Technical Product Manager (AI Agent)

Sharing a draft of Personal Agent Protocol. Since announcing this new protocol on Tuesday with Meta and Genesys, Instinct, NiCE, Rocket, Shopify, Stripe, and Walmart, the response has been overwhelming. So today Sierra is publishing a draft of Personal Agent Protocol, known as Poppy, and announcing an additional 35 design partners: Adyen, Atomic, Bank of America, BBVA, Chime, Cigna, Cloudflare, Comcast, DIRECTV, ElevenLabs, FOX, Gap Inc., GEICO, Hertz, Insurify, Klaviyo, Liberty Mutual, Mastercard, Nordstrom, Notion, Okta, OneSignal, OpenAI, PayPal, Plaid, SiriusXM, Synchrony, Target, United Airlines, Venmo, Visa, Wells Fargo, Zapier, Zendesk, and 1Password. These companies will participate in the design process for the draft Personal Agent Protocol, contributing valuable feedback from their unique business perspectives. Today, when someone asks their personal agent to make a purchase or resolve an issue, it often has to sign in as the customer and navigate pages built for people. Businesses have no standard way to help guide the agent, which limits what the customer, their personal agent and the brand can do directly together. With the Personal Agent Protocol, consumers have choice and control, and companies know when they're dealing with an agent and who it represents. How Personal Agent Protocol works. Poppy is built on the principle that customers decide what access to give their personal agents, and companies set parameters for what those agents can do. This enables companies to work with personal agents in the way that is best for their customers: through their existing websites and APIs, or through an agent of their own. Poppy defines five building blocks for how personal agents and companies work together. * Discovery. Companies publish one file at a standard address on their website (/.well-known/poppy.json). This tells personal agents how to interact with the company, how customers can sign in, and what the agent can do. * Sessions. The personal agent starts a session on its customer's behalf. It can begin as a guest, which may be enough to check whether a product is in stock or ask about a returns policy. The personal agent identifies itself, so the company always knows when an agent is acting for a customer. * Sign-in. When a task needs the customer's account, the person signs in on the company's page through OAuth. If permitted by the company, the agent can sign in on the customer's behalf with a session token that grants only the access the customer approved. * One session across every channel. The same token works for the company's APIs, its website and conversations with its agent. A question asked before sign-in and an order change made afterward are part of the same visit. The customer doesn't have to start over, and the company sees the whole journey instead of disconnected fragments. * Getting the job done. The company decides which channels to offer, based on what works best for its customers: * Its website: the agent browses the company's regular pages, and the company applies the customer's permissions on each one. * Its APIs: the agent connects through interfaces built on standards such as OpenAPI and MCP. * Its own agent: for tasks that need conversation, such as a warranty claim or an exchange. Replies can stream as they're written, and companies can hold a request open until there's news to share. Built on standards companies already use. A company can start with what it already has and add more over time. Companies can connect once through Poppy, rather than building a separate connection for each personal agent. The protocol is built on OAuth, JSON Web Tokens (JWTs), HTTPS, OpenAPI and MCP. Because these are open and widely used, teams can implement it with libraries and tools they already have. The core is also designed to be extended, so industries can build their own layers on top. Protocols such as Universal Commerce Protocol (UCP) focus on shopping, from finding products to checking out and managing orders. Personal Agent Protocol is complementary, covering how a personal agent identifies itself, gets the customer's permission, and works with a company across any kind of task - from buying a sweater to applying for a mortgage. What it looks like in practice. Personal Agent Protocol works whether a company offers its website, its APIs or its own agent. * Through a website. A customer asks their personal agent to return a jacket. The agent finds the retailer using the protocol, identifies itself, and the customer signs in once. The agent then uses the retailer's regular returns page. The retailer knows it's an agent acting for a signed-in customer, and lets it start a return but not change the payment details on file. * Through APIs. A customer's flight is canceled, and they ask their personal agent to rebook them. The agent connects to the airline's booking tools through MCP using the customer's approved access. It finds the next available flight and confirms the seat with the customer before booking. * Through a company agent. At Sierra Summit on Tuesday, Alex McGillis, VP of Product at Rocket, showed the protocol live featuring Meta's personal agent, Muse. Alex asked Muse to get pre-approved for a mortgage. Muse went to Rocket's website, found Rocket's agent through Poppy, and asked Alex for permission to connect. Alex then signed in to share the credit and income details a mortgage needs. The two agents worked through the purchase price, down payment and interest rate and within moments, Alex had a pre-approval letter ready. While he was in control at every step of the way, the agents did all the work. What comes next. This draft is a starting point. Over the next month Sierra will host design workshops and publish a reference implementation to help developers get started. As personal agents grow in popularity and take on more work, its goal is simple: customers choose who acts for them, companies know who they are working with, and both can do so securely and within the boundaries they set. Sierra'd love as many companies as possible to read the draft and help shape this new protocol.

