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    <title>topic The anatomy of an agent matters more than you think. in SAS Customer Intelligence</title>
    <link>https://communities.sas.com/t5/SAS-Customer-Intelligence/The-anatomy-of-an-agent-matters-more-than-you-think/m-p/986916#M2119</link>
    <description>&lt;P&gt;&lt;FONT size="6" color="#3366FF"&gt;&lt;STRONG&gt;&lt;SPAN data-contrast="none"&gt;The anatomy of an agent matters more than you think.&lt;/SPAN&gt;&lt;/STRONG&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559739&amp;quot;:0,&amp;quot;335559740&amp;quot;:276}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/FONT&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Agent.png" style="width: 795px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/114512iCB2EC2E75903EC8C/image-dimensions/795x398?v=v2" width="795" height="398" role="button" title="Agent.png" alt="Agent.png" /&gt;&lt;/span&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-contrast="none"&gt;Every agent is made of two components: a model and a harness. Knowing how they differ, and why that matters, is the key to evaluating whether an agent is truly reliable&amp;nbsp;or just impressive in a demo.&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-contrast="none"&gt;The model is&amp;nbsp;the&amp;nbsp;reasoning engine. When we think of AI, this is often what we picture.&amp;nbsp;It's&amp;nbsp;the part that interprets your goal, evaluates the situation, and decides what to do next.&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-contrast="none"&gt;Models&amp;nbsp;are becoming increasingly commoditized;&amp;nbsp;the vast majority of&amp;nbsp;agents that are being built today are powered by the same handful of frontier models. These days, the model is&amp;nbsp;tables&amp;nbsp;stakes.&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-contrast="none"&gt;If the model is the brain of the agent, the harness is everything else: the nervous system, the skeletal and muscular systems, and the cardiovascular system, all at once.&amp;nbsp;It's&amp;nbsp;the execution layer that connects the model to your world — your data, your tools, your workflows,&amp;nbsp;and your&amp;nbsp;constraints.&amp;nbsp;&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;134233117&amp;quot;:true,&amp;quot;134233118&amp;quot;:true,&amp;quot;201341983&amp;quot;:0,&amp;quot;335559739&amp;quot;:0,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-contrast="none"&gt;The harness&amp;nbsp;determines&amp;nbsp;what the agent can access, what sequence it follows, how it recovers when something goes wrong, and what&amp;nbsp;it's&amp;nbsp;not allowed to do.&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-contrast="auto"&gt;It's&amp;nbsp;the middle layer — between the intelligence of the model and the complexity of the enterprise — where the real work gets done.&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;134233117&amp;quot;:true,&amp;quot;134233118&amp;quot;:true,&amp;quot;201341983&amp;quot;:0,&amp;quot;335559739&amp;quot;:0,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Image1_Acentic.png" style="width: 476px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/114513iBCC8B147050F79D1/image-dimensions/476x422?v=v2" width="476" height="422" role="button" title="Image1_Acentic.png" alt="Image1_Acentic.png" /&gt;&lt;/span&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-contrast="none"&gt;When choosing an agent, most of what&amp;nbsp;you’ll&amp;nbsp;evaluate&amp;nbsp;is&amp;nbsp;the harness,&amp;nbsp;not the model. How does the agent connect to your data? Does it work where your data already lives, without forcing a migration? What happens when the agent encounters ambiguity - does it guess, or does it ask? What are the boundaries of its autonomy, and who defined them? How transparent is it about what it did and why?