Imagine waking up to find that overnight your AI assistant has closed a new customer deal by negotiating pricing with the client’s procurement bot, scheduled investor meetings via their calendar agents, and even optimized your cloud costs by chatting with AWS’s automated advisor. As a startup founder, this isn’t sci-fi — it’s the coming reality of businesses run on autonomous agents working for us 24/7. The age of agent-to-agent interaction is dawning, and it’s poised to transform how startups operate and create value. This post is a call to ambitious founders to get ahead of this shift and build the next generation of agent-driven companies.

From B2C to B2A to A2A: A Paradigm Shift

Business models are evolving in an agent-driven world. Here are two new business models we expect to emerge::

• B2A (Business-to-Agent): An emerging model where companies interface with AI agents that represent users. Example: Instead of a user navigating your app, their personal AI assistant contacts your service via an API or plugin (acting on the user’s behalf). Think of a traveler’s AI agent booking a flight by connecting to an airline’s system — your business must effectively “sell” to the user’s agent by providing easy integration and trust. Many companies are already enabling this with AI-friendly APIs (for instance, food delivery services offering chatbot/voice assistant ordering).
• A2A (Agent-to-Agent): The future model where AI agents autonomously negotiate and transact with each other on behalf of humans or organizations. Example: Your sales agent and a client’s purchasing agent hash out a contract and pricing, then schedule implementation automatically. In the pure A2A scenario, the agents handle the entire process end-to-end — from initial outreach to closing the deal — with minimal human input. We’re seeing early signs of this: in finance, algorithmic trading bots already trade stocks with one another in milliseconds, and pilot projects in supply chain are letting AI negotiators handle vendor contracts. This A2A economy will unlock efficiency and scale that’s impossible with direct human interaction alone.

For founders, these shifts mean new opportunities: building products and infrastructure that cater not just to human end-users, but to their digital representatives. Below, we highlight key opportunity areas in this agent-to-agent future — each an invitation to innovate and build a breakout startup.

Opportunities in an Agent-to-Agent World

1. Agent Builders & Orchestration Tools

Founders can create the “Shopify for AI agents.” There’s a growing need for platforms that let anyone design, customize, and deploy AI agents without deep AI expertise. The opportunity here is to build agent builder frameworks — think of low-code or configuration-driven tools to spin up an agent tailored to a specific task or industry. This matters because today, assembling an autonomous agent (with reasoning, tool usage, memory, etc.) often requires stitching together libraries and prompting hacks. A dedicated builder platform could streamline complex orchestration (managing an agent’s step-by-step planning and actions) and integrate pre-built skills. Why it’s valuable: Just as web builders unlocked a wave of online businesses, an agent builder platform lowers the barrier for founders and companies to create agentic applications. Imagine a sales manager easily configuring an AI SDR agent that automatically finds leads, sends personalized outreach, and books meetings. By empowering more businesses to leverage agents, the startup that provides the go-to builder toolkit can capture a wide market of users hungry for automation. Real-world example: Open-source projects like Auto-GPT sparked interest in agents that can act autonomously, but they’re geeky and unreliable. A polished, user-friendly agent-building SaaS could become the “Shopify of AI agents,” letting a founder assemble a marketing agent or a research agent in hours instead of months.

2. Memory & Context Extensions

Make agents smarter by helping them remember. Today’s AI agents have short memories — they often rely on an LLM’s limited context window or a few past interactions. There’s a huge opportunity for startups to build memory infrastructure for agents: long-term storage of knowledge, interactions, and preferences that an agent can access on the fly. This could be specialized vector databases, knowledge graphs, or memory management APIs optimized for AI reasoning. Why it matters: For agents to truly be effective collaborators, they need to learn and improve over time. With robust memory, an agent can recall a user’s goals, adapt to prior feedback, and avoid repeating mistakes. For example, a customer support agent that remembers a user’s previous issues can skip redundant questions and resolve problems faster, boosting user satisfaction. Or consider a personal health coach agent that tracks months of fitness and dietary data — it can give far more personalized and effective advice than one with no long-term memory. By providing the “brain” that outlives a single chat session, a memory-focused startup becomes an essential layer in the agent tech stack. 

3. Authentication, Identity & Trust

Every agent needs an “ID badge” and a handshake protocol. As agents start acting on our behalf — logging into our accounts, making purchases, or negotiating deals — authentication and identity become critical. Founders can build solutions that verify an agent’s identity and permissions in a way that businesses and other agents can trust. The opportunity: create the OAuth or Okta for AI agents, enabling secure delegation of authority. Why is this important? If your finance AI is going to send invoices or transfer funds, the recipient (or bank API) must know it’s legitimately representing you, not a rogue bot. Robust identity frameworks (which could be something like digital certificates, signatures, or blockchain-based IDs for agents) will prevent fraud and mistakes in an A2A world. They also allow humans to set limits — e.g. an agent can be authorized to spend up to $1,000 or access only certain data. Example: A startup could offer an “Agent ID Kit” that other businesses integrate: whenever an agent interacts with a service, a secure token vouches for who it represents and what it’s allowed to do. A real-world analogue is how today we use single sign-on to let third-party apps act for users; in the near future, your personal AI assistant might carry a digital credential that logs it into your email and negotiates with your travel agent, all with your encrypted approval. Founders who solve agent authentication will become the trust layer for countless agent-to-agent transactions.

