Corporate AI program
Agentic AI Training for Enterprises
For: Software engineers, ML engineers, solution architects and technical product teams.
In short
AI Anytime's Agentic AI Training teaches engineering teams to design, build, evaluate and deploy AI agents — LLM systems that plan, call tools, use memory and work together. Participants build agents with tool calling, the Model Context Protocol (MCP), multi-agent orchestration and human-in-the-loop guardrails, and finish with a working agent on your own use case.
What your team will be able to do
- Understand when to use a workflow, a single agent or a multi-agent system
- Build agents with tool calling, structured output and memory
- Expose internal systems to agents through MCP servers
- Evaluate, trace and guard agents before production
- Ship a working agent prototype on a real company use case
Capstone
Teams build and demo a production-shaped agent on a company use case — with tools, an MCP integration, evals and a deployment plan.
Tools & stack
Curriculum
Program modules
A typical outline — every program is tailored to your team's roles, tools, data policies and use cases after a scoping call.
- 01
Agent fundamentals
- The agent loop: reason, act, observe
- Workflows vs agents — choosing the simplest thing that works
- Structured outputs and tool calling across OpenAI, Anthropic and Gemini APIs
- 02
Tools, context & MCP
- Designing good tools for agents
- Building and consuming MCP servers
- Context engineering: retrieval, memory and state
- 03
Frameworks & orchestration
- LangGraph, CrewAI, OpenAI Agents SDK, Claude Agent SDK, Google ADK
- Multi-agent patterns: supervisor, hand-off, swarm
- Long-running and durable agents
- 04
Evaluation, safety & guardrails
- Agent evals, traces and regression tests
- Prompt injection and tool-permission design
- Human-in-the-loop approvals and cost control
- 05
Deploying agents
- APIs, queues and background jobs
- Observability with Langfuse / LangSmith / OpenTelemetry
- Rolling out to real users safely
FAQs
Agentic AI: frequently asked questions
Still have questions? Talk to our team — we reply within one working day.
What is agentic AI training?
Agentic AI training teaches developers to build AI agents: LLM-powered systems that plan steps, call tools and APIs, use memory, and act with some autonomy. It covers design patterns, frameworks, MCP, evaluation and safe deployment.
Which agent frameworks do you teach?
We teach the patterns first, then implement them in the frameworks your team uses — commonly LangGraph, OpenAI Agents SDK, Claude Agent SDK, Google ADK, CrewAI or plain Python. We stay framework-neutral.
What are the prerequisites for agentic AI training?
Working Python and basic API experience. Prior LLM experience helps but isn't required; we can add a half-day LLM fundamentals primer.
Can the agent capstone use our internal data and systems?
Yes — ideally. We can run labs inside your environment, on your cloud and model endpoints (Azure OpenAI, AWS Bedrock, Vertex AI or on-prem), under your security policies.
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Next step
Bring Agentic AI to your team.
Tell us who you want to upskill and what outcome you need. You'll get a tailored proposal — curriculum, format, trainers and pricing — within 48 hours.