AI's Whopper Moment: The Bespoke Software Revolution
Software's "one-size-fits-most" era is dead.
We’re all familiar with product-market-fit where a product is developed to deliver value to a group of customers. The Product Manager will research, perform discovery to understand what potential customers problems are and how they could solve them via some product. As the product matures, we carve out various personas, add more features to capture more of the market and over time the product has a spectrum of customers who take advantage of a range of features and distribution is something like the below.
What if all of this is about to change? What if AI can allow you to “Have it your way” (Burger King’s iconic mantra)? AI is flipping this model on its head. By 2027-2028, the total addressable market for software will collapse to its ideal size: exactly one person. You.
This isn't just an evolution—it's a revolution in how we interact with technology. Exponential advancements in AI-powered code generation are democratizing software creation, transforming custom solutions from luxury to necessity, and making the personal truly personal.
The old paradigm of adapting to standardized software is giving way to a new world where your apps adapt perfectly to you.
The Problem With Today's Software: Almost Good Enough Isn't Good Enough
The apps we use daily are marvels of engineering, designed to accommodate millions of users with different needs. Yet this universality is precisely their limitation - they can never be perfectly optimized for everyone. Your weather app provides temperature and precipitation forecasts, but doesn't integrate with your golf club's tee time system to suggest the perfect window for your weekend game. Your fitness app offers pre-designed workout plans, but doesn't account for your specific work schedule, sleep patterns, or the equipment you have access to.
We've grown accustomed to software that's almost good enough - applications that meet 80% of our needs while leaving 20% unfulfilled. We adapt our workflows, habits, and expectations to fit the limitations of our tools rather than the other way around. If you expand this to our enterprise environment we have entire departments and hundreds of workflows aligned to how the software works, not how the organization works.
The rapid evolution of AI is poised to invert this paradigm entirely.
AI's Coding Revolution: From Months to Minutes
The capability for AI to generate functional code has advanced dramatically, with tools now able to transform natural language descriptions into working applications. What once required months of development by professional programmers can increasingly be accomplished in hours or even minutes through conversation with an AI assistant.
Research suggests that by 2027-2028, AI could handle up to 90% of development tasks, making it possible for non-developers to create software simply by describing their needs. Tools like GitHub Copilot are already transforming the coding landscape, and this trend will only accelerate. According to a 2025 Medium post, 80% of engineers will need to upskill by 2027, as AI fundamentally changes the development landscape.
The implications are profound - when creating software becomes as simple as describing what you want, the bottlenecks that have historically limited bespoke solutions disappear. This democratization means that the barrier to entry for custom software is plummeting. AI solutions now cost around $100-$5,000 per month in 2025, making customized technology accessible to individuals and small businesses, not just enterprises with massive IT budgets.
The Personal Software Revolution
Let's explore what this future might look like with a fun example. Imagine you're a casual golfer who enjoys playing 3-4 times a year on pleasant evenings. Your ideal weather app wouldn't just show you the forecast—it would orchestrate your entire golfing experience through a seamless workflow:
Continually and automatically scan weather forecasts for the next two weeks on evenings you are available, identifying the best evenings for golf based on your preferences for temperature, wind conditions, and precipitation chance.
Once ideal dates are identified, the app would check availability with your primary group of friends by sending automated inquiries.
If members of your primary group can't make it, the app would automatically notify your secondary friend group of the opportunity while informing your primary group that you'll find another date. (this could get tricky)
When responses come back positive, the app would book the tee time or confirm a provisional reservation that was made earlier.
Finally, it would send confirmations to everyone, complete with personalized recommendations for what to wear based on the expected weather.
This seemingly simple task—scheduling a golf outing—actually involves numerous steps that consume significant time and attention (weather conditions, golf course selection and available tee times, scheduling with a group of people). Would it make sense for someone to build this solution in a pre-AI world? Maybe, if you could find a market of casual golfers large enough but if you could literally just describe what your needs are and what you want to accomplish, and AI builds this app for you? You would probably take a swing at it. 😊
The implications extend far beyond convenience. Consider these other transformative possibilities:
Health and Fitness: Rather than generic workout apps, you could have a personal health companion that adapts to your specific body type, injury history, equipment access, and even your motivation patterns - suggesting exercises, nutrition, and recovery techniques perfectly calibrated to your unique needs.
Productivity: Your task management system could understand how you specifically work best - organizing information according to your cognitive preferences, scheduling tasks during your peak energy hours, and integrating seamlessly with the unique combination of tools you use.
Learning: Educational software could adapt not just to your knowledge level but to your learning style, presenting information in ways that resonate with your specific cognitive patterns and connecting new concepts to your existing knowledge and interests.
