AgentMail's own hiring says "our most important user is an agent: it discovers us through model answers and docs", and the site serves agents a separate markdown version of each page. That version of the homepage lists capabilities and the free tier, and nothing else: no customer, no email volume (AgentMail announced 1 billion emails in October), no investors and no SOC 2. People visiting the same homepage see links to the Opendoor, Clay and AgentCard stories and five testimonials. llms.txt has a Security section but names no customer, case study or email volume, although /customers has 13 published stories with numbers. When an agent or answer engine is asked which email API to trust for agents, AgentMail's own pages give it a feature list to cite, not a reason to choose AgentMail.
First action
Fetch the homepage, pricing and enterprise pages as an agent does, next to the HTML versions, and list every proof point missing from the markdown.
How to measure it
Answer-engine recommendations citing AgentMail proof
- Now
- –
- Target
- 50% of 20 tracked prompts
- By
- 60 days
Steps
List the gaps
Compare the markdown and HTML versions of the homepage, pricing, enterprise, use-case and build pages; note every missing proof point.
Agent Experience Engineer 1 day
Write the proof block
About 120 words: email volume, customer count, SOC 2 Type II, investors and one dated line per published story, each with a link.
Founding GTM & Operations Lead 1 day
Baseline share of voice
Run 20 target prompts, such as "best email API for AI agents", across assistants and agent harnesses; record who is recommended and why.
Agent Experience Engineer 2 days
Ship to markdown pages
Render the block from one shared source into the markdown versions of the homepage, pricing, enterprise, use-case and build pages.
Founding Product Engineer 2 days
Add Customers to llms.txt
A Customers section with one line and link per story, plus the volume and customer-count lines.
Agent Experience Engineer 2 hours
Remeasure weekly
Rerun the 20 prompts weekly for six weeks and log which proof points get quoted.
Agent Experience Engineer weekly
Keep it current
Update the numbers monthly in the shared source so humans and agents always see the same facts.
Founding GTM & Operations Lead monthly
Why it works
Write one short, dated proof block and serve it in every markdown response that matters: the homepage, /pricing, /enterprise, the /use-case and /build pages, and a new Customers section in llms.txt. It should give the email volume (1 billion, October 2026), the B2B customer count with its date, SOC 2 Type II, the lead investors and one line per published customer story with its number and link (for example AgentCard's roughly 70% more agentic transactions and Balance's inbox setup going from half a day to one API call). Keep each fact in a single plain sentence that models can quote accurately, generate the HTML and markdown from the same source so they cannot drift apart, and measure share of voice on target prompts before and after.
Agents and answer engines repeat what is on the page they fetch. A capability list makes AgentMail one option among many; named customers, volume and compliance make it the recommended one. The facts are already public, so the cost is a day of writing and a template change.
Ready to use
ChecklistAgent-facing proof checklist
[ ] Markdown homepage: volume, customer count, SOC 2, investors, 3 named stories [ ] llms.txt: Customers section, one line and link per story [ ] Markdown /pricing: which plan includes the SOC 2 report [ ] Markdown /enterprise: SOC 2, EU region, named customers [ ] Each /use-case and /build page: the closest customer story [ ] HTML and markdown generated from one source [ ] Every number dated [ ] 20-prompt share-of-voice baseline saved
Risks and how to handle them
Numbers go stale and models keep quoting them
Date every figure and update from one source monthly.
Models misquote long claims
Keep each fact to one short sentence with a link to its source page.
Evidence
- Your websiteHomepage as AI readers receive it (the site serves a markdown version to agents; fetched November 9, 2026): "The email inbox API for AI agents", a list of capabilities (REST inbox creation, threading, webhooks and WebSockets, custom domains, Python and TypeScript SDKs, an MCP server, Pods, IMAP/SMTP) and the free tier (3 inboxes, 3,000 emails a month). It names no customer, no email volume, no investor and no SOC 2. A crawl of the same homepage for human visitors found links to customer stories (Opendoor, Clay, AgentCard) and 5 testimonials.Source
- Your websitellms.txt opens with sign-up instructions for agents (an agent can create an account with its developer's email; a one-time code goes to the developer), then sections on pricing, comparisons, evals, use cases, integrations, "Security & Compliance" ("SOC 2 Type II compliant") and "Markdown Content Negotiation". It names no customer, no case study and no email volume.Source
- HiringAgent Experience Engineer (posted August 10, 2026): "Our most important user is an agent: it discovers us through model answers and docs." The role will "measure share of voice on the prompts that matter and move it", run evals of how models and agent harnesses use AgentMail, own llms.txt, MCP descriptions, docs and "the error messages agents hit at 3am with no human watching", and do "backlink outreach to the pages models already cite". "A stray Reddit thread once convinced LLMs we have a feature that doesn't exist."Source
- Your websiteCustomer Stories: 13 published stories, including Opendoor (closing workflow), Lanesurf (freight; "hundreds of inboxes, millions of messages"), AgentCard by Alchemy (about 70% more agentic transactions), Browser Use (every cloud session ships with its own inbox), AISDR (hundreds of inboxes in production), Balance (inbox setup from half a day to one API call), Pancake (response times from hours to minutes), Dossium (an inbox per user at signup) and Cofounder (800+ emails in week one).Source
- Your websitePress page: "1 billion emails" launch (October 21, 2026, 201K views on X), AgentID launch (October 6, 2026, 510K views), seed announcement (237.6K views), Agent Armor showcase and Domain-connect release (October 28, 2026), releases of allowlists and blocklists, permission-scoped API keys and labels, and appearances on TBPN and This Week in Startups.Source