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Description
An agent that cannot reach the systems a business already runs is a chat window. Most teams stall exactly here, because giving a model real access safely is a different problem from prompting it well. This covers Model Context Protocol end to end. Typed tools instead of scraped screens, read paths kept separate from anything destructive, credentials verified before a single write, and the failure modes that only show up in production. Built on open source MCP servers I publish for infrastructure, ERP, marketplace and booking platforms. The code is readable on GitHub before we start.
What you'll get from this package
One MCP server exposing your own system to an agent, running locally on your machine
A safety model that keeps read paths separate from anything that can destroy data
Additional details
Coaching delivered via live sessions.
Three to four sessions. We pick one system your agent needs to reach, design the tool surface together, build the server live, then test it against the cases that actually break things, a bad credential, a timeout, a malformed response.
Talk to a team member
Schedule a call with a Leland team member who can help you explore your options.
Schedule a call
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Mirza also coaches for Break Into AI Careers, AI for Data & Analytics, AI for Finance, AI for Product Development, AI for Sales & Marketing, Build with AI, and AI Services. View all.
Offered by Mirza I.
Joined February 2026
4.93
Production AI Is a Different Problem (AI & ML Engineering)
Official Mastra AI Agents Ambassador, building production RAG pipelines, MCP server connectivity, and multi-agent orchestration systems for enterprise clients. Udacity Machine Learning Engineer nanodegree. Sixteen years of cloud architecture across GCP, AWS, and Azure. Production AI systems delivered for Accenture and Capco clients in highly regulated industries where failure has real consequences. The sessions teach the engineering decisions that keep AI systems running past month one. Ideal for : Software engineers, ML practitioners, and technical leads building AI systems that need to survive contact with real data
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