Beyond Code: How Engineers Need to Evolve in the AI Era

The software engineering landscape is undergoing a fundamental transformation as generative AI reshapes what it means to be an engineer in the modern era. Ben Greene, a four-time founding CTO and current CTO of Tessi.ai, offers a compelling perspective on how engineers must evolve beyond traditional coding to remain valuable in an AI-driven world.

The End of the Artisanal Engineer

The era of the "artisanal software engineer" is drawing to a close, according to Greene. Generative AI has created a new paradigm where engineers who embrace these tools can achieve unprecedented productivity levels. This shift is comparable to learning how to delegate tasks to other humans—it requires overcoming the fear that work won't be done to exacting standards.

"The time of the artisanal software engineer is passing," Greene explains. "Generative AI lets you be more productive than you ever thought possible if you are willing to embrace it."

This transformation demands a mindset shift. Engineers must learn to manage around imperfection and trust AI tools to handle routine tasks while focusing on higher-level problem-solving.

Beyond Code: Understanding Business Outcomes

As AI tools become more sophisticated, the value proposition of pure coding skills diminishes. Greene argues that engineers must expand their focus beyond technical implementation to understand the larger business outcomes they're building.

"To be really valuable as a software engineer now, you need to understand the larger outcomes that you're trying to deliver," he says. "At a time when designers and product managers and salespeople and everybody else can start getting their hands into code with generative AI, a software engineer who doesn't start expanding their own visibility into the larger business is going to look pretty simplistic."

This expansion of perspective is crucial because tools like Cloud Code, while not yet great high-level engineering thinkers, will continue to improve. Engineers who can point out what these tools miss and think at a higher system level will remain indispensable.

Systems Thinking Beyond Software

Software engineers possess exceptional systems thinking abilities—the capacity to anticipate corner cases and potential failures when presented with a feature. Greene believes this skill should extend beyond code to organizational design and business processes.

"Software engineers are incredible systems thinkers," he notes. "We go into a meeting, someone describes a feature, and we can tell them immediately all the things that can go wrong because they didn't think through every corner case. That's an incredibly valuable skill that, frankly, we should be bringing outside of the creation of software and into the creation of the larger system of businesses and organizations."

This broader application of systems thinking can help organizations bulletproof their processes and identify potential failure points before they occur.

The Forward-Deployed Engineer Model

One emerging trend that Greene finds particularly exciting is the "forward-deployed engineer" model. Companies are increasingly hiring engineers to embed directly with customers, becoming experts not just in their own platform but in the customer's business and challenges.

"This is what we've been telling product managers to do for years," Greene explains. "Don't just interview them, go to their office and sit with them and watch what they do, watch how they interact with your product. Now, we're sending the engineers to do it, which I love, because engineers should stop thinking, 'I just type on a keyboard.' I do go out and I talk to people and I empathize with them."

The ability to empathize and understand customer needs at a human level is becoming increasingly critical as technology advances.

Building Customer Empathy in Engineering Culture

Creating a culture that values customer empathy requires intentional effort. Greene emphasizes the importance of spending time with customers and understanding their real-world challenges.

"You have to go see them doing their job, help them do their job," he advises. "You have to make sure that you engender a belief within the company that what your customer is doing matters and that your customers as people matter."

Even in B2B contexts, Greene reminds us that behind every business decision is a person with personal goals and challenges. Understanding these human elements is crucial for building effective solutions.

Prioritizing Code Quality and Readability

Despite the rise of AI, code quality remains paramount, particularly readability and legibility. In startup environments where rapid pivots are common, engineers must be able to understand and modify existing code quickly.

"When you are going zero to one, looking for product market fit, you're going to have to make a lot of changes on the way, and if you don't understand what you did and why you did it, you have no ability to change that code the way you want to," Greene explains.

His approach to fostering this culture involves modeling vulnerability—admitting when he doesn't understand something and creating psychological safety for others to do the same.

Hiring for the AI Era

The criteria for hiring engineers are evolving. Greene no longer looks for engineers who want to write all the code themselves. Instead, he seeks individuals who can orchestrate AI agents and build things efficiently.

"I'm hiring software engineers to come in and get things built," he states. "If I hire a 10-year experienced engineer who wants to come in and write all the code, I'm not hiring them. If I'm looking for someone to build stuff and someone new at a college has mastered having agents direct other agents, I'm bending over backwards to get them to join."

The key skill is now AI orchestration—the ability to direct and coordinate AI tools effectively to achieve desired outcomes.

Managing AI Agent Reliability Expectations

Greene identifies a critical gap in the current AI adoption landscape: the need for better communication about when AI agents are appropriate and when traditional coding is necessary.

"We need to get better at communicating what sort of problems should be solved with agent-based reasoning and what sort of problems still need to be solved with code," he explains. "There are a lot of companies selling AI agent reasoning solutions boasting 95% reliability, but there are so many engineering problems to which 95% is abysmal failure."

This conversation requires engineers to take a more active role in setting realistic expectations about AI capabilities.

The Critical Importance of Human Communication

As technology continues to advance, Greene identifies person-to-person communication as the critical weak link in organizational systems. While computer-to-computer communication keeps improving, human communication skills often lag behind.

"Person-to-person interaction is critically important," he emphasizes. "Being able to communicate effectively with a person, now being able to communicate effectively with an AI agent, being able to communicate effectively with a computer through code. These are different types, but all equally valid and equally important, because we are all, at the end of the day, part of one big system."

Greene believes that empathy and sympathetic understanding are the foundations for improving human communication. By assuming that everyone we interact with has challenges we know nothing about, we can approach interactions with more kindness and consideration.

The Path Forward

The evolution of software engineering in the AI era requires engineers to embrace continuous learning, expand their business acumen, and develop stronger human communication skills. The most successful engineers will be those who can effectively orchestrate AI tools while maintaining a deep understanding of the human and business contexts in which they operate.

The future belongs to engineers who can think beyond code—who understand that they're not just building software, but creating solutions that affect real people's lives and businesses. As Greene puts it, "There are still so many things that software and technology computers can do to make the world a better place and to make businesses more effective and society run smoother and to help democracy, there are so many things we can do, but we do have to care, or else we're not going to even see them."