How AI can help you create your next project

AI doesn’t replace developers, it multiplies them. It takes care of repetitive work so the team can spend its time solving customers’ problems.

Marco MendãoCo-Founder & CTO · 8 min

Building an MVP used to take weeks of repetitive work: project setup, CRUD endpoints, schemas, tests and docs. Today AI does much of it in hours. The goal is not fewer people, it is more output per person.

More autonomous developers

  • Generate scaffolding, endpoints, models and config in minutes.
  • Debug faster and understand unfamiliar code.
  • Write tests alongside features.
  • Do repetitive refactors with little effort.
  • Explore new ground, like a frontend developer prototyping backend logic.

The result is smaller teams producing what used to take larger ones.

Focus on customers, not software

When building gets cheap, the temptation to build what nobody asked for grows. That is why we apply lean startup to development: the hours saved go into interviews, prototype tests and product decisions.

  • Start with the user’s problem, not the feature list.
  • Validate before automating.
  • Measure outcomes, not output.
  • Cut features early: keeping what isn’t needed still costs.

Less effort on details, more on the core

AI handles project setup, standard CRUD, documentation, UI components, migrations and standard integrations well. People still own architecture, product direction, user experience, production debugging and security.

In practiceA team that spent 60% of its time on infrastructure and boilerplate can bring that down to 20%, and put the rest into features and experience.

AI in a three-month MVP

  1. Weeks 1–2: setup, architecture scaffolding and first endpoints.
  2. Weeks 3–6: the team focuses on the core flow; AI handles tests, docs and integrations.
  3. Weeks 7–8: help with bug fixes and refactoring.
  4. Weeks 9–12: launch focuses on onboarding and feedback.
Example: Coach IDCoach ID launched with an AI virtual assistant coaches use every day. Without these tools it would have needed a dedicated machine learning team and extra months.

What AI doesn’t change

AI is a multiplier, not a magic wand. A team building the wrong product faster is worse off than one building the right product slowly. You still need a product plan, experienced developers to review and decide architecture, direct conversations with users and the discipline to launch and measure.

AI makes us faster. The method keeps us focused. The stack keeps us consistent.
Marco Mendão
written byMarco MendãoCo-founder and CTO at Betacode. Writes about architecture, product engineering and using the right technology to ship faster.
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