Software Is Eating Itself: Why Execution Alone Is No Longer Enough
TL;DR:
Execution used to be the moat. Now it’s the commodity.
MVP costs are collapsing, AI is integrating like REST APIs, and protocols like Anthropic’s MCP are making productization trivial.
In this post, I unpack the macro collapse in execution cost and explore what enduring moats will matter most in a world where anyone can ship.
Strategic judgment. Proprietary data. Market understanding.
Welcome to the world where software is eating itself.
In 2011, Marc Andreessen declared that “software is eating the world” (Andreessen Horowitz). Now, over a decade later, software is devouring itself. Code is writing code, and the barriers to software creation have collapsed – AI can generate applications from a prompt, and no-code tools let anyone build programs in hours. The upshot? The once-formidable moat of execution is no longer enough. Execution is ubiquitous, democratized, almost commoditized. Simply shipping a product is no longer sufficient; enduring advantage comes from strengths beyond code.
Several forces have made software execution dramatically easier and cheaper. Cloud platforms and open-source components have slashed the cost of launching new products by orders of magnitude (Andreessen Horowitz). Modern development frameworks and automation accelerate the process: using cross-platform tools like Flutter can cut MVP build costs by ~30–40% (Ptolemay), and AI-augmented coding has trimmed development timelines by up to 50% (PR Newswire – OutSystems & KPMG). The playing field for building software is flatter than ever.
This democratization means a great product alone doesn’t guarantee success, and investors have raised the bar. Early 2025 seed funding was about $7.2 billion (14% down YoY) (Crunchbase News), indicating fewer startups getting funded. Meanwhile, 71% of U.S. VC deal value in Q1 2025 went into AI-related companies (SiliconANGLE) – showing that investors are chasing a narrow set of “hot” tech bets. Paradoxically, when everyone can execute, execution alone stops being a moat. As one analysis noted, “while building is easier, defending what you’ve built has become exponentially more challenging” (Insignia Business Review).
The AI REST API Moment and the Rise of MCP
One of the clearest signals that execution barriers are falling even further is what many now call the “AI REST API moment.” The analogy is apt: just as REST APIs in the 2000s standardized and accelerated web development, new AI protocols like Anthropic’s Model Context Protocol (MCP) are dramatically lowering the effort required to integrate powerful AI into applications.
MCP is an open standard that enables secure, two-way communication between AI systems and external tools. It eliminates the need for custom-built integrations with data sources, APIs, or applications – meaning a startup can plug GPT-style models into product workflows with almost no bespoke engineering (Anthropic, Humanloop).
This marks a critical turning point:
Product integration is now modular and fast.
Time-to-value drops.
Execution becomes increasingly about orchestration, not invention.
The consequence is profound: even teams with minimal backend engineering expertise can launch deeply integrated AI workflows. It’s a collapse in complexity – and a key driver behind the broader democratization of entrepreneurial execution. What was once the domain of elite engineering teams is becoming accessible to almost anyone with a market insight and a model to build with.
What Sets Companies Apart Now?
When execution is cheap and abundant, moats must come from somewhere else. That means returning to fundamentals – advantages that are far harder to clone or automate.
The Imperative Moats:
Strategic Judgment: Knowing what not to build. In an age of infinite tools and options, clarity on focus and sequencing is a defining skill. This can’t be outsourced or automated.
Deep Market Understanding: Particularly in B2B, founders who understand customer psychology, procurement behavior, and systems integration reality win more often than those with just technical speed.
Proprietary Data Utilization: As AI-native apps commoditize, the quality and uniqueness of the data loop – not the model – becomes the defensible moat. Data advantage compounds.
The Novel Moats:
Community Building: B2B startups are increasingly building network gravity by embedding themselves in communities. These user collectives increase switching costs and expand feedback loops.
Narrative & Category Design: Founders who shape the frame win the game. Category-defining companies aren’t just built; they’re declared – and storytelling is the lever.
Human-AI Interface Mastery: The edge is not just in using AI, but in designing superior interactions between humans and intelligent systems. Trust, usability, and context-awareness are the new frontier.
In the end, as software eats itself, what remains is not the code — it’s the craft.
The next iconic companies won’t just be well-built — they’ll be well-understood, well-positioned, and well-loved.
Execution is no longer a moat.
Understanding is.