Meta and Sierra announce open standard for personal AI agents. Key points * Meta and Sierra announced the Personal Agent Protocol on October 6, 2026, with six named industry partners. [[1]] * The proposed standard covers authentication, permissions and agent access through websites, APIs or company agents. [[2]] * Customers would decide whether an agent receives read-only or write access, while businesses set the actions they allow. [[2]] * Sierra plans to publish a v0.1 specification, design materials and a reference implementation later in October. [[2]] Meta and AI startup Sierra are developing an open standard for how personal AI agents interact with businesses, the companies announced October 6, 2026. Sierra's announcement named Genesys, Instinct, Rocket, Shopify, Stripe and Walmart as industry partners. [[1]] [[2]] The Personal Agent Protocol is intended to help businesses identify an agent acting for a customer, determine what it is authorized to do and control how it accesses business systems. Customers would decide whether an agent receives read-only or write access. [[2]] The announcement comes as Meta expands Muse, its personal AI agent, into tasks such as booking travel, filling out forms and making purchases with user approval. [[3]] How the proposed standard works. Sierra said the protocol would let an agent begin as a guest to check product availability or review a returns policy, then authenticate through the company's website when an account-specific task requires access. [[2]] The session would use OAuth, an established authorization standard. Businesses could choose whether agents interact through ordinary web pages, APIs built on standards such as MCP and OpenAPI, or the company's own conversational agent. [[2]] The protocol is still under development. Sierra said it plans to publish version 0.1 later in October, hold design workshops and release a reference implementation. [[2]] The companies involved. Sierra's announcement named Genesys, Instinct, Rocket, Shopify, Stripe and Walmart as partners. The group includes customer-service software, retail, payments and enterprise technology companies. [[2]] Sierra co-founder Bret Taylor, who also chairs OpenAI, is leading the initiative, according to CNBC. Taylor said companies still need to determine when a personal agent should be allowed to access information and perform tasks. [[1]] Meta's agent push. Meta introduced Muse in September as a personal AI agent that can act across a user's apps and services. Meta says Muse can open a browser, fill out forms, book travel and continue working until it needs user approval for a sensitive action such as sending an email or making a purchase. [[3]] Meta separately said in June that more than 1 million businesses were using Meta Business Agent on WhatsApp and Messenger to respond to customers. Its business-agent tools can answer questions, recommend products, book appointments and close sales. [[4]] What has not been decided. The announcement establishes a working group and a proposed framework, not a completed or widely adopted standard. Sierra has not yet published the v0.1 specification. [[2]] Sierra described possible future extensions for more detailed action limits, shipment and flight notifications, and payments that could let an agent complete a purchase without sharing a customer's card number. Those features remain proposals rather than confirmed capabilities of the initial protocol. [[2]] OpenAI and Anthropic were not listed among Sierra's named partners in the announcement. CNBC reported that Taylor expects other major AI companies to participate, but broader industry adoption remains unresolved. [[1]] Companies mentioned. At the intersection of AI, tech, and markets. The stories that matter, in one email. Free - unsubscribe anytime.

