DEVOPSdigest

DEVOPSdigest invited experts across the industry — consultants, analysts and vendors — to comment on how AI can support the software development life cycle (SDLC). In Part 13 of this series, experts offer some final recommendations to ensure success while using AI to support software development.

EMBRACE AI

Embrace it. Learn about AI. Be ready as new advancements in AI technology come. Like any other revolution, industrial, or internet, the gap between those that adopt/adapt versus those that don't, will continue to grow.
Sterling Chin
Senior Developer Advocate, Postman(link is external)

FIND THE RIGHT TOOLS

Choose the best tool to get the job done. Throughout my career, I've often been asked what is the best programming language. To which I would reply with the following question. What are you trying to accomplish? Just as each programming language has its own strengths and weaknesses that make one more appropriate for one project over another, the same will be true for AI.
Scott Willson
Head of Product Marketing, xtype(link is external)

In an attempt to adopt AI, many companies are attracted to rushed solutions. However, the perceived effectiveness of many AI-powered workflow solutions isn't reality. After demos, or worse, the software is implemented, organizations often find that the actual performance and usability that meet their unique business needs fall short of what they expected after the initial sales pitch. This post-demo disappointment can be avoided. Decision-makers must look beyond the superficial appeal of mega-consolidated software, and instead, focus on considering solutions that are truly designed to be easily integrated, scaled and usable.
Eoin Hinchy
CEO and Co-Founder, Tines(link is external)

LISTEN TO YOUR DEVELOPERS

Listen to your developers. They'll tell you what's adding value and what's not!
Matt Healy
Director of Product Marketing, Intelligent Automation, Pega(link is external)

FOSTER A CULTURE OF EXPERIMENTATION

Different developers and teams have different attitudes toward generative AI. Some are embracing it, while others remain skeptical. I recommend introducing a culture of experimentation and demos on generative AI tooling. Often, the skeptics just haven't spent enough time on appropriate use-cases to experience a real-life win associated with the technology. Hosting a hackathon, with prizes, that focuses on using generative AI to accelerate innovation or reduce development time can be a good starting point to get your team inspired.
Matej Bukovinski
CTO, Nutrient(link is external)

It's advisable to keep AI environments open and flexible, allowing teams to experiment and innovate without overly restrictive controls. This is possible today through self-hosted models, chat interfaces, or with team subscriptions to ChatGPT or other providers. This approach fosters creativity and helps developers become more comfortable with AI as a valuable part of their toolkit.
Michael Webster
Principal Software Engineer, CircleCI(link is external)

PRIORITIZE USER EXPERIENCE

Prioritize user experience (UX) and ensure that AI is applied in ways that genuinely enhance it rather than using AI for its own sake. For example, integrating AI into development environments to streamline tasks like code editing or facilitating smoother transitions between tools can significantly improve the developer experience.
Michael Webster
Principal Software Engineer, CircleCI(link is external)

ENABLE ACCESS

Organizations need to enable access so that developers can find the solutions that work for them. Software development and workflows are deeply personal, and individuals will have their own preferences.
Rodric Rabbah
Principal Scientist, Flows & AI, Postman(link is external)

Encouraging teams to sign up for tools by not restricting licenses or seats on AI platforms can be a practical way to introduce AI into the workflow and broader team.
Michael Webster
Principal Software Engineer, CircleCI(link is external)

TRACK PERFORMANCE

Before implementing AI support for development, define your goals and map those goals to metrics and measurements. From those goals, evaluate which AI tools may be beneficial for the team and be thoughtful in designing your pilot processes and how you roll it out to the team. Also, consider any additional coding standards, policies or testing practices that may need to be modified for your organization. Once in place you can evaluate your goals against the metrics to understand the impact of AI support for your team. For example, is our use of AI tools increasing or decreasing productivity? Are we producing quality code? What are our bug levels? Understand how you want to leverage AI support for development.
Robert Rea
CTO, Graylog(link is external)

HIRE AI EXPERTS

Companies should prioritize hiring developers who have a solid understanding of AI, even if they do not master every aspect of this rapidly evolving field. It is important to focus on candidates with practical experience in successfully implementing AI solutions in production environments. Strong coding skills are essential for developers working with AI, as is the ability to communicate AI concepts effectively to non-experts. These skills will be crucial for integrating AI into development processes and maximizing its potential benefits.
Tom Hodgson
Innovation Tech Lead, Redgate(link is external)

It all comes down to how prepared your engineering teams are. The AI boom is reminiscent of the mobile app development boom of 15 years ago. Where there was once an urgent demand for mobile app developers, there is now a demand for AI engineers. This lesson of the past is a place for companies to learn strategies for successful AI support in development. With the demand for AI engineers outpacing supply, hiring the right engineers, AI or otherwise, is key to ensuring AI implementation is effective. This means taking a two-pronged approach — hiring AI experts, and leveraging the skills of your existing engineers who can be upskilled by these experts.
Scott Bonneau
EVP of Product and Operations, Karat(link is external)

