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Ibrahim Denis Fofanah

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.

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30 articles
AnalysisCareer · Data Analyst

Excel or Python First? What Data Analyst Job Postings Actually Say

SQL appears in 80%+ of data analyst postings, Excel in 60%, Python in 50%. Here's the learning order that matches the market, and the trap that costs beginners a year.

Ibrahim Denis Fofanah·Jul 12, 2026·5 min

TutorialPython · Data Cleaning

7 Pandas One-Liners That Replace 20 Lines of Data Cleaning

Seven vectorized pandas one-liners that replace dozens of lines of manual cleaning code, with copy-paste examples.

Ibrahim Denis Fofanah·Jul 10, 2026·3 min

Deep DiveCover Story

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

TutorialCode-Along · LangGraph · Multi-Agent

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

ResearchRAG · Fine-Tuning

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

arXiv Breakdown

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