2023 was a turning point for the adoption of AI tools in the development of software. Github Co -cilate, cursor and other code assistants enhanced by language models have become omnipresent in the workflows of thousands of developers. More than 50% of programmers already use AI tools, and companies such as Accenture have deployed Copilot to tens of thousands of engineers. Microsoft estimates more than 1.3 million paid users. These tools not only accelerate work (up to 55%, according to Github), but also increase satisfaction: 90% of users feel more made.
But the impact is not limited to writing speed. Today, these tools also generate evidence and documentation, referring code, and even implement complete functionalities. Companies such as Vercel or Lovable allow to build entire web applications from a Promptwhile Startups As AI headlights have measured improvements of up to 15% in code integration rates. In short: AI is no longer an experiment: it is a key part of the development flow.
The software life cycle with AI: from autonomous assisted
The next jump is structural: moving from a process focused on code to a native process in specification focused. This means redesigning the development cycle (SDLC) with AI in the center. Instead that humans write code and the assist, now humans write specifications and the AI generates, tests, maintains and improves the system.
Startups As Tessl are leading this change with platforms that translate requirements in natural language or formal specifications directly into functional code. It’s not just writing less, but operating a completely different process. IA can also be in charge of maintenance: dependencies updates, security patches, adaptation to APIS changes, automatic tests. Vision is an application that remains alone.
Tools such as Devin Ai de Cognition have shown that this is technically viable: he built, displayed and maintained a complete application without human intervention. In companies such as Clenk, an “Devins Army” helped refracting millions of lines of code in weeks, something that would have taken more than a year. Development teams will no longer be formed only by humans, but by humans + AI agents.
The engineer of the future (2025–2027)
In this new paradigm, the role of the engineer changes radically. It is no longer about writing each function by hand, but to design specifications, supervise the output of the AI, and give feedback to correct deviations. They become architects, editors and curators of the product generated by Ia.
Matt Garman (AWS) predicts that in less than 24 months, engineers will describe what they want to build instead of programming it directly. Jensen Huang (Nvidia) has said that “the code could be dead.” But this does not eliminate the programmer: elevates it. Its value lies in understanding the problem, defining the solution and guiding the system to build it correctly. The 2027 developer is an AI agent orchestra director.
This Prompting delivery introduces us to the concept of “service as Sophware ”, A new way of thinking about the traditional SAAS model from the implementation of artificial intelligence based technologies.
New roles are already emerging: “AI Software Engineer”, “Prompt Engineer”, “AI OPS”. Professionals with technical skills but also with domain of generative models behavior. Gartner estimates that by 2027, 80% of the engineers of software They will need to resent to collaborate with AI.
Key data and trends
The transition to native IA development teams is not science fiction: it has already begun. In the next two years we will see an acceleration in the adoption of these practices. The real challenge is not technical, but organizational. It is about learning to work with AI agents as colleagues, and redesign our flows, metrics and equipment structures for an era where the code is written at the speed of silicon.
Final reflection: 2027 is just around the corner
In recent months, working with various companies in Latin America, we have noticed that most organizations are very late in this transformation. Starting with the adoption of tools such as cursor or co -pilot, less than 20% of developers use them regularly. And this applies to both traditional companies and digital native startups.
When we ask: “How many agents of AI actively collaborate with their development teams?”, The most common response, regardless of whether it is a company with 30 years of history or a Fintech Recent is: zero.
2027 is not far. If we want to stay relevant, innovate with speed and compete globally, we need to accelerate this change of mentality and practice. It is not enough to activate a github co -ilot license. You have to redesign the process, form new roles and rehearse new forms of work.
The call is clear: it is time to stop experiencing superficially with AI and start building native equipment, products and cultures of artificial intelligence.
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