Conversations on data, AI, and the systems behind them.
Long-form interviews with engineers, researchers, and operators working at the production edge of AI.
Currently · taking a few client engagements
AI consulting for teams shipping real ML and generative-AI systems.
I'm Muhammad Afzaal — 20+ years building enterprise software, the last five on production LLM and data platforms. I help teams move from prototype to production without losing the plot.
- 20+ years shipping enterprise software
- 5+ years on production LLM systems
- D365 F&O · MCP · RAG · Data platforms
Recent engagements that shipped to production.
Three projects that show what I bring: pragmatic system design, a bias toward measurable outcomes, and code that survives in real environments.
Enterprise ERP team
Built the d365fo-client Python library + MCP server: 29 tools, OData query, FTS5 metadata search. AI assistants can now operate D365 F&O via natural language.
- Python
- MCP
- OData
- FTS5
Generative search platform
Production RAG with chunking, hybrid retrieval, and reranking. Cost dropped 60% on the same answer quality after evaluation-driven optimization.
- LangGraph
- Ragas
- pgvector
Data governance initiative
Mapped 6 OSS data-governance frameworks against NIST AI RMF; published the comparison + architecture guide that anchors team decisions.
- Governance
- OSS
- NIST AI RMF
Notes from production AI.
Lessons from real systems — RAG cost economics, MCP integration, governance frameworks, evaluation pipelines that don't lie.
The Gen AI ROI Crisis: What the 95% Failure Claim Really Means
The latest evidence shows real AI productivity gains but scarce enterprise returns. Learn how to measure, govern, and scale workflows into financial value.
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Value at Risk in Python: Rolling Volatility, EWMA, and Breach Testing
Build and backtest historical, rolling-normal, EWMA, and Student-t VaR in Python, then compare breaches, fat-tail failure modes, and Expected Shortfall.
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Longstaff-Schwartz: Monte Carlo Meets Optimal Stopping
Learn how least-squares Monte Carlo turns American option pricing into backward regression, with reproducible Python benchmarks and practical caveats.
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100 Posts Later: How Sharing My Work Helped Me Find My Momentum Again
My 100th post is a reflection on rebuilding momentum through public learning—and how 165,000 words across AI, enterprise software, mathematics, and finance changed me.
Read
A drop-in chat widget you can deploy in minutes.
Open-source assistant with LangGraph orchestration and a clean theme system. The same widget that powers the chat on this site.
Have a hard AI problem?
I work with a small number of teams each quarter — usually on production LLM pipelines, MCP integrations with enterprise systems, or evaluation frameworks that survive contact with real data.