Skip to content
View mattiamancusi's full-sized avatar
💭
Open to Python, Operations and Junior Data opportunities
💭
Open to Python, Operations and Junior Data opportunities

Block or report mattiamancusi

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
mattiamancusi/README.md

Mattia Mancusi

Python automation · Linux operations · evidence-driven AI workflows

Based in Amsterdam, Netherlands. Open to Python, Operations and Junior Data opportunities.

About

I build practical automation and operational tooling around Python and Linux, with an emphasis on deterministic processing, observability, validation and reproducible technical evidence.

My public repositories are sanitised representations of real workflow families. They use synthetic fixtures and exclude production credentials, private runtime data and account-specific state.

Featured projects

A navigable, sanitised map of a production-style VPS architecture containing documented Python and Bash workflows, synthetic fixtures, validation tooling and tests.

Demonstrates: Linux operations, Python automation, append-only processing, JSON reconciliation, observability and publication safety.

Sanitised case studies covering AI-assisted debugging, technical audits, failure analysis and evidence-driven remediation.

Demonstrates: root-cause analysis, audit methodology, structured evidence, remediation boundaries and deterministic verification.

A reproducible pipeline for collecting, validating and presenting evidence from AI-assisted technical workflows.

Demonstrates: Python data pipelines, provenance, JSONL processing, validation, synthetic testing and reproducible reporting.

Technical focus

  • Python automation and command-line tooling
  • Linux and VPS operations
  • Bash scripting and process supervision
  • JSON, JSONL and SQLite workflows
  • Append-only records and reconciliation
  • Health checks, telemetry and operational observability
  • Git, GitHub Actions and publication validation
  • Synthetic fixtures and deterministic tests

Currently expanding my applied skills in SQL, Power BI and operational data analysis.

Engineering approach

  • Prefer deterministic and inspectable workflows over opaque automation.
  • Preserve evidence through append-only records and explicit provenance.
  • Separate production state from public examples and documentation.
  • Default potentially sensitive workflows to read-only or dry-run behaviour.
  • Treat validation, reconciliation and failure handling as part of the system design.

Contact

LinkedIn

Popular repositories Loading

  1. ai-workflow-evidence-pipeline ai-workflow-evidence-pipeline Public

    A reproducible pipeline for collecting, validating and presenting evidence from AI-assisted technical workflows.

    Python

  2. ai-debugging-audit-portfolio ai-debugging-audit-portfolio Public

    Sanitised case studies in AI-assisted debugging, technical audits, failure analysis and evidence-driven remediation.

  3. root-know-your-path root-know-your-path Public

    A sanitised, navigable map of a production-style VPS architecture, with documented Python and Bash workflows.

    Python

  4. mattiamancusi mattiamancusi Public

    Profile README — Python automation, Linux operations and evidence-driven AI workflows.