A personal growth roadmap focused on architecture, system design, AI-enabled engineering, production readiness, API/DX, algorithms, and security-aware engineering.
| Goal | Competency Area | What I want to strengthen | Why it matters | Evidence / Outcome |
|---|---|---|---|---|
| 1. Architecture & System Design Ownership | System Design | End-to-end design, system boundaries, data flow, scalability, reliability, failure modes | Strong product / FAANG-like companies expect engineers to understand the whole system, not only implementation tasks | 2–3 system design writeups, participation in design discussions, architecture diagrams |
| 1. Architecture & System Design Ownership | Architecture Decisions | ADR, alternatives, consequences, risks, assumptions, constraints | Shows mature engineering thinking and makes technical decisions transparent for the team | 5–10 ADRs or technical decision notes |
| 1. Architecture & System Design Ownership | Product Architecture | Product goals, user flows, maintainability, evolution path | Helps build products that can evolve instead of becoming a set of disconnected features | Product architecture overview for one part of the system |
| 1. Architecture & System Design Ownership | Technical Communication | C4 diagrams, architecture overview, design documents | Senior/staff-level engineers need to explain complex technical decisions clearly to different audiences | 2–3 readable technical diagrams or design docs |
| 2. AI-enabled Product & Engineering Capability | AI Product Thinking | Understanding where AI can bring real product or engineering value | AI is becoming part of modern products, but it needs practical use cases, not hype-driven adoption | 1–2 AI use case proposals |
| 2. AI-enabled Product & Engineering Capability | RAG / Knowledge Systems | RAG, embeddings, vector search, chunking, grounding | Useful for documentation search, knowledge bases, developer workflows, support and architecture review | PoC or demo: AI search / RAG over technical docs |
| 2. AI-enabled Product & Engineering Capability | AI Evaluation | Evals, hallucination checks, quality criteria, test cases | AI solutions should be measurable and validated, not only “looks good” | Evaluation notes / test cases |
| 2. AI-enabled Product & Engineering Capability | AI Architecture | Model abstraction, provider abstraction, privacy, latency/cost, fallback strategy | AI should be designed as part of system architecture with clear boundaries, risks and runtime behavior | AI architecture writeup |
| 3. Production Engineering Excellence | Cloud / Runtime | Docker, Kubernetes/k3s, Helm, Argo CD, AWS basics, Terraform | Strong product engineers understand not only code, but how software is deployed, configured and operated | Deployment flow, Helm chart, Argo CD notes |
| 3. Production Engineering Excellence | Native / JVM Runtime | Quarkus native profile, GraalVM Native Image, JVM vs Native trade-offs | Relevant to the current project because it uses Quarkus/native build and has software + hardware context | JVM vs Native notes / build-runtime comparison |
| 3. Production Engineering Excellence | Observability | Logs, metrics, traces, Prometheus/Grafana/Loki/OpenTelemetry | Helps debug production-like systems and understand behavior after deployment | Dashboard / troubleshooting runbook |
| 3. Production Engineering Excellence | Algorithms & Performance | Graphs, caching, rate limiting, search/ranking, complexity, benchmarking | Builds efficient coding habits, improves system reasoning and supports FAANG-style engineering expectations | 3–5 algorithmic engineering notes / benchmarks |
| 3. Production Engineering Excellence | Security-aware Engineering | Vulnerability detection, dependency scanning, threat modeling, secure defaults | Security mindset is important for platform, enterprise and product engineering roles | Security checklist / vulnerability triage notes |
| 3. Production Engineering Excellence | API / DX / Documentation | OpenAPI, error model, quickstart, dev scripts, troubleshooting docs | A good product should be easy to integrate, maintain, onboard and debug | API/DX checklist, improved docs, quickstart |