What AI assisted development changes for buyers

A change in the daily work

Most software teams now use AI coding assistants as part of ordinary work. A developer describes a function, a form or a test, and the assistant drafts it. The developer reads the draft, corrects it, and fits it into the rest of the system. For many routine tasks, that loop is quicker than writing every line by hand.

If you are buying software, this matters to you in two ways. It changes what a sensible price looks like, and it changes what you should check before you hire a team. It is also part of what makes the 2good.dev price possible.

What AI assistants change

Routine code takes less time

A large share of any business system is routine: screens that list and edit records, forms with validation, API endpoints that read and write a database, reports that export to Excel. Experienced developers have written these many times. AI assistants are good at drafting this kind of code, and a developer who knows what good looks like can check and correct the draft quickly.

Take an Ahmedabad clinic chain that wants patients to book appointments over WhatsApp. The booking screens, the staff calendar and the admin pages that list appointments are routine work, and an assistant can draft much of it. The rules about which doctor sees which kind of patient, and what happens when a patient cancels late, still need a person who understands the clinic.

Review matters more

When code is drafted faster, the careful reading of that code becomes the main safeguard. AI assistants produce code that looks right and is sometimes wrong in small ways: a missing check, an edge case ignored, a library used in an outdated way. A good team treats every AI draft as a first draft from a quick but inexperienced colleague. Someone who understands the system reads it, questions it and fixes it before it goes further.

This is why senior review has become more valuable. The senior person spends less time writing routine code and more time checking the structure, the security and the decisions that will be hard to change later.

Testing matters more

Faster code means more code to test. Teams that use AI well also write more automated tests, often with AI help, and they run them on every change. Manual testing against the specification still matters, because it is the only way to see the system as your users will. For you as a buyer, a team's testing habits are a better guide to quality than any claim about tools.

Documentation can be easier to keep up

Assistants can draft README files, setup notes and explanations of how a module works. These drafts still need a person to correct them, and they make it easier for a team to hand over clear documentation with each delivery.

What AI does not change

The specification

An assistant can write a screen. It cannot tell you which screens your business needs. The hard part of most projects is deciding what to build: which rules matter, which reports people actually use, which steps can be dropped. That work happens in conversation with you and ends in a written specification. AI tools can help draft and tidy that document, and the decisions in it still belong to you and the people who know your business.

A Surat textile trader wanting a dealer ordering app still has to decide how credit limits work, which dealers see which prices, and what happens when stock runs out. Those answers shape the system far more than the speed of typing code.

Judgement

Choosing a database, deciding how two systems should talk to each other, spotting that a requirement will cause trouble at scale: these are judgement calls. They come from people who have seen similar systems succeed and fail. An assistant can suggest options. A person has to choose, and has to answer for the choice.

Acceptance

At the end, you test the work against the specification and decide whether it does what was agreed. That step stays exactly as it was. Whether a line of code was typed by a person or drafted by a tool makes no difference to whether the invoice report totals correctly or the booking confirmation reaches the patient. This is one reason pay after acceptance fits well with AI assisted work: you judge the result, and the method is the team's responsibility.

Questions to ask a vendor

If a team says it uses AI tools, that is normal and generally a good sign. What matters is how well they use them.

Who reviews AI written code?

Ask who reads the code before it reaches you, and what they check. A good answer names a role, such as a senior developer, and describes the review: structure, security, tests, readability. Be cautious if the answer is vague.

What about licences?

AI assistants learn from large amounts of existing code. Ask how the team makes sure the code delivered to you is free of licence problems, and which open source libraries the project will use, under which licences. Ownership of the delivered code, and when it passes to you, should be written into your agreement. For anything you plan to sell or raise money on, it is worth asking your lawyer to read that clause.

What data is sent to AI tools?

When a developer uses an assistant, parts of your code, and sometimes sample data, are sent to the tool provider. Ask which tools the team uses, what those providers do with the data, and whether real customer data ever leaves your systems. If your system handles personal data of Indian users, the Digital Personal Data Protection Act applies, and overseas clients may have their own rules. Agree in writing what may and may not be shared with AI tools.

How do you handle security?

Ask how the team checks for common security mistakes, how passwords and keys are stored, and whether anyone looks specifically at security before release. AI drafted code can repeat insecure patterns found in public code, so this check matters.

How do you show progress?

Ask how you will see the work as it is built. Regular increments you can click through tell you far more than reports of hours spent.

Why the 2good.dev price is possible

2good.dev charges USD 2 or INR 199 an hour at the Prime tier, in blocks of 150 hours, with no advance and payment after acceptance. Plus is USD 5 an hour and Pro is USD 10 an hour, with INR prices on request. Taxes apply as usual. Three things make that price work, and why the price covers each in more detail.

AI changed the daily work

Routine code takes much less time to draft than it used to. That leaves more of each block for the parts that need people: understanding your business, reviewing code, testing and talking with you.

People trained on the job, with a senior checking each stage

Much of the work is done by people trained in the Code Colonies on the job programme. They work on real projects, and a senior checks each stage before it moves on. Senior technical review, testing and project management are included in every block at no extra charge. You get careful work at an honest price, and new developers learn the right habits on real systems.

Priced close to cost

Code Colonies passes the saving on and prices close to cost. The model relies on volume, referrals and clients who choose to stay for further blocks.

The AI tool budget

Each tier includes a USD 50 AI tool budget per block. It covers AI coding assistants, AI testing tools and API usage for AI assisted delivery. The tiers differ in how much senior time goes into each block; tiers compares them.

For many routine business systems, the same budget can now buy several times the work it bought a few years ago, given a clear specification and careful review. Your own first block is the fairest test.

A sensible way to start

If you are curious but cautious, start with one well defined piece of work. Write the specification carefully, ask the questions above, and test the result as you would test anything you pay for. The tools a team uses matter less than what you can see working at the end, and whether it does what the specification says.