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    <title>DEV Community: POTTUMUTHU UDAY</title>
    <description>The latest articles on DEV Community by POTTUMUTHU UDAY (@pottumuthuuday_a0ead).</description>
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      <title>DEV Community: POTTUMUTHU UDAY</title>
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    <item>
      <title>IncidentIQ: Teaching an AI Incident Response Agent to Remember What Broke Before</title>
      <dc:creator>POTTUMUTHU UDAY</dc:creator>
      <pubDate>Mon, 28 Sep 2026 18:05:19 +0000</pubDate>
      <link>https://dev.to/pottumuthuuday_a0ead/incidentiq-teaching-an-ai-incident-response-agent-to-remember-what-broke-before-dbl</link>
      <guid>https://dev.to/pottumuthuuday_a0ead/incidentiq-teaching-an-ai-incident-response-agent-to-remember-what-broke-before-dbl</guid>
      <description>&lt;p&gt;Most AI agents can analyze an incident. The harder problem is remembering what happened the last time something similar broke.&lt;/p&gt;

&lt;p&gt;I built IncidentIQ to explore that problem: an AI incident response agent that uses Hindsight as long-term memory. Instead of treating every outage as a completely new investigation, IncidentIQ can recall previous incidents, their root causes, resolutions, runbooks, and outcomes.&lt;/p&gt;

&lt;p&gt;The goal is simple:&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Detect → Analyze → Recall → Recommend → Resolve → Learn&lt;/strong&gt;&lt;/p&gt;

&lt;h2&gt;
  
  
  The Problem With Starting Every Incident From Zero
&lt;/h2&gt;

&lt;p&gt;Consider an authentication service that suddenly starts returning failures because its Redis connection pool is exhausted.&lt;/p&gt;

&lt;p&gt;A conventional AI assistant can analyze the current logs and explain that the connection pool may be saturated. But it does not automatically know that the same organization previously experienced a nearly identical incident, what fixed it, or which attempted fixes failed.&lt;/p&gt;

&lt;p&gt;That historical context can be more valuable than another generic explanation of Redis.&lt;/p&gt;

&lt;p&gt;IncidentIQ treats previous incidents as operational experience.&lt;/p&gt;

&lt;h2&gt;
  
  
  How IncidentIQ Works
&lt;/h2&gt;

&lt;p&gt;IncidentIQ uses a Next.js frontend together with a FastAPI analysis backend.&lt;/p&gt;

&lt;p&gt;The frontend handles the incident investigation workflow and communicates with the backend through server-side calls. Hindsight provides the long-term memory layer, while the analysis service uses the current incident together with recalled memories.&lt;/p&gt;

&lt;p&gt;The workflow is:&lt;/p&gt;

&lt;ol&gt;
&lt;li&gt;An incident is created or selected.&lt;/li&gt;
&lt;li&gt;IncidentIQ extracts important incident signals.&lt;/li&gt;
&lt;li&gt;Hindsight recalls relevant historical incidents.&lt;/li&gt;
&lt;li&gt;The analysis service combines current evidence with those memories.&lt;/li&gt;
&lt;li&gt;IncidentIQ generates a root-cause hypothesis and resolution recommendation.&lt;/li&gt;
&lt;li&gt;The engineer reviews the recommendation and creates a post-mortem.&lt;/li&gt;
&lt;li&gt;The resolved knowledge is retained in Hindsight.&lt;/li&gt;
&lt;li&gt;A future incident can recall that knowledge.&lt;/li&gt;
&lt;/ol&gt;

&lt;p&gt;This makes memory part of the investigation rather than a separate search screen.&lt;/p&gt;

&lt;h2&gt;
  
  
  Hindsight Is the Important Part
&lt;/h2&gt;

&lt;p&gt;The Hindsight integration is deliberately placed inside the investigation workflow.&lt;/p&gt;

&lt;p&gt;For a new incident, IncidentIQ sends information such as the service, severity, error message, description, and incident context to the recall layer.&lt;/p&gt;

&lt;p&gt;The application receives historical memories containing information such as:&lt;/p&gt;

&lt;ul&gt;
&lt;li&gt;Incident ID&lt;/li&gt;
&lt;li&gt;Service&lt;/li&gt;
&lt;li&gt;Severity&lt;/li&gt;
&lt;li&gt;Root cause&lt;/li&gt;
&lt;li&gt;Resolution&lt;/li&gt;
&lt;li&gt;Runbook information&lt;/li&gt;
&lt;li&gt;Outcome&lt;/li&gt;
&lt;li&gt;Relevance&lt;/li&gt;
&lt;li&gt;Historical context&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;The investigation interface presents these memories alongside the current incident.&lt;/p&gt;

&lt;p&gt;A simplified version of the recall workflow looks like this:&lt;/p&gt;



&lt;div class="highlight js-code-highlight"&gt;
&lt;pre class="highlight plaintext"&gt;&lt;code&gt;
typescript
postJson("/api/hindsight/recall", incidentInput)
  .then((data) =&amp;gt; {
    if (data.state === "ok" &amp;amp;&amp;amp; data.results) {
      setRecall({
        phase: "ok",
        results: data.results
      });
    }
  });
&lt;/code&gt;&lt;/pre&gt;

&lt;/div&gt;

</description>
      <category>ai</category>
      <category>aiprogramming</category>
      <category>aiagents</category>
      <category>devops</category>
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