Your Team Uses AI Every Day.
Most of Them Are Getting
3% of Its Value.
The productivity ceiling isn't the AI. It's the absence of a system — custom modes, reliable workflows, eval loops, and the confidence to push AI into every SDLC phase. We build that system with your team, on your real code, in three weeks.
Built on real sprints.
Measured end to end.
We embed with your engineering team for three weeks and make AI the way you build software — not a side tool some people use sometimes. Every session runs on your actual backlog, your repository, your stack. A before/after metrics report is included, and the playbook is yours when we leave.
- Custom AI modes and instructions tuned to your specific tech stack and repos
- Portable workflow playbook — AI from requirements through deployment and code review
- Eval loops and hallucination checks embedded into your CI/CD pipeline
- 100% test coverage on all AI-generated code before it merges
- Team owns the system when we leave — no ongoing dependency created
AI workflow design for your stack. Custom mode configuration per engineer. Architecture review, AI-assisted design patterns, and workflow documentation sprint.
Full-stack AI development sprints: component generation, AI-assisted testing, code review with eval loops. Before/after cycle time tracked from day one.
LLMOps integration: deploy, monitor, alert. Final metrics report comparing cycle time, coverage, and confidence before vs. after. Portable playbook handover.
From AI Foundations
to Production Agent Engineering
Four structured pathways that build on each other — or stand alone as focused intensives. All run on live tools, real use cases, and your actual stack.
AI Literacy & Prompt Engineering
How LLMs actually work, where they fail, and how to get reliable outputs. Context windows, system prompts, structured outputs — no black boxes left unexplained.
- LLM fundamentals, inference, and limitations
- Prompt engineering and structured output design
- Evaluation, iteration, and reliability patterns
- Model selection: cost vs. capability trade-offs
LLM Engineering & RAG Systems
Build AI features that work reliably in production — RAG pipelines grounded in your data, LLM APIs wired into your product, and evaluation loops that catch regressions before users do.
- RAG architecture: chunking, embedding, retrieval
- GraphRAG for multi-hop and relational knowledge
- LLM API integration with structured tool use
- Automated eval and regression testing
Agentic AI & Multi-Agent Systems
Design and build agents that plan, act, and self-correct — not scripts dressed as AI. Multi-agent orchestration with defined roles, memory, and human-in-the-loop controls for production reliability.
- Agentic patterns: ReAct, Reflection, Plan-and-Execute
- Multi-agent orchestration with LangGraph and CrewAI
- MCP for tool use and external system connections
- Memory, state management, and context scoping
LLMOps & Production AI
Ship AI that stays reliable after day one. Monitoring, drift detection, guardrails, cost management, and the incident playbook that makes your on-call team less afraid to push AI to prod.
- AI observability: tracing, logging, alerting
- Drift detection and hallucination monitoring
- Model governance, audit trails, and compliance
- Cost optimization and inference at scale
Not a Workshop.
A Capability Transfer.
We designed our training to leave no dependency behind. One engagement, one team, one system — and it runs without us from week four onwards.
On Your Real Stack
Every session runs on your actual codebase, your backlog, your tools. No synthetic demos. The skills transfer because the context is real.
Measured, Not Assumed
Before/after metrics on cycle time, test coverage, and defect density — collected from the start, reported at handover. You don't take our word for it.
You Own the Playbook
Custom AI workflows, mode configurations, and eval loops designed for your team — documented and handed over in week three. No retainer, no ongoing license.
Senior Practitioners
Engineers with production AI experience coaching your team — not instructors reading from slides. They've shipped the things they teach.
Domain-Ready
Healthcare, pharma, supply chain, and financial services tracks available — with domain-specific compliance, safety, and data sensitivity baked in.
SMB-Priced
Structured for teams of 5 to 50. You don't need enterprise L&D budgets to get enterprise-grade AI engineering capability.
Tech Stack We Teach Across
Build the System.
Leave the Dependency Behind.
Book a free 30-minute discovery call. We'll identify your team's readiness level, agree on the right pathway, and show you what the programme looks like on your actual stack.
Response within 1 business day · No lock-in · You own the playbook