2026: The Year AI Left You Behind

Introduction: A Glimpse Into 2026

Imagine it’s 2026. The software industry (and the world) has undergone a dramatic transformation, reshaped in ways few people could have imagined in the year 2024. Super small, AI-savvy startups — as in, teams of fewer than half a dozen people and even solopreneurs — have emerged as the new industry leaders, creating system after system with truly groundbreaking features. 

The world has a new batch of solopreneurs who have built 9-figure (maybe 10?) businesses in insanely short periods of time, using what was until now considered “unconventional” methods and tools. And their profit margins are beyond belief because they’ve automated their operations to such an extent that efficiencies allow them to avoid the significant overhead still required by other purely human-driven organizations with little to no automation to speak of. Contrary to many predictions, these innovators have seen an improvement in the cost-to-value ratio of using AI since 2024.

And these innovators are continually rolling out new capabilities in a fraction of the time and cost of their larger, more traditional competitors. By combining their own imaginations with their AI skills, these forward-thinking “new age” engineers’ and business leaders’ ability to imagine new possibilities and then deliver on them seem limitless.

Entire industries have been shaken. Slow-moving companies who were certain their “moats” were impenetrable have learned some tough lessons. For some, those lessons came too late. Their reluctance to embrace AI, rooted in skepticism, fear, and often simply ambivalence has proven to be their Achilles’ heel.

IT professionals who refused to acknowledge the reality and instead bet their futures on the false hope that ‘AI will hit a wall and die’ before it threatens their traditional methods have also had to face hard truths.

Some accept this and adapt, although, it’s unlikely they’ll be among the leaders or top earners, since many of their colleagues in the industry have already gone through the school of hard knocks and mastered the use of AI in every aspect of everything they do. The late-comers discover there’s no way to catch up to the sheer expertise of such people, because technology, business and society are changing at an even faster pace. They try to quickly catch up to the target — and the target moves.

But the path to this new reality hasn’t been smooth. Since 2024, we’ve witnessed significant incidents related to AI adoption, particularly in the areas of security and privacy. These events have prompted intense debates about the risks of AI, with critics citing them as evidence of technology’s instability and dangers. 

Even so, such growing pains are not unique to AI. Every major technological leap in history — from the internet to cloud computing — has been marked by similar challenges. Each time, we’ve adapted, learned, and moved forward. The undeniable value of AI has ensured that individuals and organizations who innovated have not only recovered from such setbacks but thrived, evolving alongside this transformative technology.

2024: The ‘Perceived Wall’ Fallacy and the Power of AI Ecosystems

Despite the extraordinary advancements in AI over the past few years, as of the end of 2024 doubts persist. Some claim AI has “hit a wall,” citing a perceived “slowdown” in progress. But this perception stems more from human psychology than reality. 

Comparing the monumental breakthroughs of 2023 with the more incremental — but still powerful — developments of 2024 creates an illusion of stagnation. However, AI is not slowing; it is maturing, expanding its reach, and solidifying its role as an indispensable part of the technology landscape.

If you’re reading this in mid-2025 and you were among the “AI is dead” crowd, you no doubt by now realize how wrong you were.

AI’s real strength doesn’t lie in any single tool or model — it lies in the ecosystem. Just as the power of cloud computing wasn’t unlocked by storage capacity alone but by the interplay of scalable platforms, APIs, and services, AI derives its true power from the combination of advanced models, robust tools, and increasingly sophisticated user expertise. 

AI models + tools/frameworks + user skills -> increased AI capability

Developers today have access to ecosystems that integrate AI seamlessly into workflows, enabling unprecedented efficiency and innovation. These systems are becoming more than tools — they are really smart co-workers.

Explore More If you’d like to learn how to leverage AI tools and build your AI software engineering skills, check out my “Coding the Future With AI” YouTube channel for hands-on tutorials and insights. Also, join my Skool.com community to connect with like-minded individuals, access exclusive resources, and participate in weekly discussions!

The Rise of AI-Augmented Development Teams

AI isn’t replacing developers — it’s empowering them. As I write this in November of 2024, companies like Google already report that AI tools generate up to 25% of all new code across their teams. 

Kelly, J. (2024, November 1). Forbes. “AI Writes Over 25% Of Code At Google — What Does The Future Look Like For Software Engineers?” https://www.forbes.com/sites/jackkelly/2024/11/01/ai-code-and-the-future-of-software-engineers/

Open-source projects such as aider (https://aider.chat/), a popular AI coding assistant, showcase a growing contribution by AI to their projects’ codebases, providing tangible proof of AI’s effectiveness in real-world software development.

