AI
RAG vs Fine-Tuning for Business Data
A practical framework for choosing RAG, fine-tuning, SQL, or a hybrid architecture when building AI features around business data.
18 min read
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AI
AI articles are practical engineering notes about using ChatGPT, coding agents, prompts, and documentation workflows without giving up technical control or code review discipline.
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Start from the curated articles
These articles are selected as practical entry points based on topic coverage, internal relevance, and a clear reading path.
01An Operating Model for AI Coding Agents in Backend TeamsA team-level operating model for using AI coding agents in backend engineering: scope boundaries, approvals, risky tasks, security review, CI checks, and rollout ownership.02How I Use ChatGPT for TSDs, ERDs, and Database DocumentationA practical backend workflow for using ChatGPT with Google Docs, DDL, DBML, dbdiagram.io, ERDs, and database documentation.03My Practical AI-Assisted Engineering WorkflowThe review loops, context boundaries, and verification habits I use to make AI useful without giving up engineering judgment.
Recommended reading order
1An Operating Model for AI Coding Agents in Backend Teams14 min read2How I Use ChatGPT for TSDs, ERDs, and Database Documentation16 min read3My Practical AI-Assisted Engineering Workflow10 min read4RAG vs Fine-Tuning for Business Data18 min read5My Claude Code Refactoring Review Loop19 min read6From PRD to Production Code with Claude Code15 min read
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AI archive
AI
My Practical AI-Assisted Engineering Workflow
The review loops, context boundaries, and verification habits I use to make AI useful without giving up engineering judgment.
10 min read
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My Claude Code Refactoring Review Loop
How I used Claude Code to scan a codebase, produce a numbered quality report, and apply approved refactors one finding at a time.
19 min read
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From PRD to Production Code with Claude Code
A delivery workflow for turning product requirements into reviewed technical design, implementation slices, tests, and rollout decisions with Claude Code.
15 min read
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Reviewing AI-Generated Code Before Merge
A practical review checklist for validating AI-generated backend code: business logic, state transitions, data integrity, security, tests, and production impact.
18 min read
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Designing Backends That Survive LLM Model Deprecations: A Practical Playbook
A practical backend playbook for surviving LLM model deprecations with toggles, fallbacks, evals, SLOs, and review checklists.
17 min read
ReadAI
How I Use ChatGPT for TSDs, ERDs, and Database Documentation
A practical backend workflow for using ChatGPT with Google Docs, DDL, DBML, dbdiagram.io, ERDs, and database documentation.
16 min read
ReadAI
An Operating Model for AI Coding Agents in Backend Teams
A team-level operating model for using AI coding agents in backend engineering: scope boundaries, approvals, risky tasks, security review, CI checks, and rollout ownership.
14 min read
Read