INCORPORATE AI INTO THE INTERVIEW PROCESS

There is concern about the potential over-reliance on AI. Companies will need to make sure their engineers understand the code, even if it's produced by AI tools. To accomplish this, implementing new standards at the beginning of the interview process is key. Incorporating AI tools into technical interviews, or using code reviews to assess how the candidate analyzes AI-generated code, are just some of the ways companies can ensure efficient adoption of AI tools.
Scott Bonneau
EVP of Product and Operations, Karat(link is external)

EMPOWER CONTINUOUS IMPROVEMENT

Developers should be empowered toward continuous improvement by placing those with increasing development/AI skills on the most critical applications/assignments.
Pieter Danhieux
Co-Founder and CEO, Secure Code Warrior(link is external)

INVEST IN DEVELOPER TRAINING

Upskill your existing engineering team on AI and machine learning concepts.
Patrick Doran
CTO, Synchronoss(link is external)

Investing in training for developers to effectively use AI tools is an essential component to making the most of AI's benefits.
Jobin Kuruvilla
Head of the DevOps Practice, Adaptavist(link is external)

Provide training for DevOps teams to ensure they know how to work with AI tools effectively. This includes learning how to interpret AI outputs, integrate AI into workflows, and address any ethical concerns.
Ed Frederici
CTO, Appfire(link is external)

PROVIDE SECURITY TRAINING

Companies seeking to leverage AI need to have proper training in place to ensure the developers implementing it have foundational security awareness and know how to protect code from the start of the software development lifecycle (SDLC). For instance, those entrusted with AI should be able to spot poor coding patterns, and therefore be able to determine which AI outputs are trustworthy and which are not.
Pieter Danhieux
Co-Founder and CEO, Secure Code Warrior(link is external)

CULTIVATE JUNIOR DEVELOPERS

AI widens the gap between junior and senior developers. Seniors are always going to be necessary, so companies need to be aware of that. Everybody is going to have to make sure that they don't get lazy and let their own skills slip when they have AI as an assistant. Companies will need to work harder to make sure they have the senior developers they need. That will probably involve being very intentional about training junior developers.
Mike Loukides
VP of Emerging Tech Content, O'Reilly Media(link is external)

ARM DEVELOPERS WITH KNOWLEDGE

Balance your investments, and don't forget about your workforce. Just as you're considering investing in AI to support your software development, don't forget that investment is necessary for your developer team. Take time to research and invest in education for your developers, ensuring they know how best to work alongside AI, understanding where it's a game-changer, and where it's still falling short. Arming your workforce with this knowledge will set your AI implementation strategy up for success, and avoid wasted hours in your deployment pipeline.
Scott Willson
Head of Product Marketing, xtype(link is external)

UTILIZE LOW CODE/NO CODE

For enterprises seeking to boost development productivity, don't just focus on AI — explore AI-enabled low-code solutions as well. These platforms offer even greater efficiency and provide seamless IT/Business collaboration that significantly accelerates developing and deploying enterprise-grade software.
David Brault
Product Marketing Manager, Mendix(link is external)

Platforms that offer low-code/no-code capabilities on a unified platform can help companies simplify the integration of AI, making app development more accessible for developers of all skill levels.
Jithin Bhasker
GM & VP for the App Engine Business , ServiceNow(link is external)

As AI-generated code improves in the near term, a rapid rise of citizen developers will be seen, and having a plan and pipeline to handle this new throughput will be critical to ensuring the integrity and security of your network and infrastructure. Deploy IT resources now to build out processes, procedures and pipelines for this new volume of code production to ensure stability and safety.
Scott Willson
Head of Product Marketing, xtype(link is external)

STAY UP-TO-DATE

Teams need to emphasize continuous learning to stay up to date with how AI is evolving, particularly early in the adoption of AI, creating channels to share and encourage ways to use it successfully.
Shourabh Rawat
Senior Director, Machine Learning, SymphonyAI(link is external)

Stay Informed: Keep abreast of the latest developments in AI for cybersecurity and software development. Engage with research and thought leadership to understand the evolving landscape and how AI can support your development goals.
Javed Hasan
CEO and Co-Founder, Lineaje(link is external)

AI tools are continuously evolving. LLMs are the hot new thing, but traditional AI technologies such as supervised learning and NLP are still the best tools for certain tasks. New advancements such as on-device LLMs or specialized modules within LLMs can significantly change how we interact with LLMs, so companies need to keep up to date with the latest AI technologies to ensure they're ahead of their competitors.
Leo Jiang
Staff Software Engineer, Amplitude(link is external)

Go to: Exploring the Power of AI in Software Development - Part 14: 2025 Predictions and Beyond