I’ve used aider in my work for several months and, even though aider produces several releases every month, I’ve personally experienced exactly ONE bug that affected my work — and the maintainers released a fix within 24 hours. I’ve also reviewed the code. I and other developers with whom I network agree that the design and code are quite maintainable. Of course, the maintainers have really learned how to leverage AI. And herein lies the difference between success and failure with AI.

Although anecdotal, this seems to directly contradict the narrative that AI is ineffective or produces poor-quality code. Sure, in the hands of a naive user who expects a one-shot prompt to produce the next killer eCommerce platform, AI will be disastrous. Developers who invest the time to learn how to guide AI tools effectively are already producing code that matches — and often exceeds — manual efforts.

Also, the focus on AI’s “coding” capabilities often overshadows its much broader potential. AI’s most transformative impact lies not just in generating code but in integrating it across the entire software development lifecycle (SDLC). 

Today, I use AI in every task you can imagine related to software development: ideating on features, generating and maintaining requirements documentation, designing system architectures, generating diagrams, creating a project plan, generating user stories and use cases, generating/editing/documenting code, generating unit tests… Notice how little of this involves "generating code". The ability to “brain dump” my thoughts and ideas, help me refine them and capture them in a well-organized set of documents and diagrams alone saves me an amazing amount of time! And AI tools often point me to new valuable ideas I hadn’t even thought of.

The current hyper-focus on AI’s coding abilities, as if that were all that mattered (or even the most important thing), is beyond misguided. If you’re an experienced software developer, in general, what percentage of your time do you truly spend heads-down on “code creation or editing”? If you say anything North of 50% (and I’m being very generous here), you are in a very exclusive club, my friend, so be grateful :-) 29 years, about a dozen industries, tells me that ain’t normal.

In addition, there’s an area where AI truly shines today: building proof-of-concept (POC) applications. Unlike production-bound applications, which require significant guidance, careful prompting, and extensive review from software engineers, POCs are typically designed to be disposable. They serve to prove a concept, allowing technical and business stakeholders to visualize and prove out an idea and make a go/no-go decision — or refine the concept further. This makes POCs a natural sweet spot for AI tools. 

With just a few well-crafted prompts and a modern AI coding assistant, developers can generate functional POCs in record time. Imagine iterating through a dozen versions of a POC in a single week — this level of agility has become a reality with AI. Even today, this represents a high-leverage, high-value use case for AI that is transforming how ideas move from concept to decision.

Know that, just because you’re unaware of it doesn’t mean it’s not happening. And just because you’ve experimented with AI and have been unimpressed, doesn’t mean AI isn’t impressive. Instead, maybe you should ask yourself: “What is it about AI that I am missing?”

I believe that, by 2026, AI will have become fully integrated into every phase of development. Agile teams will leverage AI to ideate, diagram, and document systems nearly instantaneously, enabling faster decision-making and shorter development cycles. Testing, quality assurance, and security checks will be performed at a speed and depth that would have been unimaginable today. This level of end-to-end integration will fundamentally shift the software development process, enabling teams to focus on innovation rather than rote, repetitive tasks.

Never mind 2026. By mid-2025, I believe these advancements will have begun to redefine software engineering careers. Hiring managers will increasingly emphasize at least basic AI proficiency in technical interviews, preferring candidates who can demonstrate expertise in integrating AI into their workflows. And solopreneurs and insanely small startups will be giving established larger companies major competition.

Over the next couple of years, those who master AI tools will find themselves working on groundbreaking projects, while those resistant to adopting AI will begin to be left behind, relegated to less innovative roles. This is already starting, slowly, imperceptible to those only paying attention to media reports related to AI. But it has started.

The divide between AI-savvy engineers and traditionalists will become stark — reminiscent of COBOL developers, who find steady but uninspiring work maintaining legacy systems. 

Of course, it’s silly to think that we won’t continue to need a lot of developers for legacy systems or that you’re going to be unemployed because you haven’t learned to use AI (at least not for a few years). There are millions of legacy systems in the world — and AI’s not going to suddenly take over maintaining them all. But it’s hard to imagine that NEW software will be developed without the help of AI by the year 2026.

