𝗔𝗜 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘀𝘁𝘀 𝗮𝗻𝗱 𝗥𝗶𝘀𝗸𝘀

𝗔𝗜 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘀𝘁𝘀 𝗮𝗻𝗱 𝗥𝗶𝘀𝗸𝘀

AI in coding sounds fast. Some experts say it is a big mistake. You risk your software quality if you trust AI too much.

Three main failures happen:

• Lack of review. AI writes code with hidden errors. These errors build up. Your software becomes fragile.
• Poor testing. AI learns in labs. It does not know your real systems. It fails after you launch.
• Wrong use. AI finds patterns. It does not solve complex problems. This creates technical debt.

Relying on AI also kills expertise. You lose senior knowledge. Junior developers stop learning. This leaves your system open to risks.

Use a hybrid model instead.

• Let AI handle repetitive tasks.
• Let humans handle the design.
• Review all AI code.
• Test in real world settings.
• Train your team to work with AI.

Do not pick speed over quality. If you ignore the risks, you pay the price. Balance innovation with oversight.

Source: https://dev.to/maxgeris/ai-integration-in-software-development-addressing-predicted-high-costs-and-negative-consequences-4lli

Optional learning community: https://t.me/GyaanSetuAi