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.
Most Analytics Bugs Are Data Bugs. Five Checks That Catch Them Before the Meeting.
Five validation checks every analyst should run before trusting a table: duplicates, NULL key columns, out-of-range values, cross-field arithmetic, orphan references. Tested on a 2,010-row orders table with 50 planted defects; the checks flagged 51 rows, and the misses are as instructive as the catches.
Ibrahim Denis Fofanah·Oct 11, 2026·8 min
The Hermes Index Ranks Agent Models on Score and Cost. The Lab That Built It Just Raised $90M.
Nous Research's Hermes Index (Oct 6, 2026) pairs agent scores with cost per task for 14 models. Opus 5.5 leads on score at 63.31; the value story belongs to Sonnet 5.5 and DeepSeek V4.1 Flash.
Ibrahim Denis Fofanah·Oct 10, 2026·8 min
Your Benchmark Leaderboard Is Measuring the Test, Not the Model. Stanford Checked 56 of Them.
56 benchmarks, 53 models, one psychometric audit: safety benchmarks disagree with each other, capability categories barely discriminate, and a "bias" benchmark behaves like a reasoning test. If your model selection rests on leaderboards, read this first.
Ibrahim Denis Fofanah·Oct 9, 2026·8 min
The EU AI Act Is Already Enforcing. The Deadline Everyone Watched Was the One That Moved.
The enforcement machinery is running: chatbot disclosure, synthetic-content marking, GPAI documentation demands, and a US state banning algorithmic grocery pricing.
Ibrahim Denis Fofanah·Oct 8, 2026·12 min
The Press Releases Promise African-Language AI. The Data Pipeline Is the Real Product.
Tether's 0.8B-parameter TranslatePsy-AfriSLM beat models up to 150x larger at African translation, and the trick was deleting 96% of low-quality training data. Google's WAXAL took three years to record 11,000 hours of speech across 21 languages. In African-language AI, the data pipeline is the product. Benchmarks still cover only 52 of 2,000+ languages.
Ibrahim Denis Fofanah·Oct 7, 2026·9 min
Window Functions Are SQL's Most Underused Feature. Five Patterns Cover Nearly Everything.
Five window-function patterns that cover most analytics SQL: dedupe with ROW_NUMBER, top-N per group with RANK, period comparisons with LAG, running totals with explicit frames, bucketing with NTILE. Every query ran and its output is shown; a 200,000-row timing test puts the window function at 0.46s against 5.92s for the equivalent self-join on 5,000 rows.
Ibrahim Denis Fofanah·Oct 6, 2026·8 min
Gradient Boosting Still Rules Tabular Data. The Foundation Models Are Gaining Ground.
Four years after a 45-dataset benchmark crowned gradient-boosted trees on tabular data, tabular foundation models (TabPFN, LimiX-2, NVIDIA's Kumo Tabular) are topping leaderboards. What the 2022 verdict got right, where it no longer holds, and how to choose your next tabular model.
Ibrahim Denis Fofanah·Oct 5, 2026·13 min
MCP, Explained for Data People: It Standardizes the Plumbing, Not the Thinking
MCP standardizes how agents connect to data and tools: three roles, three primitives, one wire format. I built a minimal server and ran it end to end; here is what the protocol guarantees, and the security fine print most tutorials skip.
Ibrahim Denis Fofanah·Oct 4, 2026·9 min
UNDP and GSMA Back African-Language AI. The Announcement Is Real; the Numbers Are Not
UNDP and the GSMA announced a partnership on 2 October to scale African-led AI, with African-language models as the priority. The language-first focus is right. The release carries no funding figure and no timeline.
Ibrahim Denis Fofanah·Oct 3, 2026·6 min
The Battle for the Agentic Interface: Meta Muse, OpenAI Dots and Grok Bot
Meta Muse, OpenAI Dots and Grok Bot point to a new AI interface: persistent agents that can use tools, maintain state and keep working after the chat ends.
Rodriquez Allen·Oct 3, 2026·9 min
Build a RAG System That Knows When It Doesn't Know
A practical AI engineering tutorial on building a retrieval-augmented generation system with semantic search, confidence checks, grounded answers, and a simple evaluation layer.
Rodriquez Allen·Oct 2, 2026·8 min
RAG Systems Collapse When They Retrieve Their Own Writing. One Self-Authored Document Can Start It.
79.6% of 1,528 RAG simulations collapsed when the model retrieved documents it had authored itself, and a single self-written reference can trigger it. If your pipeline indexes its own output, this paper is about you.
Ibrahim Denis Fofanah·Oct 2, 2026·6 min
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