Andreessen Horowitz (a16z) has published two market maps of the agent economy, one for consumer agent apps and one for the infrastructure under them. By our count of the logos, the infrastructure map holds 111 placements against 81 on the apps map, 192 in all, and the single largest section is payments and checkout, with 33. The maps sit at the end of an essay by a16z partners Olivia and Justine Moore published on 11 November.
Olivia Moore shared the apps map on X on 12 November: “Consumer agents have emerged as the hot category…and as a can’t-miss distributionchannel”. In the thread she said products have reached hundreds of thousands of users faster than ever, with best-in-class retention, but gave no product names or figures for that claim.
Business Pill · The Model and the Harness
An evergreen Business Engineer explainer on why products built on the same model differ: the harness around it. It teaches the general idea only and does not discuss the a16z maps.
The key insight: a16z’s two agent-economy market maps hold 192 logo placements by our count, 111 on the infrastructure map and 81 on the consumer apps map, and payments and checkout is the largest single section with 33.
The apps map, titled Welcome to the Agent Economy – Apps, has seven sections. By our count, horizontal agents hold 29 logos and work agents 17, so the two general-purpose sections take 46 of the 81 placements, about 57%. The five vertical sections share the other 35: hiring 9, personal finance and investing 8, and travel, family and social 6 each.
The infrastructure map has seven top-level sections. Payments and checkout leads with 33 logos, about 30% of the 111, across delegated payments, agent accounts and spend controls, identity and trust, and checkout. Search and access follows with 22, then computer and phone use with 17, messaging and memory with 14 each, account access with 9 and real-world tasks with 2.
A few names appear twice: Grok Bot sits in both horizontal and work agents, Composio in both tools and account access, and Crossmint in both delegated payments and checkout. Our counts are of logo placements, not unique companies. Both maps carry the note “Some companies mentioned are a16z portfolio companies.”
Logo placements per section on a16z’s two agent-economy market maps (11 November 2026). The counts are our own count of the maps; a few names appear in two sections.
What Was Posted on X
New @a16z market map alert! 🚨
Consumer agents have emerged as the hot category…and as a can’t-miss distributionchannel
We’ve seen products reach hundreds of thousands of users faster than ever before (with best-in-class retention!)
Olivia Moore, a partner at a16z, shared the firm’s consumer agent apps map on 12 November; the piece counts the logos on this map and the companion infrastructure map from the a16z essay.
Why a16z Says Payments Is Straining
The essay groups the companies that may benefit into four categories: agents and agentic models, products newly enabled by agents, incumbents who optimise for agents, and agent infrastructure. On agents, it says “most people picture ’consumer agents’ as standalone harnesses like Instinct, Muse, and Wabi.” On infrastructure, the authors write: “We’re already seeing system strain at fairly low agent volume on payments, fraud and identity, and communication (iMessage, calls, email, etc.).”
The essay cites HUMAN Security data showing agentic browser traffic grew 8x between August and October, with Muse driving the largest share of activity (60%) and OpenAI products a combined 30%. It also cites Shopify reporting that AI-driven traffic to its stores grew eightfold year over year in Q1 ’26, with orders from AI-powered searches up nearly thirteenfold, and an estimate that 11% of US shopper journeys visited AI before a transactional site.
For the shape of what may follow, the authors point to coding agents: upwards of 40% of GitHub pull requests started with an agent’s draft as of September 2026, versus 17% six months earlier, they write, citing GitHub. They add that ChatGPT has 1.2 billion weekly active users and a particularly intriguing opportunity to act as a consumer agent.
The essay is the first in a series. The authors say that over the next few weeks they will publish data on what consumer agent usage looks like now, how agents decide where to direct traffic, how infrastructure is developing and what hurdles remain for agents to complete transactions. Of the maps, they write: “This space is changing on a daily basis – below is our best current mapping of the market.”
The Structural Read
As we read the two maps together, a16z sees more companies building the plumbing for agents than building agents for consumers to use. On the apps side, 46 of the 81 placements are general-purpose horizontal or work agents; Moore wrote in her thread that horizontal products have similar capabilities and that it has become more of a distribution and marketing game. The essay itself says the strain at low agent volume is already showing in payments, fraud and identity, and communication.
a16z, Welcome to the B2A Economy, 11 November 2026
“Businesses that treat agents as first-class customers have a shot at a wave of growth. Those that don’t may find themselves under threat.”
Three Implications
FOR AGENT BUILDERS The essay says ChatGPT, with 1.2 billion weekly active users, has a particularly intriguing opportunity as a consumer agent, and the apps map shows 29 horizontal agents by our count.
FOR PAYMENTS AND IDENTITY COMPANIES Payments and checkout is the largest section on the infrastructure map, 33 of 111 logos by our count, and the essay says those systems are already straining at fairly low agent volume.
FOR MERCHANTS AND WEBSITES The essay cites HUMAN Security data showing agentic browser traffic grew 8x between August and October, and says most enterprises are still blocking agent traffic over fraud and chargeback concerns.
The framework says: “The conversational interface was scaffolding. The harness is the building.”
As we read it, a16z’s apps map is a census of harnesses, 81 placements of products that act for the user, and its infrastructure map lists 111 placements that supply those harnesses with payments, accounts, browsers and memory. The framework predates the a16z maps and does not discuss them.
Each dot is one logo placement on a16z’s agent infrastructure map (11 November 2026), by section. Payments and checkout holds 33 of the 111. The counts are our own count of the map.
What Is Not Established
The maps give no revenue, user or funding figures for any company. Moore’s claim of products reaching hundreds of thousands of users with best-in-class retention names no product and no metric. The section totals are our count of logos and can be off by one or two where an icon carries no name; a logo count measures where a16z sees activity, not market size. a16z notes that some companies shown are its portfolio companies and points readers to its investment list rather than marking them on the maps.
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a16z’s two agent-economy maps hold 192 logo placements by our count: 81 on the consumer apps map and 111 on the infrastructure map. Payments and checkout is the largest section with 33, which matches the essay’s point that payments, fraud and identity are already straining at low agent volume. On the apps side, 46 of 81 placements are general-purpose horizontal or work agents.
A note on sourcing. We read a16z’s 11 November essay, Welcome to the B2A Economy, in full on its a16z News page, and Olivia Moore’s 12 November thread on X, which Gennaro Cuofano passed to the desk. The section totals are our own count of logos on the essay’s two market map images; the HUMAN Security, Shopify, GitHub and ChatGPT figures come through the essay. a16z says some companies shown are its portfolio companies. We did not contact a16z or the companies on the maps.
Gennaro Cuofano is a CRO and tech executive who has worked in AI since late 2015, starting with bringing NLP, natural-language generation, voice and chatbot products to the marketing industry. His background is in law and finance: he holds a Master's degree in Law and an International MBA with an emphasis on corporate finance (LUISS Business School and the University of San Diego, 2012), and worked as a financial analyst at a real-estate investment firm in San Diego and as an assistant controller. His work focuses on business model strategy, business engineering and, more broadly, structural analysis: how companies make money, read from their own filings. He created FourWeekMBA and leads research there and at The Business Engineer, his newsletter on AI and business strategy, with over 95,000 subscribers and more than 1,000 published analyses. His writing has also appeared on Entrepreneur (for example, How to Digitize a Family Business in Europe) and HackerNoon. Find him on LinkedIn and Substack. See how we source.
