AI agent architecture
How to decompose workflows into discrete agent tasks. Where to keep human control. What fails at scale.
Fifteen years across engineering and product. I've shipped systems at scale, trained teams to own their work, and learned what it takes to move fast without breaking things. Now I help companies integrate AI agents into production workflows — and do it with the judgment that keeps the work yours.
How to decompose workflows into discrete agent tasks. Where to keep human control. What fails at scale.
Shipping agents that work on real data, real systems. Testing, monitoring, and recovery patterns.
Teaching teams to own and iterate on agentic systems. Documentation that survives the build.
We talk through your workflow, pain points, and where agentic AI fits. I ask hard questions about your data, your scale, and your team capacity.
I sketch a minimal pilot: which agents, what prompts, how they chain together. We agree on success metrics and a two-week timeline.
Pilot runs in production. Real data, real edge cases. I tune prompts, build monitoring, and document everything your team needs to own it.
Your team learns to iterate on prompts, debug agents, and scale the system. Documentation lives; knowledge transfers.
I take on a small number of consulting engagements each year. If your team is ready to integrate AI agents into production — and wants someone who thinks about the long game — let's talk.
Or email me directly: mir@mirquadri.com
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