AI in Business: Making Smart Choices About New Features

Article Summary

In the past, adding a new small feature to a computer system meant that writing the code was usually the most expensive part. Today, this has changed a lot. With new tools like Artificial Intelligence (AI), writing the first version of code has become much cheaper and faster. Because of this, the real cost for businesses is no longer the writing of the code itself. Instead, the most expensive part is often the meetings and long discussions about whether to create the code at all.

Engineers used to be careful about every small request. They learned that even small changes could lead to big problems. For example, a two-hour code change might take two weeks if it affected an important part of the system. So, engineers would spend a lot of time discussing if a change was truly needed, if it was part of the plan, and if it could cause problems later. These long talks made sense when writing the code was expensive. However, with AI, an initial piece of code, called a 'patch,' can be created very quickly. This means that trying out an idea is now much cheaper than having a long debate about it.

The article suggests a new way to work. Companies can use AI to quickly create a first draft of the code. This draft is not the final product; it is a test. It helps teams check important things: Does the code affect only the right files, or does it spread to many parts of the system? Is it easy to test, or does it create new problems? This quick test helps people make better decisions. If the AI-generated code is simple and works well, it can be approved easily. But if it causes many issues, the team learns quickly that the change is actually very big and costly to manage in the long term. This approach saves time and helps businesses understand the true cost of changes before they commit to them. The real skill now is knowing which changes are cheap to try, not just cheap to write.

Key Vocabulary

Comprehension Questions

1. What was typically the most expensive part of adding a small feature in the past?

• A) Testing the code
• B) Designing the feature
• C) Writing the code
• D) Marketing the feature

2. According to the article, what does AI help companies do instead of having long discussions?

• A) Hire more engineers
• B) Create a quick 'patch' of code
• C) Teach new skills to staff
• D) Manage marketing campaigns

3. Why is it important for teams to carefully check an AI-generated code 'patch'?

• A) Because AI code is always perfect and needs no review
• B) Because AI code is often too long and needs to be shortened
• C) Because it helps understand the true long-term cost and problems
• D) Because it makes the team work slower if not checked

4. What new skill is important for engineers in the AI era, as mentioned in the article?

• A) To write code much faster than before
• B) To always say 'yes' to new requests
• C) To quickly understand and 'price' how uncertain or risky a change is
• D) To stop having any discussions about new features

5. Do you think using AI to create a 'patch' before full development is always a good idea for every type of business change?

• A) Yes, because it always saves time and money
• B) No, because AI cannot create good code for serious changes
• C) Yes, but only for simple changes that are easy to check and manage
• D) No, because it makes decisions too quickly without enough human thought

Discussion Prompts

1. How has technology changed the way tasks are done in your company today compared to five years ago?

2. Can you think of a time when a 'small' project in your work became much bigger or more expensive than expected? What happened?

3. Do you think using AI to test new ideas quickly could help your team make better decisions? Why or why not?

Live Session Prep & Cheat Sheet

🎯 Speaking Targets (Vocabulary)

Try to use these target terms in your speaking turns:

• feature request
• scope
• patch
• ownership cost
• validate

⚙️ Grammar Target Formula

Comparing Past and Present Situations: 'Used to' vs. 'Now': Past: Subject + used to + Verb (base form) ; Present: Subject + now + Verb (simple present)

💬 Discussion Openers

Use these phrases to open or structure your arguments:

• In my opinion...
• I think that...
• What do you think about...?
• That's a good point.
• Could you explain more?

Teacher Notes

This lesson focuses on how AI is changing business decisions, especially in technology development. Encourage students to share personal examples related to how new tools affect their work processes. Pay attention to their use of 'used to' and 'now' when comparing past and present situations, and gently correct if needed.

Speaking Class Facilitation Guide (Tutors/Moderators Only)

🎭 Role-Play Scenario

Situation: Your company wants to add a new 'last active' status to its customer website. It seems like a small change. Your team needs to decide if it's truly simple or if it could cause bigger problems later.

Goal: Decide whether to use AI for a quick test first, or to have a long meeting to discuss all possible risks before doing any work.

⚖️ Debate Prompt

{"side_a":["AI saves time and money, helping find real costs early.","It leads to faster product updates and customer satisfaction.","Quick tests can show if an idea is good or bad without large investment."],"side_b":["AI might miss important hidden risks, leading to bigger problems later.","Long discussions are necessary for important changes to ensure quality.","It could create more problems if not planned carefully by humans."],"question":"Should businesses use AI to quickly test all new feature ideas, even if some risks are unknown?"}

💡 Discussion Facilitation Tips

Encourage students to use 'used to' and 'now' when comparing different approaches. Prompt students to provide specific reasons for their arguments using phrases like 'because...' or 'for example...'. Help students express agreement or disagreement politely using B1 phrases.

Session Blueprint

How has technology changed the way tasks are done in your company today compared to five years ago?