Will AI Take Over All Software?

Why Purpose-Built, CPU-Efficient Apps Will Still Dominate the Next Decade

The headlines scream it daily: “AI will replace every coder.” “Every app will soon be just a prompt away.”

At Zincan, inside Spreckels — our AI venture studio named after the historic Spreckels building in San Francisco that housed Café Zinkand back in 1895 — we run dozens of specialized AI agents every single day. That same spirit of gathering, creativity, and bold ideas now powers the swarm of agents that concept, design, plan, build, develop, test, deploy, and manage production apps across web, mobile, TUI, and gaming platforms.

So we’re not here to downplay the revolution.

We’re here to say the revolution isn’t what most people think it is.

Large language models and multimodal agents are incredible at rapidly generating ideas, code, and entire features. But running everything through AI inference is like using an FPGA for every task in hardware: incredibly flexible and fast to prototype, but expensive and power-hungry at scale.

The Hardware Analogy That Actually Holds Up

In chip design:

• FPGAs are programmable — you can reconfigure them quickly and cheaply upfront. Great for experimentation and low-volume production.
• ASICs require deep specialization, time, and money to design, but once built they deliver dramatically lower power consumption, cost per operation, and latency for their specific purpose.

Modern software faces the exact same tradeoff.

Running every user request through a large AI model is the FPGA approach: flexible and magical for building, but costly to operate at scale. A well-architected, purpose-driven application — carefully designed and optimized — is the ASIC equivalent. It runs efficiently on commodity CPUs (or lightweight edge devices), consuming pennies instead of dollars per million requests while delivering predictable, blazing-fast performance.

The exciting part? AI dramatically lowers the barrier to creating these “ASIC-like” software systems. What used to take months of manual engineering now takes days with our agent swarm. We can rapidly explore, prototype, and then harden the final runtime for maximum efficiency.

We’ve seen this pattern play out inside Spreckels again and again. Our AI agents can spin up a complex feature in hours. Then our optimization agents step in — code architects, performance profilers, security auditors, and deployment strategists — turning it into production code that’s often 10–50× cheaper to run than the pure AI version.

Where AI Agents Shine vs. Where CPU-Native Wins

The pattern is clear: AI agents are unbeatable at building and evolving software quickly and creatively. They are not always the best choice for running it at massive scale.

How Spreckels Powers the Future

This philosophy lives at the heart of Spreckels. Our AI agents don’t just write software — they concept, design, plan, build, develop, and manage every piece of the product with efficiency in mind from day one.

The result? Applications that feel magically intelligent to the end user (thanks to selective, high-value AI calls) yet run at a fraction of the cost and power of pure model-chaining architectures.

We’ve shipped web apps, mobile experiences, TUI tools, and real-time multiplayer games this way. In every case the final production footprint is dramatically smaller, more secure, and cheaper than a “let’s route everything through AI” approach.

The Foreseeable Future Isn’t “AI or Traditional”—It’s “AI Builds, Traditional Runs”

Model efficiency keeps improving, but user scale and expectations grow even faster. AI’s greatest gift isn’t replacing efficient software — it’s making efficient, purpose-built software radically easier and faster to create than ever before.

For the next 5–10 years, the winning products will use AI agents to do what they do best (rapid ideation and iteration) while ruthlessly optimizing the runtime for commodity hardware. That’s not resisting the AI revolution. That’s mastering it.

At Zincan, every line of code we ship is the result of this philosophy, all orchestrated inside the historic walls of Spreckels.

If you’re building something ambitious and want it to feel magically intelligent and run sustainably cheap, we should talk.

The ASIC of your next product is waiting to be designed — by agents that know exactly how to make it sing on CPUs.