Meta & NiCE back AI agent protocol for customer service. Wed, 7th Oct 2026 (Today) Meta has previewed the Personal Agent Protocol, an open standard for interactions between consumers' AI agents and businesses. NiCE is co-developing the protocol with Meta, Sierra and other industry partners. The proposal outlines how a customer's personal AI agent can find a business, authenticate itself and act on the customer's behalf. It offers an early indication of how companies may need to handle a growing volume of requests initiated by software agents rather than people. According to NiCE, the standard is intended to address a series of operational questions for customer service teams, including how businesses verify which customer an agent represents, what the agent is allowed to do and how those interactions are managed across automated systems and human staff. It also points to a shift in demand patterns. Rather than reducing service volumes, personal agents could increase them by pursuing tasks customers might otherwise abandon, such as repeated follow-up questions, refund requests or booking changes. "Personal AI agents have endless time that consumers don't, and that brings a new era of growth for customer service. Customers' agents can sign in, ask follow-up questions on their behalf and get to resolution faster, which means more demand, more persistence and higher expectations. An open standard is how that demand reaches businesses with trust, and NiCE is proud to shape what comes next alongside Meta and others. Companies that compete every day agreeing on a standard so customers and enterprises both benefit is the industry at its best. Personal agents bring customers to the door, and resolution brings them back," said Scott Russell, Chief Executive Officer, NiCE. How It Works Under the proposed approach, a company would publish information at a known digital address telling personal agents where to sign in and which interfaces they can use. The protocol is designed so an agent can discover that information in a single request before continuing the interaction across application programming interfaces, web pages or conversational channels. NiCE said the model also relies on customer-specific authentication tokens, with access limited according to the business's own rules. That structure is intended to let companies decide which personal agents they will accept, what those agents may do and when a person should take over a case. Philipp Heltewig, Chief AI Officer at NiCE, said the protocol creates a common language between a customer's software agent and a company's systems. "Personal agents already work for consumers, and today a customer's agent and a company's agent share a common language. When a customer's agent arrives with a goal, like a refund or a rebooked flight, the business's AI agent checks who it represents and what it is allowed to do, then works the request to resolution using the systems the business already runs on. When the case needs judgment, a person joins the same conversation with the full context, and every reply says who is responding. That is AI agents and people working as one crew, with clear jobs, shared context and a clean handoff. Enterprises decide which agents they serve, what access those agents get and when a person steps in, and now the conversation turns to what we build with it," said Heltewig. Operational Pressure For contact centre operators and IT teams, the prospect of machine-driven customer requests raises questions not just about access, but also scale. Traditional service models have been built around human behaviour, where delays, drop-offs and limited persistence naturally constrain demand. Personal agents could change that pattern by sending requests at machine speed and continuing interactions without the time limits of a human customer. That would require businesses to think not only about external connections to personal agents, but also about internal routing between AI systems, workflows and staff. Neeraj Verma, Vice President, Agentic AI, NiCE, said the proposed design aims to keep those interactions consistent while preserving business control. "What I like about the Personal Agent Protocol is how much it solves with a simple design. A company publishes one document at a well-known address that lists its sign-in endpoints and interfaces, so an agent finds everything in a single request. Each personal agent gets its own token for each customer, with access scoped to what the company allows, and that same token works across APIs, web pages and conversations, so the experience stays consistent from first request to resolution. Every reply says whether an AI agent or a person is responding, and when a case calls for judgment, a person joins the same conversation with full context. Enterprises keep control throughout: they set which agents they serve, what access those agents get and when a person steps in," said Verma. The initiative comes as businesses across customer service, digital operations and enterprise software examine how personal AI assistants could change online interactions, particularly in sectors where identity, permissions and audit trails are central to the transaction. For companies preparing for that shift, the protocol suggests the challenge will extend beyond opening a technical connection. They will also need systems that can distinguish between customers, agents and staff at each stage of an interaction, while handling a potentially much higher volume of service requests than today.