# /get-headless — Full Content A publication and knowledge base about the headless economy. --- # Articles ## What It Means to Get Headless *The shift from human-interface-first software to a headless economy where agents discover, evaluate, access, pay for, and consume digital goods through machine-native interfaces.* *Published: 2026-04-14* > **to get:** > (1) Do something > (2) / get command Software engineering is going through its largest shift in the past decades with the arrival of agentic workflows. Tools like Claude Code now author up to XX% of requests to GitHub [TODO: add source], have caused a major market meltdown (the [SaaSpocalypse](https://www.thesaascfo.com/the-saaspocalypse-ai-agents-vibe-coding-and-the-changing-economics-of-saas/)), brought [Anthropic to hitting a $30B](https://www.theinformation.com/briefings/anthropic-says-topped-30-billion-annualized-revenue) run rate and made developers [rethink their jobs](https://x.com/big_duca/status/2008043013180686657). This explosion in agentic workflows is extending to other fields and leading an enormous change in **how software is being used and who uses it**. Nothing illustrates this shift more poignantly than Ramp's recent announcement to ship a CLI ([command line interface](https://en.wikipedia.org/wiki/Command-line_interface)) for users of their expense management software. All modern expense management software combines an intuitive user interface with a linked credit card. Card expenses show up as transactions in a web interface. You then upload receipts and match them to the corresponding transaction ([illustration of process here](https://www.youtube.com/watch?v=Gl8WiV4fI9c)), through drag and drop, confirming automatic matching or uploading receipts individually for each transaction. Perfecting this workflow process and pairing it to sophisticated features such as spend monitoring gave rise to several $B+ expense management vendors like Ramp, Brex or Expensify. A few weeks ago, Ramp shipped a custom CLI where **an agent would complete the entire workflow**. The agent figured out that a receipt was missing, found it on the user desktop and uploaded it. Ramp did the matching. A human directed this process through the Terminal but the GUI was bypassed entirely: [Ramp's agent-driven expense workflow (via @RampLabs)](https://x.com/RampLabs/status/2037253351583141910) > The user interface is no longer graphic — it's based on text, machine-readable data and natural language. **The target user is an agent.** Not a human. ## The headless economy *Beyond the GUI* Most businesses are not ready for agents becoming consumers of digital goods and services in their own right. The way agents make consumption choices will be very different from us and products they prefer look nothing like the ones most software businesses have been building. These new patterns of consumption will result in the rise of the **headless economy**. The headless economy is the emerging market in which agents discover, evaluate, access, pay for, and consume digital goods and services through machine-native interfaces.[^1] [Headless software](https://adchitects.co/blog/definition-of-headless-in-software) does not rely on a "head" or graphical user interface (GUI). It exposes API endpoints that allow the user to **access data**, manipulating it in whatever form they want to. Pre-agentic, the term was often used to describe "headless content management systems" — systems that allow you to surface content in a structured manner, such as this blog, but without supplying a GUI as a service. The shift we're talking about with the headless economy is not new. APIs have existed for decades and API-first businesses are not uncommon. What's changed now is the actor. For most of software history, the entity navigating, selecting, integrating and paying for a product was a human. And using it — we click, log in, drag, match, upload, filter, select. If there was an API, we would implement it in deterministic fashion to power other GUIs. **The GUI was the product.** Agents do not need a GUI. They need access to structured data. And in the headless economy, that will happen through APIs, [MCP servers](https://modelcontextprotocol.io/docs/getting-started/intro), [CLIs](https://aws.amazon.com/what-is/cli/). Headless implies that a **human-legible GUI is not the primary consumption layer**. When the primary consumer of a good changes, the product needs to catch up. The headless economy is specifically about how software gets consumed and who or what is doing the consuming — with the following implications: 1. The value of investing in human-centric interfaces will decrease, unless they marry human-native and machine-native 2. The value of businesses building infrastructure and abstracting away complexity from agents will increase Stripe still needs to build world-class financial infrastructure. YipitData still needs to create proprietary datasets. Ramp still needs to provide world-class