Phase 01
RAG Mastery + Foundations
Retrieval-augmented generation end to end: ingestion, chunking, embeddings, retrieval quality, grounding, and failure modes.
in progress4 WEEKS
PROGRESS0%
Jun 15 → Jul 12
150-DAY MISSION · LIVE
FromDataEngineertoGenAIEngineer
I'm building my GenAI career in public — RAG, Agents, LLMOps, Data Engineering, YouTube, interviews, and real execution tracked daily.
Mission clockDAY 0 / 150▍
Scroll
// MISSION STATS
Telemetry from the field
Recruiters don't trust claims. They trust proof. These numbers update as the work ships.
Current Day
0
of the 150-day mission
Current Week
0
of 22 roadmap weeks
Total Progress
0%
mission runway elapsed
Learning Streak
0
consecutive logged days
Project Completion
0%
avg module progress
Videos Published
0
on Datainteg AI Lab
Weeks Completed
0
shipped and reviewed
Project Modules
0
flagship build scope
// THE JOURNEY
Five phases. 150 days. One outcome.
A month-by-month flight plan — from RAG mastery to a signed GenAI Engineer offer. Every phase ships public output.
Phase 01
RAG Mastery + Foundations
Retrieval-augmented generation end to end: ingestion, chunking, embeddings, retrieval quality, grounding, and failure modes.
in progress4 WEEKS
PROGRESS0%
Jun 15 → Jul 12
Phase 02
Agents & Orchestration
Agent fundamentals, LangGraph deep dive, multi-agent systems, MCP, and agent observability.
not started4 WEEKS
PROGRESS0%
Jul 13 → Aug 9
Phase 03
LLMOps + Evaluation + DE for AI
RAG evaluation with RAGAS, deployment, tracing, data engineering for AI workloads, and fine-tuning basics.
not started4 WEEKS
PROGRESS0%
Aug 10 → Sep 6
Phase 04
System Design + Portfolio
GenAI system design, core DE refresh, portfolio finalization, resume, LinkedIn, and Naukri.
not started4 WEEKS
PROGRESS0%
Sep 7 → Oct 4
Phase 05
Apply + Interview + Decision
Launch applications, interview mode, decision checkpoint, and notice period strategy.
not started6 WEEKS
PROGRESS0%
Oct 5 → Nov 15
// FLAGSHIP BUILD
One project. Production-grade. Public.
Learning is good. Shipping is better. The whole mission compounds into a single enterprise system, built in the open.
// ENTERPRISE AGENTIC RAG PLATFORM
Enterprise Agentic RAG Platform
A production-grade AI system that can ingest documents, logs, SQL metadata, and pipeline run history, then answer questions, debug data pipeline issues, generate Spark/SQL suggestions, and escalate when unsure.
01RAG v102Hybrid retrieval03Reranking04Agent tools05Tracing06Evaluation07Deployment
0%module completion
0
Modules
0
Active
0
Shipped
// CRITICAL PATH MODULES
- 01criticalnot started
Document ingestion pipeline
Ingest docs, pipeline logs, Airflow DAG metadata, SQL queries, and Spark job failures into a unified store.
- 02criticalnot started
Vector database storage
Vector store setup, collections, metadata schema, and upsert flows.
- 03criticalnot started
Hybrid search
Dense + BM25 retrieval with metadata filtering and score fusion.
- 04criticalnot started
RAG answer generation
Grounded generation with context budgeting and refusal behaviour.
- 05criticalnot started
Agent tool calling
Tool registry and calling loop for retrieval, SQL, and log analysis tools.
- 06criticalnot started
LangGraph workflow
Full state-machine orchestration: plan, retrieve, act, verify, escalate.
// CONTENT ENGINE
Datainteg AI Lab on YouTube
Series: "Data Engineer to GenAI Engineer" — the journey is the content. Every concept learned becomes a video shipped.
0
Short ideas
0
Long-form ideas
// BUILD LOGS
Public proof, day by day
Raw execution logs from the mission — published, not polished. Small daily execution beats weekend motivation.
akshay@datainteg:~/build-logs --public
> 2026-06-10SCORE 85
Prepare Mission Control launch
learned: Studied RAG ingestion patterns and chunking strategies for week 1.
built: Outlined the document ingestion pipeline design.
> 2026-06-09SCORE 72
Set up the 150-day mission structure
learned: Mapped the full 22-week roadmap and locked phase goals.
built: Drafted the flagship project module breakdown.
> ▍
// FOUNDER NOTES
This is not a todo list. This is my career operating system. 150 days. One flagship project. Public proof every week.
motivation · excited
Decision: the flagship project is an Enterprise Agentic RAG Platform for data teams — it compounds my DE background instead of discarding it.
decision · confident