&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Agentic2.png" style="width: 397px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/114514i8B4CE429BE097C1B/image-dimensions/397x260?v=v2" width="397" height="260" role="button" title="Agentic2.png" alt="Agentic2.png" /&gt;&lt;/span&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-contrast="none"&gt;These are hard questions. Asking&amp;nbsp;these&amp;nbsp;is how&amp;nbsp;you’ll&amp;nbsp;recognize a powerful agent built for your business&amp;nbsp;and how&amp;nbsp;you’ll&amp;nbsp;spot the ones that&amp;nbsp;won’t&amp;nbsp;hold up past&amp;nbsp;a&amp;nbsp;demo.&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;STRONG&gt;&lt;FONT color="#3366FF"&gt;We have a few convictions that guide our harness design:&amp;nbsp;&amp;nbsp;&lt;/FONT&gt;&lt;/STRONG&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;UL&gt;
&lt;LI data-aria-level="1" data-aria-posinset="1" data-list-defn-props="{&amp;quot;335552541&amp;quot;:1,&amp;quot;335559685&amp;quot;:720,&amp;quot;335559991&amp;quot;:360,&amp;quot;469769226&amp;quot;:&amp;quot;Symbol&amp;quot;,&amp;quot;469769242&amp;quot;:[8226],&amp;quot;469777803&amp;quot;:&amp;quot;left&amp;quot;,&amp;quot;469777804&amp;quot;:&amp;quot;-&amp;quot;,&amp;quot;469777815&amp;quot;:&amp;quot;hybridMultilevel&amp;quot;}" data-listid="1" data-font="Symbol" data-leveltext="-" aria-setsize="-1"&gt;&lt;SPAN data-contrast="auto"&gt;Agents should be transparent about their actions, obedient to your constraints, and honest about their limits.&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559739&amp;quot;:0,&amp;quot;335559740&amp;quot;:278}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;UL&gt;
&lt;LI data-aria-level="1" data-aria-posinset="2" data-list-defn-props="{&amp;quot;335552541&amp;quot;:1,&amp;quot;335559685&amp;quot;:720,&amp;quot;335559991&amp;quot;:360,&amp;quot;469769226&amp;quot;:&amp;quot;Symbol&amp;quot;,&amp;quot;469769242&amp;quot;:[8226],&amp;quot;469777803&amp;quot;:&amp;quot;left&amp;quot;,&amp;quot;469777804&amp;quot;:&amp;quot;-&amp;quot;,&amp;quot;469777815&amp;quot;:&amp;quot;hybridMultilevel&amp;quot;}" data-listid="1" data-font="Symbol" data-leveltext="-" aria-setsize="-1"&gt;&lt;SPAN data-contrast="auto"&gt;Agents should escalate when stakes exceed their authority.&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559739&amp;quot;:0,&amp;quot;335559740&amp;quot;:278}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;UL&gt;
&lt;LI data-aria-level="1" data-aria-posinset="3" data-list-defn-props="{&amp;quot;335552541&amp;quot;:1,&amp;quot;335559685&amp;quot;:720,&amp;quot;335559991&amp;quot;:360,&amp;quot;469769226&amp;quot;:&amp;quot;Symbol&amp;quot;,&amp;quot;469769242&amp;quot;:[8226],&amp;quot;469777803&amp;quot;:&amp;quot;left&amp;quot;,&amp;quot;469777804&amp;quot;:&amp;quot;-&amp;quot;,&amp;quot;469777815&amp;quot;:&amp;quot;hybridMultilevel&amp;quot;}" data-listid="1" data-font="Symbol" data-leveltext="-" aria-setsize="-1"&gt;&lt;SPAN data-contrast="auto"&gt;Agents should&amp;nbsp;fit to&amp;nbsp;your data infrastructure, not force you to rebuild it.&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559739&amp;quot;:0,&amp;quot;335559740&amp;quot;:278}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;UL&gt;
&lt;LI data-aria-level="1" data-aria-posinset="4" data-list-defn-props="{&amp;quot;335552541&amp;quot;:1,&amp;quot;335559685&amp;quot;:720,&amp;quot;335559991&amp;quot;:360,&amp;quot;469769226&amp;quot;:&amp;quot;Symbol&amp;quot;,&amp;quot;469769242&amp;quot;:[8226],&amp;quot;469777803&amp;quot;:&amp;quot;left&amp;quot;,&amp;quot;469777804&amp;quot;:&amp;quot;-&amp;quot;,&amp;quot;469777815&amp;quot;:&amp;quot;hybridMultilevel&amp;quot;}" data-listid="1" data-font="Symbol" data-leveltext="-" aria-setsize="-1"&gt;&lt;SPAN data-contrast="auto"&gt;Agents should get better as you use them - not because the model improved, but because the harness&amp;nbsp;learned&amp;nbsp;your context.&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559739&amp;quot;:0,&amp;quot;335559740&amp;quot;:278}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-contrast="none"&gt;Our approach is centered on trust. The harness is where trust lives:&amp;nbsp;it’s&amp;nbsp;where guardrails stand strong and where the division of labor is enforced.