Minimum Knowledge for AI Software Development

AI is a tool. It does not replace your knowledge of architecture and engineering.

Stop outsourcing your decisions to AI. You must define all functional and non-functional requirements. Be specific about every detail.

There is no free lunch. Free or cheap models fall behind professional grade models. Use Opus or GPT with high reasoning levels for software engineering. Low quality models lead to more rework. This wastes your time and the time of your reviewers.

Use AI agents on your local machine. The harness matters. Use Codex for GPT and Claude Code for Opus. A poor harness produces poor results even with the same model.

Cheap plans work for amateur projects. Professional projects require plans with access to the best models and high usage limits.

Every project needs a CLAUDE.md or AGENTS.md file. Keep it short and objective. Write it in English. Include only critical project information.

Never implement code immediately. Follow this process:

  • Analyze the problem.
  • Create a plan.
  • Review the plan.
  • Implement the code.

Your plan must include architecture, acceptance criteria, tests, and feedback loops.

Be skeptical of your plan. Review everything before you code. Ask the AI to find gaps and challenge your decisions. The AI should only fail if your plan is bad.

Develop your critical thinking. AI speeds up execution. It does not replace judgment or engineering decisions.

Change your role. Stop being a task implementer. Act as an architect, tech lead, and product owner. Think about the whole system.

Context is everything. One prompt is not enough. Provide business rules, architecture, conventions, and constraints.

Always validate automatically. Every cycle must end with builds, tests, linters, and static analysis.

Do not accept code just because it works. Demand readability, simplicity, security, and maintainability.

Use skills to standardize prompts in your company. This maintains quality and architecture across all projects without repeating instructions.

If planning and testing feels like too much work, do not use AI for software. You will create low quality code and technical debt.

You own the responsibility. You are responsible for every line of code in production. Do not blame the AI or the tools. Your company expects results from you.

Source: https://dev.to/andredarcie/o-minimo-que-voce-precisa-saber-para-desenvolver-software-com-ia-1dc9