AI · Language · Uncertainty
I build systems that understand.I write about why we often don’t.
I'm Aissam Outchakoucht, an AI engineer building language, speech, and agentic systems. This is where I share things I build, ideas I'm exploring, and essays about uncertainty, perspective, intelligence, and the strange business of knowing things.
The rooms
Four places to look
A personal site, not a brochure. Pick a room.
01
About
AI engineer working on conversational systems — and the questions they leave open.
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02
Projects
Darija datasets and libraries, production ML pipelines, chatbots, and voice skills.
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03
2-minute reads
NLP boiled down. Foundations to advanced techniques, packed into a short note.
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04
Thoughts
Essays on certainty, perception, and how much of what we call knowing actually stands.
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Work
Things that shipped
Datasets, libraries, pipelines, chatbots, and voice skills.
Darija libraries
Python libraries for Darija ⇆ English — word distance, translation lookup, and an LLM-assisted translator that does not pretend Darija is just messy Arabic.
Alexa Skills with Python
A five-part path from Alexa concepts to a working Rock–Paper–Scissors skill — then APL, multilingual support, and monetization, all in Python.
Darija Open Dataset
The largest open collaborative dataset for Moroccan Darija ⇆ English, built for NLP — now past 500,000 semantic rows, in both Arabic and Latin script.
ML in production
A pipeline from trained model to API to container to cloud — Keras, Flask, Docker, and Heroku, written as something you can actually run.
WhatsApp and Messenger chatbots
Business chatbots on WhatsApp and Messenger that talk to a real backend — Dialogflow, Twilio, Flask, Firebase.
NLP Explained
Notes you can read in two minutes
From foundations to advanced techniques — boiled down, simplified, and packed tight.
Mixed Precision vs. Quantization
Mixed precision and quantization are two techniques that can significantly reduce the memory and computational requirements of AI models.
Prompt Chaining
Prompt chaining is a technique that involves combining multiple prompts to generate more complex and nuanced responses from AI models.
Reinforcement Learning from Human Feedback (RLHF)
RLHF is a method that incorporates human feedback into the training process of AI models. Unlike traditional training, which relies solely on datasets and metrics, RLHF uses human evaluators to guide the model's learning.
Vector Databases in NLP
Vector databases are a powerful tool for storing and querying high-dimensional vectors. They are very useful in comparison and search tasks in NLP
Exploring LangChain
LangChain is a tool for building AI applications. It simplifies the process by making it easier to connect and manage the various components.
The Art of Fine-Tuning
Finetuning is the magic wand that transforms a general-purpose AI model into a domain-specific maestro.
How Prompt Engineering Shapes AI Interactions
Prompt engineering is the art of crafting the perfect question or instruction to elicit the desired response from an AI model.
Retrieval-Augmented Generation (RAG)
RAG combines the best of both worlds: the vast knowledge of a search engine and the creative storytelling of a language model.
Approach
How I actually think
Measure the uncertainty
A lot of what people call knowledge is borrowed confidence. The useful move is to notice where the chain of justification actually stops.
Ship conversational systems
Chat, voice, agents. The interesting work is not the demo — it is the system that holds up when a real person starts talking.
Open-source Darija
Moroccan dialect is spoken by millions and still under-served in NLP. Datasets and tools should exist in the open.
Write in public
Short notes, long essays, tutorials. Writing is how the work gets inspected — by you first, then by anyone else.
8+
Years in AI
500k
DODa entries
61
2-minute notes
11
Papers
Thoughts
A little less certainty
Series
5 chapters · 12 April 2026 – 14 April 2026
You Know Nothing, Jon Snow
Five chapters on certainty, perception, and how much of what we call knowing actually stands when you look closely.
Open series →Emergence as the starting point to Artificial General Intelligence
What made humans unique is their ability to add flexibility to the common ingredients of emergence: number and cooperation.