receipt → transaction matching and issue credit cards. The value doesn't disappear. The interface to that value changes. And it will give rise to a completely new type of business, one that doesn't need to cater to humans at all. And others are noticing too: > "The biggest opportunity in agentic commerce (...) is building headless merchants. The next generation of merchants won't have storefronts. They'll have endpoints." > — [Noah Levine, a16z](https://a16zcrypto.com/posts/article/ai-agent-commerce-headless-merchant/) > "Agents don't read your ad. They query a registry, get structured results, and pick the best option in milliseconds. Your pricing page becomes a machine-readable header. Your sales funnel collapses into three HTTP calls: discover, authenticate, buy." > — [Simon Taylor, Fintech Brainfood](https://www.fintechbrainfood.com/p/the-intention-layer) ## Why now *What unlocked this* Agents became capable of completing complex, multi-step tasks — not just generating text. What made that possible was giving them access to tooling: APIs, CLIs, MCP servers, structured data feeds as well as the ability to chain these toolings together in tight reasoning loops. One implication is that once an agent can call a tool, it becomes a user of that tool. And users have needs — discovery, authentication, pricing, reliability, trust. This in turn unlocks a lot of new opportunities like providing pre-vetted and authenticated data to agents at cheap prices. When faced with a choice between researching and computing an answer by itself or purchasing that information from a vendor, given that agents are natural optimizers (that's how their training works!), they would be able to pick the most cost efficient choice. Simon Taylor puts it nicely in the following table in "[The Intention Layer](https://www.fintechbrainfood.com/p/the-intention-layer)": | | **Agent self-computes** | **Buys from a specialist** | | ------------- | ----------------------- | ----------------------------- | | **Cost** | $0.10 – 0.50 | $0.01 – 0.02 | | **Speed** | 10 – 25 seconds | < 200 milliseconds | | **Advantage** | — | 7-50x cheaper, 50-100x faster | ## The shape of what's coming Agents don't all consume in the same way. There are three distinct patterns, which we will cover in future posts: - **Agent-as-consumer:** The agent directly consumes the capability or output as part of its own workflow. - **Agent-as-intermediary:** The agent acquires a good or service on behalf of a human or organization, but is not the ultimate consumer of that good. - **Hybrid:** The agent consumes intermediate goods or capabilities in order to generate an output for a human or another system. The journey an agent takes from discovering a capability to repeatedly consuming it follows a (for today!) similar-ish funnel than the human customer journey you're used to thinking about: 1. Discover 2. Select 3. Access 4. Consume 5. Pay ## /get-headless *Why this blog* My first job was in taking terabytes of datasets on publicly traded companies and distilling them down into 5 bullet points. This enabled investors in said companies to make well-informed bets on their stock prices. The basics behind it — structuring, slicing, reducing, querying, vetting complex sets of data into single verifiable facts — will be what power the headless economy. **/get-headless** aims to be a knowledge hub for everything around this new market. I personally am extremely intrigued by the shapes of this market and all the opportunities it brings. Some key questions I want to answer: - What businesses are being built specifically for agent demand? - How do incumbents adapt existing products for machine-native consumption? - What is the infrastructure enabling it? APIs, CLIs, SDKs, MCP servers, agent protocols? - How is pricing and access models for machine consumers going to change? - How will discovery, selection, and distribution work when the customer is software? - How to think about trust, identity, and authorization in agentic systems And we're early. The businesses that will define this market are being built now, and most of them don't have a name yet. This is their home. [^1]: Some call these "machine" or "agent-to-agent (A2A)" markets. --- # Knowledge Base ## The Headless Economy *Definition and thesis of the headless economy — the emerging market where agents discover, evaluate, access, pay for, and consume digital goods and services through machine-native interfaces.