In early 2025 we do not have the capabilities to pull this off but what makes this vision increasingly viable is the interconnectedness of Large Language Models (LLMs) via Multi-Agent Cooperation Protocol like Google’s Agent to Agent protocol (A2A) as well as protocols like Anthropic’s Model Context Protocol (MCP) which facilitates models working with business and technology tools to update and change data. These systems can coordinate multiple AI agents, each with specialized functions, to handle complex workflows like our golf scheduling example. One agent might analyze weather data, another might manage communications with friends, and a third might interface with reservation systems—all seamlessly working together to accomplish tasks that would otherwise require significant human intervention.
Enterprises Transformed: The ERP Revolution
This bespoke revolution won't be limited to consumer applications. Enterprise systems, particularly the massive ERP (Enterprise Resource Planning) market, stand to be radically transformed.
Traditional ERP systems represent the epitome of the one-size-fits-all approach - monolithic platforms that companies must adapt their processes to accommodate. With AI providing viable options for quickly writing code, 2025 could be the year companies return to writing custom code to address specific business needs in their ERP systems, connecting through APIs to run tailored tasks like extracting information to optimize supply chains during shortages.
Rather than forcing businesses to conform to standardized workflows, AI-generated code will enable truly customized enterprise systems that mirror a company's unique processes. The result will be significantly improved efficiency, market differentiation, reduced training time, and elimination of the workarounds that plague current implementations.
These intelligent ERP systems can analyze vast amounts of data, optimize processes, predict potential issues, and enhance decision-making. By adopting AI-driven ERP software solutions, businesses can achieve greater efficiency and cost reduction, giving them a significant competitive advantage.
Economics of Bespoke: When Custom Becomes Cost-Effective
Historically, custom software development has been prohibitively expensive for most use cases. The economics simply didn't make sense except for the most critical applications or for enterprises with massive budgets. But AI is fundamentally changing this equation.
Thanks to online platforms embracing AI, smaller businesses can now introduce low-scale AI solutions such as personalized recommendation engines or chatbots, with off-the-shelf solutions starting at around $20,000 – far more affordable than traditional custom development.
As AI capabilities continue to advance, the cost of customization will continue to decrease while the benefits increase. When an AI can generate 80% of an application's code automatically, the economics shift dramatically in favor of bespoke solutions. The question becomes not "Can we afford custom software?" but rather "Can we afford not to have solutions perfectly aligned with our needs?"
AI investments promise substantial returns, with benefits including increased productivity, reduced operational costs, or increased sales resulting from improved customer targeting and experiences. A comprehensive ROI analysis considers both tangible and intangible benefits.
Challenges on the Path to Personalization
While the trajectory toward bespoke software seems inevitable, significant challenges remain before this vision is fully realized. There's an ongoing debate about whether bespoke apps will fully replace generic ones, with several important considerations:
Maintenance and Updates: There are concerns about maintaining and updating numerous bespoke applications over time. While AI could potentially automate much of this process, the sustainability of countless personalized apps remains an open question.
Code Quality: A 2025 Pragmatic Engineer post observed that despite productivity gains from AI, software quality isn't always improving, revealing fundamental limitations in current AI-generated code. Ensuring the reliability and performance of AI-created applications will be crucial.
Data Privacy and Security: Truly personalized applications require access to substantial personal data, raising critical questions about privacy, security, and user control.
Integration Complexity: Bespoke applications will need to communicate with existing systems and services, requiring standardized APIs and interoperability frameworks not to mention different identity management solutions.
The path to production is still relatively long in many enterprises due to governance and security checks as well as standards and compliance boxes that need to be checked.
These challenges suggest that rather than completely replacing generic applications, we're likely to see a future where bespoke apps become increasingly common but coexist with more standardized solutions. The balance will likely shift toward customization, but off-the-shelf options will remain viable for many use cases where the benefits of personalization don't outweigh the costs and complexity of maintenance.
Conclusion: Your App, Your Way
The future of software isn't about choosing between options created for the average user – it's about technologies that adapt perfectly to your unique needs and preferences. What we're witnessing isn't just an evolution in how software is created but a fundamental shift in our relationship with technology.
By 2027-2028, research suggests the creation of bespoke applications will become increasingly accessible to everyone, with AI handling up to 90% of development tasks. The implications extend far beyond convenience – personalized technology has the potential to dramatically enhance productivity, learning, health, and countless other aspects of human experience.
While not everything will be bespoke—maintenance concerns and quality assurance will ensure that some standardized applications remain valuable—the pendulum is clearly swinging toward greater personalization. The one-size-fits-all era of software is giving way to a new paradigm, where your relationship with technology is as unique as you are – a world where many things, if not everything, will indeed be bespoke.
***If you could solve a problem just by chatting with an AI, what would you build? ***