AI Eats the World: 4 Strategic Truths We Can’t Ignore

This week at Super AI Singapore 2025, Benedict Evans—a 20-year veteran tech strategist and A16Z alumnus—took the stage to present "AI Eats the World."

For two decades, Evans has been the industry’s "sanity anchor," translating platform shifts (PCs, the Web, Mobile) into economic reality. He isn’t selling a product; he’s selling perspective.

His presentation was a massive download—90 slides of macro-analysis—but it boils down to one question that every CTO, investor, and founder is asking right now: Is this a bubble, or is this the moment software economics break forever?

I’ve analyzed the talk and synthesized it with the current state of the market. Here are the four deep strategic takeaways that need to be on your radar this week.

1. The "Magic" is Evaporating (And That’s Good)

Evans points out a historical pattern: "Once it works, we stop calling it AI."

We used to call databases and search "AI." Now they are just infrastructure. Today, LLMs wear the "AI" label. But as we cross from miracle to inevitable utility, the novelty is wearing off.

We are seeing visual reasoning solved (Nano Banana Pro), semantic search for video (Meta SAM 3), and massive scaling improvements (Gemini 3). The question is no longer "Will this work?" It is "Where does the margin end up?"

The Leader’s Takeaway: Stop treating AI as a tunable R&D experiment. It is inevitable infrastructure. If you don't treat it with the same seriousness as you treat the internet or electricity, you aren't just missing a trend—you're becoming obsolete.

2. Adoption is Path-Dependent (Don't Get Trapped)

There is a massive gap between "trying" AI and using it. Evans notes that while everyone has piloted AI, few use it in core workflows.

But here is the trap: Adoption is path-dependent.

If your first AI experiment is "Summarize this document," you are setting a low ceiling for your organization. You will get efficiency, but you won’t get leverage. However, if you drop AI into a complex junction of your business—like agent-assisted customer onboarding or engineering support—you change how information flows through the company.

The Leader’s Takeaway: Don't pick random sandboxes for Friday afternoon experiments. Pick "beachheads" that fundamentally alter information flow. Where you start determines what becomes possible later.

3. The Model is a Component, Not a Religion

Evans argues that models are looking more like commodity inputs. While I’d argue that the cutting edge (OpenAI, Google, Anthropic) is still defensible, for the enterprise buyer, this commoditization is a superpower.

We need to stop saying, "We are a [Insert Vendor] shop."

The Leader’s Takeaway: Design for leverage. Be multi-model from day one. Your long-term architecture should treat models as interchangeable components, routing workloads based on cost, latency, and data sensitivity. Do not settle for vendor lock-in.

4. AI Changes the Org Chart, Not Just the Tech Stack

This was the most profound implication of the week. When we moved to the Cloud, we didn't just move servers; we shifted power from IT to Product. Spreadsheets didn't just do math; they empowered Finance to control the narrative.

AI is doing the same to coordination.

By 2026, we should expect agents to act as an informal "Chief of Staff" for every knowledge worker—reading emails, triaging tickets, and proposing actions. This doesn't just increase productivity; it changes who needs an assistant, where decisions happen, and which middle-management coordination layers are no longer necessary.

The Leader’s Takeaway: You aren't just doing a software rollout; you are doing organizational design. Your hiring plans and management layers will need to adapt faster than in any previous cycle.

The Bottom Line: Step Back to Zoom In

It has been a breathless week in AI news. But frantic reaction is not strategy.

As Evans suggests, these technology waves follow predictable patterns even when the tech is novel. The winners won't be the ones who read the most news feeds; they will be the ones who understand that AI is a new form of alien intelligence (a la Andrej Karpathy) that requires us to build new mental models.

Take a walk. Get a whiteboard. Digest the shift. The "miracle" phase is over. The "utility" phase has begun.

Time to build.

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