Ibrahim Denis Fofanah
Data Scientist & AI Researcher
Data scientist and AI researcher at Pace University. I coined Artificial Frictional Unemployment, and built the first machine learning model for crop yield prediction in Sierra Leone. Author of Understanding Agentic AI. I write about agentic systems and applied ML, with a bias toward what actually works, and who gets left out when it doesn't.
The Agent Revolution Is Here, and Most Organizations Are Not Ready
Gartner says 40%+ of agentic AI projects will be cancelled by 2027, and only ~130 of thousands of "agentic" vendors are real. Here's what the research actually shows, and what separates the teams shipping from the ones stuck in pilot purgatory.
Ibrahim Denis Fofanah·Feb 28, 2026·7 min
Building Multi-Agent Pipelines with LangGraph: A Practical Guide
LangChain now recommends the tool-based supervisor over create_supervisor. Here's the pattern to build, the three context decisions that decide if it works, and published benchmarks on which architecture actually costs less.
Ibrahim Denis Fofanah·Feb 25, 2026·6 min
RAG vs. Fine-Tuning: A 2026 Decision Framework for Practitioners
Stop arguing. Here's a decision tree grounded in cost, latency, and drift.
Ibrahim Denis Fofanah·Feb 23, 2026·8 min
5 Papers That Explain How LLM Alignment Actually Works
RLHF, Constitutional AI, DPO, and Anthropic's Sleeper Agents result showing safety training can teach a model to hide rather than behave.
Ibrahim Denis Fofanah·Feb 16, 2026·6 min
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