Modules

Set up your working environment and define a repeatable weekly execution workflow.

Build a reliable backend baseline with Python and FastAPI for SAP-oriented services.

You’re turning “SAP gut feeling” into rules and structure.

You stop shipping “it works on my laptop” by enforcing reproducible run/test flow and a hard Definition of Done gate.

Build one extraction flow that is predictable, observable, and resumable instead of fragile.

Turn data quality from vague complaint into an automated gate with explicit rules, mapping, and measurable output.

Build a real storage spine with Postgres schema + migrations so loads and queries are reliable.

Build a scheduled, resilient pipeline with retries and idempotent execution you can run and trust every day.

Build practical observability so you can detect failures early, debug fast, and stop guessing.

Create a structured, action-oriented ticket dataset and labeling baseline you can trust for real AI evaluation.

Make LLM outputs predictable, constrained, and parseable so they are actually usable in operations.

Turn prompt outputs into a real, validated classification and routing feature with deterministic behavior.

Detect recurring ticket patterns and turn them into actionable fixes, runbooks, and automation opportunities.

Build a repeatable evaluation harness that catches regressions, tracks drift, and proves quality over time.

Turn classifier, routing, clustering, and eval outputs into automated reports that drive operational decisions.

Design a trustworthy, structured knowledge base with chunking and metadata that supports source-grounded answers.

Improve retrieval quality with measurable search and ranking so answers with sources are actually reliable.

Establish clear governance and guardrails so the knowledge system stays safe, source-grounded, and policy-compliant.

Create practical runbooks, RCAs, and SOPs that turn tribal knowledge into consistent, retrievable operational execution.

Build a repeatable content pipeline so knowledge stays fresh, tested, and trustworthy instead of slowly rotting.

Harden the KB system with enforceable quality gates so every change is safe, testable, and demo-ready.

Package all projects into portfolio-grade assets with clear run paths, demos, diagrams, and reliable quality gates.

Turn each project into a clear, evidence-backed case study that shows problem, approach, and measurable results.

Build a small, repeatable publishing engine that turns shipped project work into visible, proof-based content.

Run an honest final review, package everything into a shareable portfolio pack, and set a focused roadmap for the next 6–12 months.