&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-contrast="none"&gt;A&amp;nbsp;well-designed harness keeps the agent focused on execution, orchestration, optimization, and efficiency. This&amp;nbsp;reserves&amp;nbsp;the decisions that require judgement, taste, or brand preference for&amp;nbsp;its users.&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-contrast="none"&gt;A&amp;nbsp;poorly designed harness either&amp;nbsp;over-automates&amp;nbsp;(making consequential decisions without asking for your input)&amp;nbsp;or under-automates&amp;nbsp;(requiring so much hand-holding that you end up wondering why you even need an agent).&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-contrast="none"&gt;This is what&amp;nbsp;responsible&amp;nbsp;agent design looks like in practice. A truly trustworthy, reliable agent is not just a powerful model behind a chat interface;&amp;nbsp;it’s&amp;nbsp;a system that was designed to know where it&amp;nbsp;ends&amp;nbsp;and you begin.&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;A href="https://communities.sas.com/t5/SAS-Customer-Intelligence/Agents-here-we-come-The-Agentic-Era-of-Marketing/m-p/986380#M2117" target="_self"&gt;&lt;SPAN data-contrast="auto"&gt;Learn&amp;nbsp;more about Customer Intelligence’s approach to Agentic AI&lt;/SPAN&gt;&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559739&amp;quot;:0,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;</description>
    <pubDate>Tue, 28 Apr 2026 17:30:29 GMT</pubDate>
    <dc:creator>Jennifer_SAS</dc:creator>
    <dc:date>2026-04-28T17:30:29Z</dc:date>
    <item>
      <title>The anatomy of an agent matters more than you think.</title>
      <link>https://communities.sas.com/t5/SAS-Customer-Intelligence/The-anatomy-of-an-agent-matters-more-than-you-think/m-p/986916#M2119</link>
      <description>&lt;P&gt;&lt;FONT size="6" color="#3366FF"&gt;&lt;STRONG&gt;&lt;SPAN data-contrast="none"&gt;The anatomy of an agent matters more than you think.&lt;/SPAN&gt;&lt;/STRONG&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559739&amp;quot;:0,&amp;quot;335559740&amp;quot;:276}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/FONT&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Agent.png" style="width: 795px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/114512iCB2EC2E75903EC8C/image-dimensions/795x398?v=v2" width="795" height="398" role="button" title="Agent.png" alt="Agent.png" /&gt;&lt;/span&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-contrast="none"&gt;Every agent is made of two components: a model and a harness. Knowing how they differ, and why that matters, is the key to evaluating whether an agent is truly reliable&amp;nbsp;or just impressive in a demo.&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-contrast="none"&gt;The model is&amp;nbsp;the&amp;nbsp;reasoning engine. When we think of AI, this is often what we picture.&amp;nbsp;It's&amp;nbsp;the part that interprets your goal, evaluates the situation, and decides what to do next.&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-contrast="none"&gt;Models&amp;nbsp;are becoming increasingly commoditized;&amp;nbsp;the vast majority of&amp;nbsp;agents that are being built today are powered by the same handful of frontier models. These days, the model is&amp;nbsp;tables&amp;nbsp;stakes.&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-contrast="none"&gt;If the model is the brain of the agent, the harness is everything else: the nervous system, the skeletal and muscular systems, and the cardiovascular system, all at once.&amp;nbsp;It's&amp;nbsp;the execution layer that connects the model to your world — your data, your tools, your workflows,&amp;nbsp;and your&amp;nbsp;constraints.