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ἐρευνητής
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poacosta/README.md
┌──────────────────────────────────────────────────────────────────────┐
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│   ██████╔╝█████╗  ██║  ██║██████╔╝██║   ██║                          │
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│   ██║     ███████╗██████╔╝██║  ██║╚██████╔╝                          │
│   ╚═╝     ╚══════╝╚═════╝ ╚═╝  ╚═╝ ╚═════╝                           │
│                                                                      │
│                     System Initialization                            │
└──────────────────────────────────────────────────────────────────────┘

$ whoami
pedro_acosta

$ cat /etc/profile
Software & AI Engineer · Málaga, Spain

I design, build and deliver software and applied AI systems.
From architecture to implementation, I connect technical
decisions with business needs.

$ cat /usr/local/roles.txt
[✓] Senior Software Engineer
[✓] AI Engineer
[✓] Data Scientist
[✓] Technical Leadership

$ ./load_expertise.sh
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100%

[INFO] Initializing experience modules...
[OK]   ├─ Building software since 2011
[OK]   ├─ Fintech, edtech and e-commerce
[OK]   ├─ Engineer, team lead and former CTO
[OK]   └─ M.Eng. in Big Data and Data Engineering

[INFO] Loading engineering capabilities...
[OK]   ├─ Full-stack applications and APIs
[OK]   ├─ Cloud architecture and automated delivery
[OK]   ├─ Data analysis and machine learning
[OK]   ├─ Retrieval-augmented generation and language models
[OK]   └─ Agent workflows and observability

$ cat /etc/stack.conf
[software]
languages  = Ruby, Python, JavaScript, TypeScript, Elixir
frameworks = Rails, React, Next.js, Phoenix, FastAPI

[ai_and_data]
ai         = LangGraph, LlamaIndex, PyTorch, scikit-learn
data       = PostgreSQL, pandas, ChromaDB, pgvector

[infrastructure]
cloud      = AWS, Azure, Google Cloud
delivery   = Docker, Terraform, GitHub Actions

$ tree ~/projects
~/projects
├── explorations
│   ├── literary-finder
│   │   Three specialist agents exploring authors and their work.
│   │   https://github.com/poacosta/literary-finder
│   │
│   └── the-librarian
│       A conversational guide to Borges using document retrieval.
│       https://github.com/poacosta/the-librarian
│
└── built-to-teach
    ├── cv-screener
    │   PDF ingestion, hybrid retrieval and source-linked answers.
    │   https://github.com/poacosta/cv-screener
    │
    ├── the-transformer-drawn
    │   Attention made visible through an interactive simulation.
    │   https://github.com/poacosta/the-transformer-drawn
    │
    └── visual-latent-space
        A guided 3D metaphor for exploring prompt quality.
        https://github.com/poacosta/visual-latent-space

$ cat /etc/philosophy.conf
# Engineering principles
- Build maintainable systems with clear interfaces.
- Test meaningful behavior and make failures observable.
- Ship useful increments and learn from feedback.
- Document decisions so others can build on them.
- Share knowledge and help teams grow.

$ echo "$MISSION_STATEMENT"
"Technology should amplify human capability.
That's the kind of AI worth building."

$ cat ~/blog/README.txt
AI explained. Engineering perspectives. Reflections.

I write about AI and software, connecting technical ideas
with practical examples and the questions behind them.

Available in English and Spanish.

$ tree ~/blog
~/blog
├── en → https://pedroacosta.dev/blog/
└── es → https://pedroacosta.dev/es/blog/

$ ls ~/links/
┌──────────────────────────────────────────────────────────────────────┐
│  CONNECT                                                             │
├──────────────────────────────────────────────────────────────────────┤
│  Portfolio EN → https://pedroacosta.dev/                             │
│  Portfolio ES → https://pedroacosta.dev/es/                          │
│  Blog EN      → https://pedroacosta.dev/blog/                        │
│  Blog ES      → https://pedroacosta.dev/es/blog/                     │
│  LinkedIn     → https://linkedin.com/in/poacosta77                   │
│  Email        → contact@pedroacosta.dev                              │
├──────────────────────────────────────────────────────────────────────┤
│  LEARN & EXPLORE                                                     │
├──────────────────────────────────────────────────────────────────────┤
│  Pluralsight  → https://app.pluralsight.com/profile/poacosta         │
│  Google Devs  → https://g.dev/poacosta                               │
│  Codewars     → https://codewars.com/users/poacosta87                │
│  Exercism     → https://exercism.org/profiles/poacosta               │
│  Goodreads    → https://goodreads.com/user/show/141287714            │
└──────────────────────────────────────────────────────────────────────┘

$ history | tail -1
> "Growing up, I couldn't stop taking things apart—mentally if not
> physically. Physics, biology, mathematics, art—I wanted to understand
> all of it. Then I discovered: software is the universal language."

$ uptime
Since 2011 turning concepts into working software.

$ ssh portfolio
[INFO] An interactive terminal is waiting at pedroacosta.dev.
[HINT] Try: whoami, work, stack, help

$ █

Pinned Loading

  1. finplifai-chat finplifai-chat Public archive

    FinplifAI is a RAG-based multiagent chat system designed to assist users with accounting and finance queries in accordance with Spanish state regulations

    TypeScript 1

  2. the-librarian the-librarian Public

    The Librarian: ChromaDB + Local Embeddings RAG System for Borges Literary Analysis

    Python

  3. literary-finder literary-finder Public

    A Multi-Agent System for Deep Literary Discovery

    Python 1

  4. agentic-rag-serverless-api-with-azure agentic-rag-serverless-api-with-azure Public template

    A serverless API implementation demonstrating how to deploy retrieval-augmented generation with basic agent capabilities using ChromaDB and LlamaIndex. (with Azure)

    Python

  5. service-health-monitor service-health-monitor Public

    Basic Service Health Monitor to notify outages using Slack

    Python 3

  6. visual-latent-space visual-latent-space Public

    An interactive 3D visualization showing how prompts steer AI models through their latent space

    TypeScript