop)
- Deploy agents safely (permissions, audit, sandbox)
- Take home an agent-rollout playbook and eval suite
Curriculum
Training modules.
01
What is an AI agent — 2026 concepts
- · Taxonomy: chatbot vs assistant vs agent vs autonomous agent
- · Agent architecture: model, tools, memory, verifier
- · Tool use (function calling, MCP, computer use)
- · Long-term memory and context management
02
The 2026 agent toolset
- · Claude Computer Use — desktop agent in practice
- · ChatGPT Agent and Operator — browser agents
- · Devin, Manus, Cline — autonomous engineers
- · Custom GPTs and Claude Projects vs real agents
- · n8n + AI nodes: low-code agents
03
MCP — the agent backbone
- · Model Context Protocol — connecting agents to systems
- · Existing MCP servers (Postgres, GitHub, Slack, Linear, Jira, Notion)
- · Building your own MCP server (Python / Node.js)
- · Permissions, audit and security
04
Mapping agent opportunities in your company
- · Workflow audit — what's automatable, what isn't
- · ROI assessment: time saved vs error risk
- · Prioritisation: where to start
- · 3 concrete agent specs for your team
05
Day 2 — we build an agent
- · One of your specs → working agent
- · MCP server for your data source
- · Agent loop wiring (Claude API + tools)
- · Eval suite: quality and regression
- · Deployment and monitoring
06
Security and compliance
- · EU AI Act 2026 — what applies to agent systems
- · GDPR data flow in an agent
- · Permissions model: scoping what agents can do
- · Audit and observability in production
FAQ
Frequently asked questions.
Ready to book?
Let's first map your team's needs — the first consultation is free.