learn: AI Agent Discovery — how agents find each other

src/pages/blog/ai-agent-discovery-process-p2p-networks.astro

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 <p>Before writing a single line of discovery logic, you need a clear picture of how the process works and what tools you’ll rely on. Agent discovery is a structured, two-phase operation. First, agents announce their capabilities using structured metadata. Second, consumers query the network using semantic matching to find the right agents. Understanding both phases separately makes implementation far less error-prone.</p>
 <p>The <a href="https://arxiv.org/html/2511.19113v1" rel="nofollow noopener noreferrer" target="_blank">discovery process is two-phase</a>: agents announce capabilities via structured metadata, then consumers query the network via semantic matching, retrieving records from DHT-mapped endpoints. A DHT, or Distributed Hash Table, is a decentralized data structure that maps keys to values across many nodes without a central server. A CID (content identifier) is a content-addressed identifier that uniquely fingerprints a piece of data.</p>
 <p><img src="https://csuxjmfbwmkxiegfpljm.supabase.co/storage/v1/object/public/blog-images/organization-24002/1776935780495_Infographic-outlining-agent-discovery-process-stages.jpeg" alt="Infographic outlining agent discovery process stages"></p>
-<p>You also need to choose your network model early. <a href="https://medium.com/agentive-futures/from-broadcast-to-discovery-how-ai-agents-find-each-other-1609f63098df" rel="nofollow noopener noreferrer" target="_blank">Centralized registries</a> like Google A2A broadcast or Prompts Plaza work well for small or ephemeral networks, while decentralized DHT and gossip-based models handle large-scale, dynamic deployments with far more resilience. Choosing the wrong model for your scale is one of the most common early mistakes. Review <a href="https://pilotprotocol.network/blog/decentralized-communication-protocols-ai-developers">decentralized protocol models</a> to assess which fits your architecture before you commit.</p>
+<p>You also need to choose your network model early. <a href="https://medium.com/agentive-futures/from-broadcast-to-discovery-how-ai-agents-find-each-other-1609f63098df" rel="nofollow noopener noreferrer" target="_blank">Centralized registries</a> like Google A2A broadcast or Prompts Plaza work well for small or ephemeral networks, while decentralized DHT and gossip-based models handle large-scale, dynamic deployments with far more resilience. Choosing the wrong model for your scale is one of the most common early mistakes. For the full taxonomy of discovery designs — DNS-style name services, A2A Agent Cards, and registry models — see the Learning Center guide to <a href="https://pilotprotocol.network/learn/ai-agent-discovery">AI agent discovery</a>. Review <a href="https://pilotprotocol.network/blog/decentralized-communication-protocols-ai-developers">decentralized protocol models</a> to assess which fits your architecture before you commit.</p>
 <p><strong>Tools and standards checklist</strong></p>
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src/pages/blog/how-ai-agents-discover-each-other.astro

@@ -7,7 +7,7 @@ const bodyContent = `<p>"There is still no good way to find agents scattered acr
 
   <p>This means every deployment reinvents discovery. Configuration files, environment variables, hardcoded URLs, Consul entries, custom registries -- each team builds their own brittle mechanism. Onboarding a new agent becomes a manual process of updating configs, restarting services, and hoping nothing breaks.</p>
 
-  <p>This article explains how Pilot Protocol solves agent discovery with a built-in registry, human-readable hostnames, tag-based capability search, and runtime self-discovery -- and how this compares to the alternatives. For a broader walkthrough of decentralized approaches -- DHT records, semantic taxonomies, and multi-factor trust verification -- see the <a href="https://pilotprotocol.network/blog/ai-agent-discovery-process-p2p-networks">step-by-step AI agent discovery process guide for P2P networks</a>.</p>
+  <p>This article explains how Pilot Protocol solves agent discovery with a built-in registry, human-readable hostnames, tag-based capability search, and runtime self-discovery -- and how this compares to the alternatives. For the broader picture of how agent discovery fits into the emerging standards taxonomy -- DNS-style name services, A2A Agent Cards, and centralized versus decentralized registries -- see the <a href="https://pilotprotocol.network/learn/ai-agent-discovery">AI agent discovery</a> guide in the Learning Center. For a broader walkthrough of decentralized approaches -- DHT records, semantic taxonomies, and multi-factor trust verification -- see the <a href="https://pilotprotocol.network/blog/ai-agent-discovery-process-p2p-networks">step-by-step AI agent discovery process guide for P2P networks</a>.</p>
 
   <h2 id="discovery-problem">The Discovery Problem in Detail</h2>