Leverage Vision: When AI Makes Software a Commodity, Why Becomes the Only Competitive Advantage

Software Is Now a Commodity. The Question Is: What Are You Building and Why?

At Davos 2026, every conversation was about AI. Not some conversations. Not most. Every single one. Anthropic CEO Dario Amodei told the audience that AI models would replace the work of all software developers within a year and reach Nobel-level scientific research within two. Elon Musk said AI could surpass humanity's collective intelligence within five years. The IMF's Kristalina Georgieva said 40% of global jobs will be impacted in the next couple of years, rising to 60% in advanced economies.

These are not abstract predictions from futurists at a cocktail party. These are the people building and deploying the systems making these predictions come true. And the single most important implication of what they are saying is something nobody at Davos fully articulated: the delivery of software is becoming a commodity. The marginal cost of building digital solutions is approaching zero. Which means the only thing that still matters is knowing what to build and why.

The Marginal Cost of Code Is Going to Zero

Consider the math. Claude Opus 4.5, released in November 2025, achieves 80.9% on SWE-bench Verified, the gold standard for real-world software engineering tasks. It can independently analyze technical documentation, plan an implementation, write the code, and iteratively refine it. Multi-day development tasks compress into hours. Products that once required 20+ engineers can now be built by teams of 2-5. Development timelines of 12-18 months are shrinking to 3-6 months.

AT&T built an internal data product in 20 minutes that would have taken 6 weeks without AI. CNBC's Deirdre Bosa, with zero coding or technical experience, whipped up multiple working applications in weeks. Josh Kopelman of First Round Capital calls these compressed commoditization cycles — the time between an innovative feature and a widely available alternative shrinking from years to weeks.

The SaaS index fell 6.5% in 2025 while the S&P 500 rose 17.6%. Wall Street is already pricing in the disruption. As BetterCloud reports, the traditional economic moat of software — high upfront development cost, maintenance complexity, specialized engineering talent — is dissolving. Bain & Company research confirms that 2026 will be the inflection point where enterprises become convinced that custom applications built to their specific use cases beat buying off-the-shelf subscriptions.

Software may have eaten the world. But AI is eating software. And the thing about commodities is that nobody gets rich producing them. You get rich by knowing what to do with them.

When You Can Build Anything, the Only Question Is Why

Here is the leverage point most people miss. When the cost of building drops to near zero, the constraint shifts entirely from execution to intention. You can now describe “a SaaS tool for managing freelance invoices with Stripe payments” and watch an AI select the database schema, generate CRUD APIs, build a responsive UI, and integrate payment processing. The bottleneck is no longer whether you can build it. The bottleneck is whether you should. Whether you have a clear enough vision of what the experience should feel like, why it matters, and who it serves.

This is the most important shift in the history of technology and business. For decades, the question was: can we build it? Then: can we ship it fast enough? Now: do we know what we actually want? The future of design is “not just creating usable interfaces but designing adaptive systems that understand and act on user intent.” The technology should be guided by the experience you want to achieve.

Accenture's Julie Sweet said it at Davos: the approach should be “human in the lead, not human in the loop.” The difference matters. In the loop means you are reacting to what the system produces. In the lead means the system builds what you envision. But leading requires knowing where you are going. And most people, most teams, most organizations have never done the deep work of figuring that out.

Vision to Matter: A Framework for the Post-Commodity Era

This is exactly why Vision to Matter exists. Traditional delivery frameworks start with requirements and sprint planning. They assume you already know what you want. But in a world where delivery is a matter of tokens and dollars, where putting the words into the system is the hard part, the framework that wins is the one that helps you figure out who you are, what you see, and how you want it to feel.

Vision to Matter begins with three foundational phases that no other delivery framework addresses:

With these three foundations established, Vision to Matter proceeds through six additional phases: North Star (strategic direction), Ecosystem (know your stakeholders), Products (your unique magic), Fund (sustainable resources), Launch (go-to-market), and Legacy Cycle (continuous renewal). But every decision in those later phases is grounded in who you are, what you envision, and how you want it to feel. This is what makes it fundamentally different from every other framework. The later phases become almost mechanical once the foundations are clear. And in 2026, the mechanical part is exactly what AI handles.

The Leverage Equation Has Flipped

In 2024, the leverage was in knowing how to build. Engineers commanded premium salaries because translating ideas into working software required scarce technical skill. In 2026, McKinsey projects generative AI alone could unlock $4.4 trillion in annual value globally. Cognizant research presented at Davos puts the U.S. labor productivity opportunity at $4.5 trillion. The leverage has flipped. The scarce resource is no longer the ability to write code. It is the ability to know what code to write.

As one engineer wrote in response to Opus 4.5: “The developers who fear replacement are often the ones who have defined their value as ‘the person who writes the code.’ But the value was always ‘the person who knows what code to write, and whether the code that exists is correct.’” That distinction is now worth trillions.

Your 30-60-90 Day Vision-First Roadmap

Days 1-30: Know Thyself

• Complete holistic personality assessments (DISC, Enneagram, Myers-Briggs, StrengthsFinder) and use AI to synthesize a composite profile
• Map team dynamics: identify communication styles, conflict patterns, and creative strengths across your organization
• Begin daily reflection practice: 10 minutes on what energizes versus depletes you
• Audit your current projects: are they aligned with who you are, or with who you were five years ago?

Days 31-60: Vision and Ethos

• Conduct guided vision sessions: visualization, breathwork, creative exercises to articulate the future you actually want
• Define 3-5 non-negotiable values and write specific behavioral examples of each one in daily work
• Design your ethos: what does a Tuesday afternoon feel like for your team? What does your customer feel during their first interaction?
• Use AI tools (Claude, Opus) to rapidly prototype three different versions of your digital vision — experience each one

Days 61-90: Build From Foundations

• With vision and ethos crystallized, use AI-powered development to build your first working prototype in days, not months
• Test every feature against your ethos: does this interaction feel the way we designed it to feel?
• Implement feedback loops where real users evaluate the experience, not just the functionality
• Establish a Legacy Cycle review: has the building process itself aligned with your values?

Charlotte: Where Vision Meets Matter

Charlotte and the Lake Norman region sit at a unique intersection. According to CharlotteWorks, 58.8% of local jobs are potentially automatable. NC Commerce reports that 68% of small businesses are adopting AI but only 41% have adequate workforce training. The Charlotte AI Institute at UNC Charlotte is building institutional capacity, but the gap between institutional pace and AI pace creates an enormous opportunity for businesses willing to move faster.

At Holistic Consulting Technologies in Davidson, we work with Charlotte-area businesses and entrepreneurs who understand that the delivery problem is solved. What remains is the human problem: knowing what you want, why you want it, and how you want it to feel. That is the work that compounds. That is the leverage that scales. And that is what Vision to Matter was designed to unlock.