Previously, building sophisticated digital experiences required large, expensive development teams. AI and agentic tools level the playing field, allowing smaller businesses to compete on capabilities that were once out of reach. This creates a new 'guy in the garage' threat for established players.

Tim McLear used AI coding assistants to build custom apps for niche workflows, like partial document transcription and field research photo logging. He emphasizes that "no one was going to make me this app." The ability for non-specialists to quickly create such hyper-specific internal tools is a key, empowering benefit of AI-assisted development.

Individuals will use AI to build bespoke software for personal use. A subset of these tools will find a niche market, creating entrepreneurs who operate outside the VC-funded, subscription-SaaS model, potentially favoring one-time purchase models due to low development costs.

AI is dramatically increasing the capabilities of a single individual, lowering the barrier to entrepreneurship. This technological leverage will enable a massive new wave of solo founders who can build and scale businesses without the need for large teams or significant venture funding.

AI acts as a massive force multiplier for software development. By using AI agents for coding and code review, with humans providing high-level direction and final approval, a two-person team can achieve the output of a much larger engineering organization.

The surprising success of Dia's custom "Skills" feature revealed a huge user demand for personalized tools. This suggests a key value of AI is enabling non-technical users to build "handmade software" for their specific, just-in-time needs, moving beyond one-size-fits-all applications.

Traditional software required deep vertical focus because building unique UIs for each use case was complex. AI agents solve this. Since the interface is primarily a prompt box, a company can serve a broad horizontal market from the beginning without the massive overhead of building distinct, vertical-specific product experiences.

AI is predicted to reduce engineering costs to near-zero, enabling individuals with strong product taste to build, launch, and market SaaS companies alone. The critical skill will shift from coding to user testing and product insight, functions that AI cannot yet fully replace.

While the internet has consolidated around major platforms, AI presents a counter-force. By drastically lowering the cost and complexity of building mobile apps, new tools could enable a 'Cambrian explosion' of personalized applications, challenging the one-size-fits-all model.