Danny Hamam’s Dilemma
Off the clock, New York City-based software engineer Danny Hamam grapples with an incessant sense of urgency. Each new AI tool release ignites a fresh wave of trepidation within him.
“My immediate reaction isn’t excitement; it’s more a panicked realization that I am falling behind. I need to master this, and I need to do it now,” shared Hamam, encapsulating the anxiety many tech professionals feel.
Since the inception of ChatGPT in late 2022, Hamam, like countless others in technology, has faced an avalanche of AI innovations.
Titans like Anthropic, Google, and OpenAI are locked in an unrelenting race to unveil the most sophisticated models.
Danny Hamam, a software engineer, reveals the anxiety induced by the rapid technological evolution he faces. Janice Chung for BI
Peter Assentorp, a Denmark-based coder and designer, has noted that the frequency of major AI model releases has surged to approximately four times the rate of the previous year.
“The pace rose to such heights that I lost track of what innovations were current—and I integrate these models into my daily work,” Assentorp stated.
His records indicate major AI releases escalated from 18 in 2023 to 69 in 2025, with an additional 30 models launched by mid-2026.
The phenomenon dubbed “The Great Coding Reset” is a multi-week series investigating the profound transformation that AI heralds in the realm of software engineering:
Jack Boudreau, CEO and co-founder of the fintech firm Habits, remarked on the futility of becoming an adept user of any singular tool amidst the tumult of constant innovation: “Becoming a subject matter expert feels almost redundant; wait another week, and a simpler alternative will emerge.”
While AI progress heralds possibilities for heightened productivity, it imposes a relentless demand on software engineers to stay abreast of developments, creating a paradox of progress that can lead to workplace paralysis, as anxiety about mastering these emergent tools mounts.
“We’re merely witnessing the tip of the iceberg,” predicted Sacha Greif, a developer located in Japan, foreseeing that AI entities will render numerous stand-alone software products irrelevant, thus hollowing out the ecosystem supporting them.
As AI constitutes its inaugural major breakthrough into professional domains, software developers find themselves at the vanguard of an upheaval, offering insights into the existential challenges looming over various white-collar professions.
Confronting the Coming Shift
The specter of potential displacement looms over those anxious about AI usurping their roles. Greif commences the tech research publisher Devographics, surveying approximately 7,000 developers, and reveals that over 40% express concerns regarding their job security due to AI.
Concerns emerge, in part, from the rapidly evolving nature of their work. Developers are increasingly tasked with overseeing and managing AI systems as coding responsibilities are delegated to these advanced tools, with some capabilities now permitting agents to undertake the prompting as well.
AI’s advancements promise increased productivity, yet necessitate an arduous pace of adaptation. Janice Chung for BI
Annie Vella, a developer from New Zealand, articulated, “We are in the process of constructing the technology that will give birth to further advancements.”
Thus far, these shifts have not precipitated a downturn in hiring trends; however, the implications fostered by AI advancements compel developers to reconsider their engagement with their craft.
Every new wave of models appears to be progressively better at writing code, prompting existential concerns about skills that required years of dedication to cultivate.
Concerns extend to the notion that AI increasingly dictates the workflow, potentially reducing developers to mere “service drones,” cautioned Cary Cooper, a professor at the University of Manchester.
Cal Newport, an author and computer science professor at Georgetown University, noted, “The deep engagement required to code from the ground up yields lasting satisfaction, far superior to merely managing automated systems.”
He remarked that the repetitive task of awaiting model outputs—what some dub ‘botsitting’—can quickly become monotonous.
Simultaneously, engineers face increasing pressure to fully embrace AI technologies. Organizations employ dashboards to monitor AI utilization, track token consumption, and weave AI proficiency into performance appraisals.
Herminia Ibarra, a scholar of organizational behavior at London Business School, stressed that misaligned expectations from employers toward engineers regarding the speed of AI adoption exacerbate these pressures.
“Engineers find themselves ensnared, instructed to innovate while adhering to the traditional modus operandi,” she explained.
Ben Eubanks, an HR technology analyst, noted that the anxiety has become so pronounced among certain software engineers that some are contemplating lateral transitions into sales or support roles.
Optimizing Under Pressure
Conversely, not every engineer feels the weight of fatigue. Developer Rafa Rafael indicated that AI has reduced the time spent on troubleshooting, enabling him to concentrate on requirements and features.
“I find myself engaged more holistically in the product rather than just the coding aspect,” he remarked, residing in the Philippines.
For Angga Pratama, overseeing workflows and managing various AI tools have supplanted much of the traditional coding—a transition he describes as heightening job intensity.
“As the pace accelerates, my focus shifts from ‘Will I finish this?’ to ‘How much more can I optimize?’” he stated, hailing from Indonesia.
The omnipresence of AI discourse can feel inescapable. It pervades workplaces, online platforms, and day-to-day life.
Akshyae Singh, who specialized in cognitive science and AI at UCLA, has sought to channel his uncertainties into constructive action through his San Francisco startup, Frame, which supports creators focused on the societal ramifications of AI.
Hamam recognizes that the pressure to adapt has yielded substantial personal growth and achievement. Janice Chung for BI
Singh anticipates that humanity may ultimately struggle to keep pace with AI systems, asserting, “It’s not biologically feasible.”
While Rafael has embraced the advancements AI offers, the adjustment was profound; he initially found the technology more taxing than traditional coding, necessitating extra hours to experiment with prompts.
Now, he refrains from coding during his off hours, opting to prioritize family, television, and relaxation instead, having curtailed efforts to remain updated with every AI release.
“New tools appear continuously, so I only delve into those I believe will genuinely assist my work,” Rafael elucidated.
The challenge extends beyond individual concerns; organizational dynamics play a pivotal role. Many engineers grapple with the dual anxiety of keeping up with AI while pondering the potential ramifications for their careers, indicated Kathy Gersch, CEO of the change-management firm Kotter.
To alleviate some of the overwhelming noise, Gersch proposed that companies foster environments where employees can share their learning experiences.
This promotes a sense of collective progression rather than a feeling of being submerged by relentless changes.
Despite the anxiety that AI may incite, Hamam emphasizes the rewarding nature of observing personal growth and achievements over recent years. “The pressure has driven me to build things I once deemed improbable,” he concluded.
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