Implications for Careers and Markets

AI’s impact on the software industry is profound, extending far beyond individual engineers to reshape entire market dynamics. By 2026, companies, especially those within the software industry, that fail to integrate AI into their strategies and daily operations will be facing existential threats. 

Longstanding industry leaders, who believed that high technical barriers to entry or entrenched dominance make them impervious to disruption will be proven wrong. Small, agile, AI-driven startups will build products faster, launch with better features, and pivot more rapidly to meet market demands, at a fraction of the cost of their legacy counterparts.

For business leaders, this reality presents both a challenge and an opportunity. The challenge is clear: entrenched processes and resistance to change will not withstand the competitive advantage AI provides to more agile competitors. 

But the opportunity is equally compelling. Businesses that adopt AI effectively can dramatically reduce time-to-market, automate routine tasks across their operations, and shift resources toward innovation and customer experience. This isn’t just about coding — it’s about transforming how products are conceived, developed, marketed, and delivered.

The ripple effects are already being felt across industries. Consider sectors like financial services, healthcare, and logistics, where traditional processes are rapidly being overtaken by AI-driven automation. 

In software, AI-savvy organizations are already releasing features and updates faster than ever before, outpacing competitors who are still reliant on legacy processes. These trends will force all players — startups and incumbents alike — to reevaluate their operating models and skill requirements.

For entrepreneurs, the message is especially clear: the barriers to entry for launching a technology-driven business have never been lower. AI has leveled the playing field, allowing small teams to achieve what once required substantial resources. With tools that automate ideation, design, coding, testing, and deployment, even a two-person startup can compete with much larger organizations, disrupting markets with innovative solutions.

What does this mean for software professionals? It should also be clear that, as business leaders and industries shift more and more towards fully embracing AI, you’ll have to do so as well. Where the market goes, you’ll go — unless you’re getting ready to retire. Demonstrating proficiency with AI tools and techniques will soon become a common requirement. “How would you use AI to help you complete the following task?” is going to be a routine part of interviews.

Lessons for 2024–2025: Preparing for the Inevitable

For organizations and professionals, the message should be clear: waiting is a really bad idea. Ignoring AI or adopting a “wait-and-see” approach won’t shield anyone from its impact. On the contrary, it increases the risk of being blindsided or rendered obsolete by competitors who are already mastering this technology. 

Preparing for this future means actively integrating AI into workflows today. And to do this, requires you to spend time learning about AI and how to best leverage it. Companies must experiment with AI tools across the SDLC, not just for coding but for everything from ideation and testing to security and documentation. Individuals must proactively build AI skills, familiarizing themselves with tools, frameworks, and techniques that make them indispensable contributors in this evolving landscape.

The time to act is now. The pace of technological progress will not slow to accommodate those who hesitate. History has shown that early adopters of transformative technologies consistently reap the rewards, while those who lag behind struggle to remain relevant. Given AI’s incredible pace of advancement and its immense potential impact, this is even truer for AI than for past technological shifts.

Conclusion: The Incredulity of “Innovation Without AI”

As we look ahead to 2026, one truth becomes unmistakably clear: AI is no longer just a tool — it has become the backbone of innovation. Companies, teams, and individuals that integrate AI into their work will lead the charge, defining the future of their industries. Those who resist or hesitate will be left grappling with irrelevance in a world that has moved on without them.

The challenges we face in adopting AI — ethical concerns, security risks, and privacy issues — are not unique to this technology. They are echoes of every transformative leap we’ve made, from the internet to mobile computing. And just as with those prior shifts, the overwhelming value proposition of AI ensures that we will learn, adapt, and move forward.

For software engineers, AI literacy is no longer optional. It’s the dividing line between shaping the future and being relegated to maintaining its legacy. For entrepreneurs, AI represents an unprecedented opportunity to disrupt entrenched markets, reduce barriers to entry, and create solutions that were unimaginable a few years ago. For business leaders, the message is simple: the time to experiment, adopt, and innovate with AI is now.

Imagine telling your customers or investors in 2026 that your organization dismissed AI or gave it a skeptical side-eye in 2024. It’s a laughable notion — because by then, calling yourself “innovative” or “forward-thinking” without having AI at the core of your strategy will be nothing short of incredulous. The future is being built today, and AI is the foundation.

So, what’s your next move? Will you master the tools and techniques that will define the next decade of innovation, or will you be a spectator to the disruption? The choice is yours, but one thing is certain: the world isn’t waiting.