Working in tech over the past decade, I’ve seen many changes, specifically within product creation and software development. Developers and engineers once had to painstakingly write hundreds of lines of code from scratch to create a piece of software. But now, a process that used to take hours to complete can be done much more quickly.
AI agents such as Claude and Gemini are the next evolution of software development, giving even non-technical individuals the chance to “vibe code” and create a unique product. While many worry that these tools are a threat to developers’ careers, AI agents will enhance their workflow rather than replace them entirely.
As someone who oversees a team of talented developers, I know their work processes will evolve, as they have in the past. But despite this, I see great potential for collaboration and creativity. Even with increased use of AI tools, developers will still play a vital role in the creation process because human problems require human solutions.
The Engineer as an AI Orchestrator
Software developers and engineers are increasingly handing off some of the repetitive, time-consuming tasks to AI agents, giving them the space to work on higher-level tasks that require a human at the wheel. As AI improves, this will become even more prevalent. Developers and engineers will become what I like to call “AI orchestrators” – people who instruct AI agents and oversee their work.
Rather than coding everything manually, people in these roles will be responsible for three main aspects of the creation process: designing, directing, and evaluating AI outputs.
Designing the process will involve defining the goals for the AI agent’s workflow, including what to create, how to create it, and any parameters to follow. From there, they’ll direct the AI to start working.
Then, once the agent has completed each task, the individual will evaluate the output to see whether it satisfies the requirements. Education and experience are vital here. Anyone can vibe code, but those with the necessary technical background can spot issues more quickly and improve things more efficiently. Finally, the developer will add any additional guardrails and establish proper feedback loops, and this process will continue until the iteration is complete.
The main benefit of this approach is that it will shorten the software development cycle, increase efficiency, and reduce the amount of time developers spend on repetitive tasks. In this way, AI agents not only accelerate development but also reshape how product teams think about building and maintaining software.
Balancing Opportunity with Responsibility
Many outside of the space might assume that AI agents are the perfect solution and there’s no need for human developers or engineers. In reality, while AI has come a long way since its inception, agents still need to be closely monitored by developers. They can help with repetitive tasks, but over-automation can lead to a variety of problems, including bugs, lower-quality code, and systems that are more difficult to maintain or understand.
To avoid these issues, developers need to define clear constraints, guardrails, and expectations for how the systems should operate. Additionally, developers must continuously review, test, and refine the workflows and outputs of AI agents to ensure they align with the set goals and new technological updates.
While AI can make developers work more efficiently, increased reliance on it will likely lead to shifts in roles, team size, and structure. A recent study by Anthropic noted that computer programmers are among the most notable roles likely to be affected by increased AI use. But as always, the goal of AI should not be to replace humans; it should be to help and empower them. Engineers and developers will be expected to make decisions and take ownership more directly over their work with AI.
Related to this, MacPaw recently completed an intensive two-week AI sprint. This gave all employees – developers and non-developers alike – the opportunity to learn and test out AI systems for themselves. Initiatives like this are critical in building confidence in AI. It also showcases a broader shift that is taking place: success in this new era depends not just on adopting AI, but on how effectively people, systems, and stakeholders work together around it.
Building a Futureproof Ecosystem for AI-driven Development
As developers work more closely with AI, communication between different parties and stakeholders will become even more crucial. Specifically, developers will need to actively communicate with users and organizations, and vice versa, to ensure success. Each party has different perspectives and insights that are vital for the development ecosystem.
In addition to support and proper upskilling, developers will need better, more advanced, and more personalized tools to orchestrate AI effectively. These tools will need coherent governance models and consistent training for developers. Organizations can provide these tools and training to developers. On the other hand, users will provide feedback on the products developers create to ensure they’re high quality and meet their needs.
While AI has made building applications easier, the hardest part still remains: understanding what to build, how to prioritize ideas, and how to create products that resonate with users. Creating a fully functional, valuable product that users love and are willing to pay for is not as easy as one might think.
Striking the right balance can take some time, but the investment is worth it. Our teams have been focused on creating an ecosystem through Setapp that both empowers developers and continuously engages with users to gather their feedback and build the best products possible. Going forward, we’re committed to becoming a place where developers can focus entirely on user problems and product value while we, as a platform, tackle the logistics of delivering those products to users seamlessly.
It’s unlikely AI will ever entirely replace developers and engineers. Instead, those who successfully use AI agents within their workflows will outperform those who don’t. As such, developers and engineers should be trusted to integrate AI agents into their workflow as it makes sense for them. Ultimately, those who thoughtfully balance human judgment with the power of intelligent automation will succeed.
To developers and engineers – both those who are just starting their careers and industry veterans who are worried about the direction of the field: don’t think that change means you’re being replaced. Creativity, innovation, and problem-solving are among the biggest strengths of humans in the field; AI just amplifies them. Stay curious, learn and refine your skills continuously, and focus on becoming an individual who knows not just how to build something, but what should be built and why.
