The following is a guest post and opinion from Bobby Shell, Board of Directors & VP of Marketing at Voltage.

AI is no longer just assisting humans—it’s making decisions, managing resources, and even spending money. But without instant, programmable payment rails, this new digital workforce is running on outdated infrastructure. Today’s AI systems are evolving into autonomous agents capable of handling complex workflows independently. These agents plan, interpret, decide, and execute operations, and increasingly are being trusted and empowered to make financial decisions too.

But for these AI systems to truly scale and thrive, they need access to digital money that is immediate, scalable, and secure: Bitcoin.

Here is why the correct infrastructure stack matters, how it is already taking shape, and why market leaders should act now to position their organizations for the future of money.

Legacy Networks Are Building. Is It Scalable?

Today’s financial infrastructure is built on closed systems: centralized platforms like Visa and Mastercard dominate payment processing, gatekeeping access to their tools and protocols. While Visa experiments with AI-powered payment orchestration and Mastercard develops dynamic transaction frameworks, these solutions are designed for incumbents, not innovators.

They’re siloed, slow to adapt, and exclude those who rely on decentralized assets like Bitcoin. These systems will never serve the edges of innovation—where creators, startups, and AI-native businesses are building the future—or those who measure value in Bitcoin’s sound money.

This is where open rails emerge as the disruptive alternative.

There are a few steps to an AI-ready payment stack:

• It begins with stablecoins, the predictable, permissionless currency for digital work, enabling global teams and AI agents to transact seamlessly, whether splitting revenue between algorithms or paying content creators across borders.
• Next comes Bitcoin’s Lightning Network, the backbone of this stack. Lightning operates beyond the constraints of Visa/Mastercard, offering instant settlements at near-zero cost. When an AI agent negotiates a contract or an autonomous drone orders replacement parts, it shouldn’t need a human to approve a transaction.
• Finally, open rails enable machines to pay machines: stablecoins become the “salary” for algorithmic work, while Lightning acts as the frictionless payroll system. This is not merely a technical upgrade—it’s the liberation of automation from human bottlenecking.

This stack redefines AI commerce: machines transact autonomously, humans collaborate seamlessly, and value flows instantly at scale—no banks, no friction.

AI Agents Are Becoming Financial Actors

Today’s AI models are capable of far more than just a year ago, with a growing prevalence in the workplace. They can execute project management tasks, file accounting records, order supplies, and even deploy code. These systems don’t just instruct; they can autonomously act.

Modern platforms like OpenAI’s GPT and LangChain frameworks make it possible to construct “agent loops” or workflows where the AI system autonomously interacts with external tools, APIs, and services. These agents often call external services, requiring payment for each action. For example, an AI writing assistant might fetch grammar checks from a third-party service, or a travel-planning bot might book a rental car.

AI operations demand automated, precise, and instant payments—yet traditional billing falters, plagued by manual delays, fee-heavy per-use models, upfront commitments, and non-programmable fiat rails reliant on intermediaries.

Stablecoins Are the Currency of Digital Work

In 2024, stablecoin volume exceeded $27.6 trillion, rivaling or surpassing major credit card networks.

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Stablecoins bypass cryptocurrency’s volatility, settle transactions instantly without delays, and enable seamless programmatic issuance, spending, and auditing—eliminating the need for manual reconciliation.

When AI is given access to capital, especially in the form of per-use, permissioned payments, it finds the best solution at the lowest cost in the shortest amount of time. This pay-per-action model reduces overhead and minimizes waste, giving open system AI agents a competitive advantage.
The result? Faster decisions, transparent spending, and measurable outcomes—exactly what businesses want from any operational layer.

Bitcoin: The Foundation Layer

Most stablecoins today run on platforms like Ethereum and Solana. But Bitcoin is still the most secure and widely trusted blockchain, and the Lightning Network is fulfilling its original promise as the “payments scaling layer.”

And what’s exciting is that there are already emerging use cases where AI agents utilize the Bitcoin Lightning Network for payments, primarily driven by the integration of AI with the Lightning Network’s L402 protocol and tools like LangChain, as pioneered by Lightning Labs.

Using the L402 protocol, an AI agent could query a specialized AI for market analysis data, paying a small fee in satoshis or stablecoins via Lightning. The L402 protocol authenticates and meters these payments, ensuring secure, instant transactions.

It can even be used to help with spam—a problem folks have been trying to solve since Adam Back’s Hashcash in 1997. A server hosting an AI model could theoretically issue an HTTP 402 “Payment Required” response, prompting the requesting AI to pay via Lightning to proceed.

These use cases are still nascent but show immense potential as AI and Bitcoin converge.
While Visa and Mastercard are building AI-powered payment networks, they remain closed, permissioned systems. By contrast, Lightning is live, open, and proven—used by some of the biggest names in the industry.

Obstacles to Overcome

The Lightning Network’s liquidity model, which requires pre-funding, could pose potential challenges to its adoption as the primary rails for AI-driven payments, particularly in high-volume, autonomous systems. If Lightning channels lack sufficient liquidity, payments exceeding a channel’s balance could fail or require complex routing through multiple nodes. Even small liquidity gaps could force payments to take convoluted routes across multiple nodes, increasing fees and latency.

For an AI agent to send payments autonomously, it must pre-fund Lightning channels with sufficient liquidity. This requires upfront capital (in BTC or stablecoins) and technical expertise to manage channels—a barrier for small-scale AI projects or those without dedicated DevOps teams. Without easy on-ramps or liquidity pools, adoption could stagnate.

This type of obstacle highlights the demand for companies to offer services that fill these gaps to ensure a smooth experience. Fortunately, the industry is full of passionate builders dead set on this very thing.

The Future Is Permissionless and Programmable

In the end, the rise of AI agents demands a new kind of financial infrastructure—one that is open, scalable, secure, and permissionless. In the AI-powered economy, speed, trust, and programmability will separate winners from laggards. Those who build on open, instant payment rails today won’t just participate in the future of money—they’ll define it.

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Similar dimensions don’t always translate to shared case usage

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Time and time again, we’ve seen many flagship phones that seem to share identical dimensions — particularly phones from Google and Samsung. However, just because two phones measure the same on paper, this does not mean that you can use phone cases designed for either model on the other device.

Smartphone manufacturers often make changes to the design of their phones, even if the size remains the same as the previous iteration. For example, the placement of the power button or volume button might change. In some instances, the speaker grills change positions. A change in the style and size of camera lenses or camera bars is also a common occurrence.

Sometimes, even when the stars seem to align, the slightest shifts in design can make a significant difference. This is the case with the Pixel 10 and Pixel 9.

As you can see from the table above, the on-paper measurements of the two Pixels are almost exactly the same. Going off of just the specs, you would think that the Google Pixel 10 can fit Pixel 9 cases. However, this is not the case.

Google changed the size of the camera island with the Pixel 10, so the shape and length don’t match the Pixel 9. The speaker, grills, mic, and USB-C port are also misaligned with the last-gen Pixel. Thus, even if you manage to fit a soft Pixel 9 case on your Pixel 10, you’ll end up covering the speaker and getting a poor fit. Hard Pixel 9 cases won’t fit the Pixel 10 at all.

Even if you manage to fit a flexible silicone or TPU case designed for the Pixel 9 on your Pixel 10, it isn’t a good idea to do so. Since the case is designed to add protection to the Pixel 9, it will not provide the same level of impact absorption or drop-proofing to your Pixel 10. It’s simply not worth the risk. Please buy a new Google Pixel 10 case instead. There are plenty of excellent options in varying price ranges.