4. Collaboration Protocols & Interoperability

Building the language for agents to talk to each other. In a fully agent-to-agent economy, no agent will operate in isolation. Sales agents will talk to procurement agents; personal assistants will coordinate with meeting scheduler bots; one agent might even hire another to perform a sub-task. This opens an opportunity for standardized protocols and platforms for agent communication. Founders can create the “network layer” that lets agents published by different companies seamlessly interact. Why this is a big deal: Right now, most AI agents communicate in ad-hoc ways (often via human-centric formats like emails or API calls). Establishing a common protocol (akin to SMTP for email or HTTP for web) would supercharge A2A interactions. For example, if every calendar agent adhered to a scheduling protocol, any two agents could negotiate meeting times instantly without dragging humans into email tag. Similarly, a marketplace or hub where agents can discover and query other agents’ services could ignite a new ecosystem. Emerging example: We’re already seeing early marketplaces where humans post tasks and AI agents bid to complete them. In one experiment, entrepreneurs created a “job board for AI” where an agent could accept a task (like analyzing a dataset) and deliver results for payment. Now imagine a more generalized agent exchange: a startup could provide the infrastructure where an e-commerce agent automatically searches multiple supplier agents for the best price or fastest delivery, then executes a transaction — all through a standardized agent-to-agent API. By solving interoperability, a founder can own the backbone of the agent economy, ensuring every agent can “talk” to any other or plug into any service. Ambitious but attainable: some industry voices predict the first agent communication protocols are around the corner, and a startup that defines the standard could become as crucial as the early internet protocols were to the web.

5. Agent Ecosystems & Marketplaces

Be the platform where agents thrive. As agents proliferate, users and businesses will need ways to deploy, manage, and discover them — similar to an app store or a marketplace, but for AI agents. This is a ripe area for founders to explore. One angle is building a marketplace for pre-trained agents or agent “skills.” Imagine a platform where companies can shop for an AI agent that specializes in, say, bookkeeping or SEO optimization, and easily integrate it into their workflow. Another angle is creating tools for agent management: dashboards to oversee what your fleet of agents is doing, analytics on their performance, and a repository of third-party plugins or data sources they can use. Why it’s promising: In the B2C app era, distribution channels (app stores, SaaS marketplaces) were kingmakers — they aggregated users and provided trust and discoverability. In the agent era, a company that provides a trusted marketplace can attract both developers (agent creators) and users (businesses or individuals deploying agents). This network effect can be incredibly powerful and defensible. Plausible near-future scenario: A small business owner visits an “Agent Marketplace” and finds a highly-rated Accounting Agent. With a few clicks, they give it access to their financial software, and it starts automatically reconciling transactions and preparing tax documents. That agent itself might come with add-ons from other developers — for example, a plugin for local tax regulations. All of this is mediated by the marketplace platform which ensures compatibility and security. Over time, such a platform could evolve into an ecosystem where agents not only are bought and sold, but also cooperate: the accounting agent could hire a specialized Tax Filing agent for a one-time task, paying through the marketplace’s currency or protocol. By founding the hub of agent activity, you’re positioning your startup at a vital junction of the A2A economy, much like the AppStore or Play Store.

6. Agent Outcome Monitoring & Pricing

This is one of the biggest untapped opportunities. Traditionally, tech products capture only 1–2% of company budgets through IT spending. Agents, however, can charge based on outcomes rather than licenses or seats, tapping into the full operating budget. If an agent can negotiate a deal, file taxes, or increase sales conversion rates, companies will happily pay a percentage of the upside. Founders can build the infrastructure for agents to track outcomes, measure performance, and invoice based on results. Startups in this space will create not just tools but new economic models that vastly expand addressable markets for AI.

Founders, lead the A2A revolution

The rise of AI agents represents a tectonic shift in how software will be built and businesses will operate. Just as the internet and mobile revolutions created multi-billion dollar opportunities for those who innovated early, the Agent-to-Agent era will produce its own giants. The difference this time is that change could come even faster — agents can work tirelessly and scale at the speed of software, so adoption can skyrocket once value is proven.

For forward-thinking founders, now is the time to stake a claim in this new frontier. Whether you build a critical piece of infrastructure (like the identity layer or a communication protocol) or an end-user application powered by swarms of agents, you’ll be riding one of the most important technology waves of our time. Keep the tone ambitious but grounded: focus on real problems agents can solve today, embed yourself in emerging agent communities, and iterate quickly as the tech matures. The examples above are just a starting point — a glimpse of near-future scenarios that savvy entrepreneurs can make real.

A call for founders: If you’re excited about the A2A future, start now. Assemble a prototype agent to tackle a pain point you know well. Experiment with letting it interact with other agents or services. Talk to potential users about how an autonomous agent could save them time or money. Every great startup begins with a vision of how the world could be, and the best founders then build that world step by step. The vision here is a world where agents handle the drudgery and complexity of business, freeing humans to be more creative and strategic. It’s a bold vision — and it’s within reach.

The future is agent-to-agent. If you’re building it, let’s talk.

About Us

Pioneer Square Labs (PSL) is a Seattle-based startup studio and venture capital fund. We partner with exceptional founders to build the next generation of world-changing companies, combining innovative ideas, expert guidance, and investment capital. PSL operates through two primary arms: PSL Studio, which focuses on creating new startups from scratch, and PSL Ventures, which invests in early-stage companies. Our mission is to drive innovation and growth by providing the necessary resources and support to turn big ideas into successful, impactful businesses. If you have a groundbreaking vision, connect with us hello@psl.com, and let’s build something extraordinary.