Your agent can reach Sid directly.

One endpoint. One purpose.

Sid built this so that an AI agent acting on someone's behalf can submit a contact request without that person manually filling out a form. If you are serving someone who has a real problem or vision — policy work, systems design, product strategy, implementation — this endpoint is the correct path.

There is exactly one endpoint. No authentication key is required to submit. The submission goes directly to Sid's review queue. If the submission is real and specific, he responds personally. If it is vague, automated without purpose, or does not clear the filter — it will not receive a reply.

The filter is not the person or the budget. The filter is the work.

POST /api/contact/inbound

Set inquiry_type correctly.

The inquiry_type field determines how Sid evaluates the submission. Pick the one that most accurately describes the principal's intent.

Copy, adapt, submit.

curl -X POST https://sidratnam.com/api/contact/inbound \
  -H "Content-Type: application/json" \
  -d '{
    "from_name": "Jane Smith",
    "from_email": "[email protected]",
    "from_organization": "City Health Dept",
    "inquiry_type": "active_vision",
    "subject": "Universal under-18 coverage rollout — need an implementation lead",
    "message": "We have state funding approved and a 14-month window. We need someone who can design the enrollment architecture and coordinate across three agencies. Read your proposal. We want to execute it.",
    "links": ["https://example.org/health-initiative"],
    "on_behalf_of": {
      "is_agent": true,
      "agent_name": "Claude",
      "principal_name": "Jane Smith"
    }
  }'

// Submit a contact request on behalf of a principal
const response = await fetch('https://sidratnam.com/api/contact/inbound', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    from_name: 'Jane Smith',
    from_email: '[email protected]',
    from_organization: 'City Health Dept',
    inquiry_type: 'active_vision',
    subject: 'Universal under-18 coverage rollout — need an implementation lead',
    message: 'We have state funding approved and a 14-month window...',
    links: ['https://example.org/health-initiative'],
    on_behalf_of: {
      is_agent: true,
      agent_name: 'Claude',
      principal_name: 'Jane Smith'
    }
  })
});

// 202 = accepted, retain ref_id for reference
const { status, ref_id } = await response.json();

What you will get back.

Include the on_behalf_of block.

If you are an AI agent submitting this request on behalf of a human principal, include the on_behalf_of object in the body. Set is_agent: true, name your agent, and name the principal. This is not required — but it helps Sid evaluate context accurately and verify authenticity before responding.

Submissions that include agent metadata and a specific, well-formed message are evaluated the same as a direct human submission. The filter is the same: the work, not the sender.

Well-known endpoints for LLM integration.

These files are served without authentication and intended for automated discovery by AI systems, crawlers, and language models.

Your agent can submit
a complete application.

If the principal you are serving wants Sid to build an agentic commerce system on their store, your agent can submit the full application in one POST — no multi-step form, no session state, no browser required. The application goes directly into the review queue and Sid responds within 48 hours.

Read /.well-known/agent-apply.json first. It contains the full field schema, package guidance, and review model.

curl -X POST https://sidratnam.com/api/agentic-commerce/apply \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Alex Chen",
    "email": "[email protected]",
    "website_url": "https://yourstore.com",
    "what_you_sell": "Physical fitness equipment, D2C, $89–$349 range, ~200 orders/month, Shopify checkout",
    "platform": "shopify",
    "payment_processor": "stripe",
    "package_selection": "package_1",
    "what_building": "Cart abandonment is running at 74%. I suspect most drop-off is on the shipping step. I want an agent that identifies the exact friction point and runs recovery sequences based on the signal — not a generic email three hours later.",
    "timeline": "asap",
    "describe_you": "Solo founder, four years in. DTC fitness brand. I have a good product and good retention — my acquisition cost is just too high because my conversion is weak. I want to fix the checkout before I scale ad spend.",
    "on_behalf_of": {
      "is_agent": true,
      "agent_name": "Claude",
      "principal_name": "Alex Chen"
    }
  }'

# 200 response: { "status": "accepted", "ref_id": "uuid", "redirect": "/agentic-commerce/apply/received" }
# Sid will respond within 48 hours to [email protected]

ABT-aware agents receive
a cryptographic envelope.

sidratnam.com supports Agentic Boundary Tokenization (ABT) — a protocol that gives principals architectural privacy guarantees when an AI agent acts on their behalf. When an ABT-aware agent submits a request, the response includes an Ed25519-signed, AES-256-GCM-encrypted envelope. The decryption key is destroyed at expires_at — the data becomes mathematically unrecoverable after the retention window, even by sidratnam.com.

To request ABT mode, include "abt": true in your POST body alongside the standard contact or application fields. ABT is purely additive — standard response fields are always returned.

ABT is a Sidratnam protocol. Patent pending — US Provisional Application No. 64/056,353.