* ## What is the headless economy? The headless economy is the emerging market in which agents discover, evaluate, access, pay for, and consume digital goods and services through machine-native interfaces. It is the shift from human-interface-first software and commerce toward machine-native products, services, and markets. In this economy, the primary path to usage does not run through screens, clicks, and dashboards. It runs through APIs, CLIs, SDKs, MCP servers, structured feeds, machine-readable documents, agent protocols, and other programmable surfaces. ## What does "headless" mean? Headless describes a product, service, or business whose primary operating surface is machine-native rather than human-interface-native. A headless product can be: - **Discovered** by software - **Evaluated** by software - **Accessed** by software - **Consumed** by software - **Monitored** by software - **Paid for or provisioned** by software Headless does not mean "no GUI" in an absolute sense. Headless means "the GUI is not the primary consumption layer." ## Core claims 1. A growing share of software usage will originate from agents rather than directly from humans. 2. Products designed for machine consumption will require different interfaces, economics, and distribution models than products designed primarily for human navigation. 3. New businesses will be built specifically for agent demand. 4. Existing GUI-first businesses will increasingly reconfigure themselves to work as headless businesses in parallel. 5. The most important market shifts will occur in discovery, selection, access, pricing, trust, retention, and interoperability. ## Central market question What kinds of products, businesses, and market structures emerge when agents become meaningful customers and consumers of digital goods and services? ## Taxonomy of Agent Consumption *Three models of how agents consume goods and services: as principal consumers, as procurement layers, and in hybrid consumption patterns.* ## How agents consume Not all agent consumption looks the same. There are three distinct patterns through which agents participate in the headless economy. ## 1. Agent as principal consumer The agent directly consumes the capability or output as part of its own workflow. **Examples:** - An agent calls an OCR API - An agent invokes a ranking model - An agent uses a CLI tool or MCP server - An agent reads structured documentation - An agent queries a proprietary dataset - An agent consumes a free or paid search endpoint This is the clearest and most direct form of headless consumption. ## 2. Agent as procurement layer The agent acquires a good or service on behalf of a human or organization, but is not the ultimate consumer of that good. **Examples:** - An agent purchases software seats for a company - An agent buys physical goods for a household - An agent handles delegated spending for a human principal This includes much of agentic commerce. It is part of the headless economy, but not its entire scope. ## 3. Hybrid consumption The agent consumes intermediate goods or capabilities in order to generate an output for a human or another system. **Examples:** - An agent accesses filings, articles, and data to produce a briefing - An agent combines free and paid tools to complete a research workflow - An agent consumes compute, models, and documents to produce a work product This is likely the most common real-world pattern. It connects direct machine consumption with human benefit. ## The Headless Customer Funnel *A framework for analyzing headless businesses through the machine-consumption funnel: discovery, selection, access, ongoing consumption, and LTV.* ## The machine-consumption funnel A useful framework for analyzing headless businesses is the machine-consumption funnel. Each stage describes how agent-driven usage differs from human-driven usage. ## Discovery How an agent becomes aware of a capability. - Registries - Search - Marketplaces - Embeddings - Recommendations - Protocol directories - Documentation hubs ## Selection How an agent determines whether a capability is fit for purpose. Decision variables may include: - Task fit - Price - Latency - Quality - Trust - Authorization requirements - Output format - Rate limits - Uptime - Policy constraints ## Access and purchase How the agent obtains the right to use the capability. - Open access - Token-based auth - Delegated auth - Enterprise provisioning - Subscription - Metered payment - On-demand settlement ## Ongoing consumption How repeated use happens over time. - Reliability - Quality consistency - Integration depth - Observability - Billing clarity - Memory and state retention - Ecosystem compatibility - Workflow dependence ## LTV in the age of agents For headless businesses, long-term value may be shaped by: - Repeated invocation - Incorporation into automated workflows - Low failure rates - Structured outputs - Strong documentation - Predictable billing - Accumulated context - Switching friction at the workflow level rather than the interface level ## Machine-Native Goods *The types of digital goods and services that agents consume in the headless economy, and the access models through which they are provisioned.