Architecture · Design Philosophy

Engineering Practice & Principles

Pragmatic, shippable, learned by building

A set of pragmatic engineering principles — from technology selection to testing to retrospectives. Not textbook theory: practiced and refined in recent hands-on projects like job-hunt and LearnArken.

Design Philosophy

Technology Selection
#01

Stability First

Choose production-ready, stable solutions (e.g., managed cloud services). Small teams cannot afford to spend time on solution stability issues.

#02

Stand on Giants' Shoulders

Reference industry best practices. You're not the first to face this problem — leverage others' experience to go further.

#03

Cost-Effectiveness First

Expensive solutions are the enemy of ROI. Use pay-per-use serverless in MVP phase, switch to fixed services when traffic is predictable.

Engineering Discipline
#04

Documentation First, Standards First

All scenarios should be considered before coding begins, not researched on the fly.

#05

Testing Has Veto Power

No product ships without tests. Every change, even minor dependency updates, requires testing.

#06

New Tech Must Be Targeted

New technology must solve a specific problem. Full replacement is nearly impossible. Research and deployment must have clear goals.

Operations & Reliability
#07

Redundant Monitoring

Never rely on a single monitoring channel — auto-call + auto-message. Production incidents happen more than expected; ensure minimal impact.

#08

High Availability Is a Feature

HA cannot stay theoretical. Make it understandable to non-technical stakeholders and visibly part of the product.

Team Culture
#09

Proactive Communication When Issues Arise

Unexpected things will happen. Communicate proactively — don't hide or sugarcoat. Conduct proper post-mortems.

#10

Post-Mortem Is the Final Step

Development without reflection isn't development. A project without retrospective isn't a project.

Project Architecture Cases

Not just theory — real projects proving the design philosophy

job-hunt

Three subsystems · human in the loop

  • Evaluation and application decoupled, each testable
  • 460+ pytest tests; testing has veto power
  • Fill-only; never auto-submits behind unmet gates
Related Principles #1Related Principles #3
View Case Study

LearnArken

Advanced RAG

Hybrid retrieval → reranking → fail-closed grounding

1

Phase 1: Hybrid Retrieval

BM25 structure-aware chunking + dense vectors (Vespa) fused with RRF, then refined by a cross-encoder reranker

2

Phase 2: Grounding Gates

Three fail-closed gates and verbatim-quote validation — refuse rather than fabricate; citations backfilled mechanically from metadata

3

Phase 3: Adversarial Eval

A 32-case adversarial set scored by two heterogeneous judges; a cross-document aggregation hallucination found and fixed

RAG for safety-critical aviation docs: reproducible and auditable — only reproducible numbers enter the README

Related Principles #5Related Principles #6Related Principles #9Related Principles #10