Software Engineer

Alexis Alulema

Software Engineer · Builder

Software Engineer with 20+ years turning complex problems into scalable solutions — across software, cloud, AI and hardware.

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Real AI projects you can spin up on demand — each one gets its own ephemeral environment.

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Live demo

Trip Planner (Chain of Agents)

Type a trip request and watch a chain of specialised agents hand the work along in real time until they deliver a day-by-day itinerary checked against your budget. A LangGraph orchestrator owns the control flow; a local Qwen 2.5 writes only the prose, while typed decisions and plain arithmetic handle the rest. When the plan goes over budget, a conflict-resolution agent renegotiates it without a human. Local LLM (Qwen 2.5 via Ollama) and no API keys; live weather, places and exchange rates come from open data sources.

PythonFastAPILangGraph
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Live demo

Agentic Racing

Six identical cars race a closed circuit in the browser. Each car is a two-tier agent: a pilot that drives every frame, and an independent LLM team boss that reads live telemetry and radios back a strategy — attack, defend, conserve — F1 team-radio style, on screen. The race never waits on the model: a fixed heuristic takes over the instant it is slow, off, or replies invalid JSON. Fully self-hosted: a local llama3.2:3b behind a proxy with its own circuit breaker, rate limit and concurrency gate.

Unity WebGLPythonFastAPI
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Live demo

RAG Chatbot over Blog Posts

An interactive retrieval-augmented generation chatbot that answers questions using my blog posts as a knowledge base. Fully self-hosted: semantic vector search (pgvector) with multilingual embeddings and a local Qwen 2.5 LLM served by Ollama — no external LLM APIs.

PythonFastAPIpgvector
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Series · 5

Reinforcement Learning from scratch

Five articles that teach RL using a real project — Agentic Racing — as the lab: from what an agent is, to PPO, imitation and how to combine them.

Start with part 1 →
  1. Part 1How Does an Agent Learn? Teaching a Car to Drive
  2. Part 2How Do We Improve a Policy Without Breaking It? PPO Explained from Scratch
  3. Part 3Can We Teach by Imitation? Behavioral Cloning Explained from Scratch
  4. Part 4Can We Learn to Behave Like an Expert? GAIL Explained from Scratch
  5. Part 5Can We Combine Imitation and RL? BC, GAIL, and PPO as One System

Latest posts

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12 min read

A Trip Planner That Reasons Without Generating: Chain-of-Agents with a 1.5B Model

I took the Chain-of-Agents pattern from chapter 7 of 30 Agents Every AI Engineer Must Build and turned it into a real demo: a local 1.5B model that writes only what it must, a JEV-style decision engine that answers with probabilities instead of text, and a budget-conflict loop that resolves without generating a single token. What worked, what the model made up, and how the code ended up writing the honest part.

agentsllmlanggraphollamapythonfastapi
17 min read

Agentic Racing: A Pilot That Never Learned to Drive, a Team Boss That Did Learn to Reason

I built a racing demo where a reactive pilot obeys a team-boss LLM that reasons per event. Eight attempts at training the pilot with reinforcement learning didn't work — the track was broken before the algorithm ever had a chance — and measuring how much the strategist actually contributes turned into the more interesting experiment: seven runs, real and partially fixable reasoning biases, and a lesson about trusting the full benchmark over the quick desk-check.

reinforcement-learningllmunityagentsollamapython
16 min read

Twenty Minutes of Infrastructure (and Then Nothing Left)

The demo behind each project card on my site doesn't exist until you ask for it, and stops existing twenty minutes later. This is the machinery behind that button: an ephemeral environment per session, a subdomain pool, a gateway, a reaper that had to be rebuilt, and the bugs that only showed up in production.

infrastructureazurecontainersgithub-actionscloudflaredevopsiac