* ## What agents consume The headless economy includes a wide range of goods consumed by software rather than navigated by humans. ### Capabilities and tools - APIs - CLI tools - SDKs - MCP-accessible capabilities - Workflow primitives ### Data and knowledge - Datasets - Search and retrieval endpoints - Content - Documents - Facts - Structured knowledge ### Infrastructure - Model inference - Ranking and classification services - Authentication and identity services - Memory and state services - Storage and hosting - Observability and monitoring - Compute ### Commerce - Payment and settlement rails ## Access models Machine-native goods may be accessed through: - **Free access** — no cost, no authentication - **Open source** — freely available code and tools - **Public web access** — publicly available data and content - **Freemium** — basic access free, premium features paid - **Quota-based usage** — limited free tier, paid beyond limits - **Subscription** — recurring payment for access - **Per-call pricing** — pay per API invocation - **Per-task pricing** — pay per completed task - **Per-result pricing** — pay per successful outcome - **Enterprise provisioning** — negotiated access and SLAs - **Internal/private deployment** — self-hosted or on-premise - **Sponsored or subsidized access** — third-party funded - **Protocol-mediated settlement** — programmatic payment rails ## Product Design for Agents *What products serving the headless economy require: machine-readable discovery, structured interfaces, strong error semantics, and more.* ## Designing for machine consumers Products serving the headless economy must be built with agent consumption as a primary use case, not an afterthought. The requirements differ fundamentally from human-centered product design. ## Requirements ### Discoverability - **Machine-readable discovery** — agents need to find capabilities through structured registries, documentation, and protocol directories, not marketing pages - **Clear capability descriptions** — what the product does, expressed in terms agents can parse and evaluate - **Structured documentation** — not just human-readable docs, but machine-parseable specifications ### Interface quality - **Stable interfaces** — breaking changes destroy automated workflows - **Predictable outputs** — agents need to parse responses reliably - **Strong error semantics** — clear, structured error messages that agents can act on programmatically - **Low latency** — agents operate at machine speed; human-acceptable response times may be too slow for agent workflows ### Access and control - **Low-friction authentication** — complex OAuth flows designed for humans create barriers for agents - **Explicit permissioning** — agents need clear, granular permission models - **Revocability** — the ability to revoke agent access cleanly ### Operations - **Observability** — visibility into how agents are using the product - **Usage transparency** — clear metering and reporting - **Policy compatibility** — alignment with organizational policies governing agent behavior - **Interoperability** — ability to work alongside other tools and systems in agent workflows ## Economics of the Headless Economy *How the headless economy changes software economics: from seat-based to invocation-based pricing, workflow-level switching costs, and machine-driven retention.* ## How software economics change The headless economy transforms several fundamental assumptions about how software businesses generate and capture value. ## Pricing shifts - **Seat-based to invocation-based** — when the user is an agent, per-seat pricing loses meaning; usage shifts to per-call, per-task, or per-result models - **Free access as infrastructure** — free tiers serve as discovery and adoption mechanisms in a world where agents evaluate and select tools programmatically - **Bundled and subsidized models** — some capabilities may be sponsored or subsidized to attract agent traffic and workflow integration ## Retention mechanics - **Workflow embedment over interface habit** — retention depends less on users returning to a familiar dashboard and more on the product being embedded in automated workflows - **Switching costs at the workflow level** — friction comes from reliability, accumulated context, integration depth, policy fit, and state — not from learning a new UI - **Machine-driven repeat consumption** — long-term value depends on repeated machine invocation rather than repeated human logins ## Value capture - Value may be captured per call, per task, per result, or per workflow - The unit of engagement becomes the API call or tool invocation, not the session or page view - Products that become embedded in high-frequency automated workflows capture compounding value - Products with strong structured outputs, predictable billing, and low failure rates build durable agent relationships ## Editorial position getheadless studies the headless economy from a market perspective. Our primary interests: - What is being built - Who is building it - Who is adapting to it - How agents consume it - How businesses monetize it - How distribution works - Where trust and control sit - Which categories are emerging - Which business models appear durable