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§ 01 — 3 MONTHS INDUSTRIAL CURRICULUM rev: 2026.2

DBERT Accelerate

Applied Industrial AI Engineering — 3 Months of Production Sprints

3 months (8 Sprint Cycles)10–15 Hours/Week (Async Sprints)Production PRs (Senior Code Reviews)Verifiable Certificate (SHA-256 Auth)
§ CURRICULUM ARCHITECTURE

Weekly Production Sprints & Deliverables

Hands-on engineering modules worked through on real code. You write executable scripts, build backend pipelines, and submit evaluated pull requests each sprint.

Weeks 1–44 Weekly Sprints · Evaluated PR Review

Specialized Stack Setup, Containerization & Schema Design

  • Advanced architecture deep dive: AI Agent state machines (LangGraph/CrewAI), Production RAG pipelines (Next.js/PostgreSQL/pgvector), or System Automation (Playwright/Celery).
  • Configuring local server dependencies, installing environment packages, and building multi-stage container sets with Docker and docker-compose.
  • Designing robust database schemas, vector indexing parameters (HNSW/IVFFlat), security controls, and authenticated API endpoints.
Weeks 5–84 Weekly Sprints · Evaluated PR Review

Production Sprints, Vector RAG & Live Repositories

  • Sprint 1: Building a functional multi-agent coordination loop with tool calling, context compression, and error recovery.
  • Sprint 2: Implementing pgvector database connections, hybrid search (dense + BM25 sparse), and automated background task queues.
  • Conducting code review check-ins on live pull requests, profiling token generation latency, and resolving concurrency bottlenecks.
Weeks 9–124 Weekly Sprints · Evaluated PR Review

Cloud VPC Staging, Telemetry & Fellowship Handoff

  • Packaging and deploying containerized applications to private cloud VPCs (AWS EC2 / Supabase) with automated CI/CD and SSL termination.
  • Implementing Prometheus metrics and OpenTelemetry tracing for LLM latency, memory consumption, and error rates.
  • Writing technical README documentation, passing automated unit and integration test suites, and receiving direct eligibility for the paid DBERT Fellowship.
§ ACTIVE PRODUCTION OPPORTUNITIES

Where Interns Are Contributing Right Now

We do not assign isolated classroom exercises. Your weekly sprint tasks and capstone map directly to these active production repositories maintained across our venture studio squads.

DBERT Production StackRole: Core AI Systems & Autonomous Workflow Engineer
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dbert-labs / dbert-agent

Production multi-agent execution pipeline orchestrating local Ollama LLMs with live web search, function execution sandboxes, and JSON signal schemas.

StateGraph Workflow LoopOllama Local Weight InferenceStreaming Token GeneratorSandboxed Python REPL
Aivara Enterprise TrackRole: Full Stack RAG & Systems Developer
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Aivara-Technologies / aivara-insight-lite

Locally hosted analytical system inferring data schemas, computing driver variance, and querying vector databases with LangChain and pgvector.

pgvector Embedding IndexHybrid Semantic SearchDocument Parser & ChunkerAutomated Slide Export
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