The next wave of software will be AI-native, industry-specific platforms, writes guest author Richard de Silva who believes the biggest winners will be vertical AI companies with deep domain expertise, proprietary data and strong customer relationships, as these advantages create durable competitive moats that generic horizontal SaaS products cannot match.
Apple’s iOS 27/macOS 27 cycle is revealing something new: AI is only as good as the operating system that supports it. The latest beta releases show that after two years in which the company has promised to become AI-native, testers finally believe it’s happening as Apple prioritizes improved system performance and Siri AI.
For example, the second developer beta (released this week) has clarified the vague “indexing” prompt that showed up two weeks ago, replacing it with a clearer message reading “Optimizing Search and Siri.”
What is indexing doing?
Developers digging into the code found the system is proactively building contextual maps of messages, notes, and photos, allowing the updated on-device architecture to swiftly pull up personal data without compromising privacy. It still takes time, but at least its purpose has been clarified.
The improved indexing seems to deliver smoother device performance overall, reflecting the deep architectural improvements supporting the entire rele
It is tempting to date cloud computing from the launch of Amazon S3 in 2006 and the rise of infrastructure as a service (IaaS) that followed. That was certainly the moment the market changed in a visible, irreversible way. But the truth is that cloud began earlier, in the 1990s, when software as a service (SaaS), application hosting, managed services providers, and various forms of remote subscription computing started to reshape how enterprises thought about owning and operating technology. Even then, the core value proposition was familiar: Let someone else run the infrastructure, abstract the complexity, deliver capability as a service, and allow the business to consume only what it needs.
What AWS changed was the scale, accessibility, and precision of the execution. Amazon turned infrastructure into a programmable utility. It made compute and storage available in ways that were elastic, self-service, API-driven, and globally reachable. That was the breakthrough. Enterprises had out
You know the meeting. The board wants an AI agent strategy by end of quarter. Someone on the leadership team has read a McKinsey report. You’ve been voluntold to build the platform. The slide deck says “AI-native.” The acceptance criteria are vague. Somebody mentions LangGraph, and somebody else says, “We’ll just wrap it ourselves.” You […]
You know the meeting. The board wants an AI agent strategy by end of quarter. Someone on the leadership team has read a McKinsey report. You’ve been voluntold to build the platform. The slide deck says “AI-native.” The acceptance criteria are vague. Somebody mentions LangGraph, and somebody else says, “We’ll just wrap it ourselves.” You […]
Because AI and LLMs are reshaping the traditional SaaS model, founders are forced to focus less on software alone and more on delivering measurable business outcomes, defensible workflow ownership, strong retention, and efficient growth. Crunchbase guest author, Ivan Nikkhoo argues that rather than chasing trends like adding services, founders should build deep moats, understand customer workflows, adapt pricing toward usage- or outcome-based models, and prove that AI creates lasting value.
Tive's innovative single-use 2G tracker slashes costs, fueling growth to a $545 million valuation.
The post Krenar Komoni: Tive reaches $100 million annual run rate, the power of a SaaS plus model for data moats, and the impact of real-time tracking on logistics | SaaS Interviews appeared first on Crypto Briefing.
Opendoor's decision to wind down its 250-person India operation in favour of small, AI-native US teams has renewed questions about the future of offshore operational work.
