Artificial intelligence is not a buzzword. There is serious money behind everything AI, mostly because it’s real. The practical usage of generative AI proves useful in industries across the board. Amazon Q – the AI-powered assistant for accelerating software development is next in line for your time and attention. Does it hold up? Where are the benefits? Should you be interested?

As an AI-proficient software development company, Code & Pepper focuses on delivering value. AI gives us the opportunity to speed up development processes, boost quality assurance, and more. The newest addition to the mix would be the Amazon Q.

What is Amazon Q?

Amazon Q is a generative AI that plays the role of a software development assistant. With it, teams can generate code, debug applications, plan production on multiple levels, and even implement the code based on developers’ demand. 

It also plays the role of data mining assistant. We probably should not use the phrase “business intelligence” to not overhype the tool, but certain features are aimed at this target. Amazon Q is capable of answering questions based on company data. Information such as employee base, company policies, internal regulations, and business data from the sales and marketing department can be mined. That way you can get an overall summary, and information on trends, and get into a dialogue with an assistant, about that data.

According to Amazon, the assistant is designed around companies’ internal data and the idea that developers should spend more time coding and less time with maintenance. It allows dashboard building, using natural language to operate with.

The idea behind the chatbot

According to internal Amazon research, developers spent only 30% of their time coding, with the rest invested in repetitive tasks and maintenance. Working with forums, documentation, and making sure that bug fixing is implemented correctly, isn’t exactly app building. It’s administration. 

Sure, it all very between companies, but add to the mix also resources and infrastructure management, troubleshooting, meetings, focus on operating costs, and sometimes people management. 

Then we have coding (wow, finally!), code refactoring, updating the code repository, tool search, configuration, and optimization, scanning for application’s security vulnerabilities… In order to deploy digital products faster, Amazon decided to launch Q as an additional help for developers. It won’t create an app and make your coffee, but it can be a valuable asset.

Amazon Q’s generative AI capabilities

Among others, the giant’s assistant is capable of many things, useful for project managers and developers alike. Including:

  • Accurate coding recommendations. Amazon Q uses the client’s code database to provide its own recommendations. Amazon claims the system is more reliable than what’s already on the market. Plus, it has an underlying foundation model (FM) that doesn’t use customer data for training, thus keeping the company’s intellectual property secure.
  • Developer agents. This is an interesting USP. Amazon Q has a function called “agents”, which can autonomously perform a range of tasks–everything from implementing features, documenting, and refactoring code, to performing software upgrades. A developer can ask Q about the implementation of a certain feature to the app and the assistant will generate a step-by-step implementation plan.
  • Security vulnerability scanning and remediation. Amazon Q can scan code for hard-to-spot security breaks, such as log injections. The chatbot can generate a recommendation based on the type of threat, greatly supporting developers in the system patching process.
  • AWS environment optimization. Error diagnostics, selecting instances, optimization of structured query language (SQL) queries, extraction, transformation, and ETL pipelines loading, and optimization of the cloud environment. These are the tasks that can be thrown upon Amazon Q. Resource allocation and environment configuration suddenly became more pleasant. 
  • Massive data source unification. Amazon Q can connect to 40+ commonly used business tools, such as wikis, intranets, Atlassian, Gmail, Microsoft Exchange, Salesforce, ServiceNow, Slack, and Amazon Simple Storage Service (Amazon S3). It’s great for unification, drawing conclusions from data, and trend analysis.
  • Security and privacy in the first place. All user identities, roles, and permission access can be managed to personalize interactions for individual users in the system. Users can block sensitive topics or filter out keywords. Amazon claims that Q is ideal for the fintech industry (because of a FiQA dataset sample) and IT in general (using a LoTTE dataset sample).
  • Creation of detailed dashboards in minutes. With the use of Amazon QuickSight, users can use natural language to build a dashboard in a matter of minutes. Business analysts can create visualizations and calculate different business outcomes. Users can also ask questions about what is presented in the dashboards, and create detailed and customizable data stories highlighting key insights, trends, and drivers.


As an Amazon Web Services consulting company, Code & Pepper welcomes new additions to the AWS family. We hire the top 1.6% developers on the market to tackle challenges just like that. Working with AI is normal for us because the landscape has changed.

Today, only centaur developers can provide an accurate level of certainty, quality, and delivery. We know, we have been here for 17 years. We had remote work before it was fashionable and used AI-driven tools before the topic blew up. We believe in efficiency. That’s why Amazon Q seems interesting – we can pair it up with an already amazing team. Development is about cooperation after all.

More on Amazon’s usefulness here, in our article on its frontend and backend solutions.