&amp;nbsp;&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;134233117&amp;quot;:true,&amp;quot;134233118&amp;quot;:true,&amp;quot;201341983&amp;quot;:0,&amp;quot;335559739&amp;quot;:0,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-contrast="none"&gt;The harness&amp;nbsp;determines&amp;nbsp;what the agent can access, what sequence it follows, how it recovers when something goes wrong, and what&amp;nbsp;it's&amp;nbsp;not allowed to do.&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-contrast="auto"&gt;It's&amp;nbsp;the middle layer — between the intelligence of the model and the complexity of the enterprise — where the real work gets done.&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;134233117&amp;quot;:true,&amp;quot;134233118&amp;quot;:true,&amp;quot;201341983&amp;quot;:0,&amp;quot;335559739&amp;quot;:0,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Image1_Acentic.png" style="width: 476px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/114513iBCC8B147050F79D1/image-dimensions/476x422?v=v2" width="476" height="422" role="button" title="Image1_Acentic.png" alt="Image1_Acentic.png" /&gt;&lt;/span&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-contrast="none"&gt;When choosing an agent, most of what&amp;nbsp;you’ll&amp;nbsp;evaluate&amp;nbsp;is&amp;nbsp;the harness,&amp;nbsp;not the model. How does the agent connect to your data? Does it work where your data already lives, without forcing a migration? What happens when the agent encounters ambiguity - does it guess, or does it ask? What are the boundaries of its autonomy, and who defined them? How transparent is it about what it did and why?&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Agentic2.png" style="width: 397px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/114514i8B4CE429BE097C1B/image-dimensions/397x260?v=v2" width="397" height="260" role="button" title="Agentic2.png" alt="Agentic2.png" /&gt;&lt;/span&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-contrast="none"&gt;These are hard questions. Asking&amp;nbsp;these&amp;nbsp;is how&amp;nbsp;you’ll&amp;nbsp;recognize a powerful agent built for your business&amp;nbsp;and how&amp;nbsp;you’ll&amp;nbsp;spot the ones that&amp;nbsp;won’t&amp;nbsp;hold up past&amp;nbsp;a&amp;nbsp;demo.&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;STRONG&gt;&lt;FONT color="#3366FF"&gt;We have a few convictions that guide our harness design:&amp;nbsp;&amp;nbsp;&lt;/FONT&gt;&lt;/STRONG&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;UL&gt;
&lt;LI data-aria-level="1" data-aria-posinset="1" data-list-defn-props="{&amp;quot;335552541&amp;quot;:1,&amp;quot;335559685&amp;quot;:720,&amp;quot;335559991&amp;quot;:360,&amp;quot;469769226&amp;quot;:&amp;quot;Symbol&amp;quot;,&amp;quot;469769242&amp;quot;:[8226],&amp;quot;469777803&amp;quot;:&amp;quot;left&amp;quot;,&amp;quot;469777804&amp;quot;:&amp;quot;-&amp;quot;,&amp;quot;469777815&amp;quot;:&amp;quot;hybridMultilevel&amp;quot;}" data-listid="1" data-font="Symbol" data-leveltext="-" aria-setsize="-1"&gt;&lt;SPAN data-contrast="auto"&gt;Agents should be transparent about their actions, obedient to your constraints, and honest about their limits.&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559739&amp;quot;:0,&amp;quot;335559740&amp;quot;:278}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;UL&gt;
&lt;LI data-aria-level="1" data-aria-posinset="2" data-list-defn-props="{&amp;quot;335552541&amp;quot;:1,&amp;quot;335559685&amp;quot;:720,&amp;quot;335559991&amp;quot;:360,&amp;quot;469769226&amp;quot;:&amp;quot;Symbol&amp;quot;,&amp;quot;469769242&amp;quot;:[8226],&amp;quot;469777803&amp;quot;:&amp;quot;left&amp;quot;,&amp;quot;469777804&amp;quot;:&amp;quot;-&amp;quot;,&amp;quot;469777815&amp;quot;:&amp;quot;hybridMultilevel&amp;quot;}" data-listid="1" data-font="Symbol" data-leveltext="-" aria-setsize="-1"&gt;&lt;SPAN data-contrast="auto"&gt;Agents should escalate when stakes exceed their authority.&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559739&amp;quot;:0,&amp;quot;335559740&amp;quot;:278}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;UL&gt;
&lt;LI data-aria-level="1" data-aria-posinset="3" data-list-defn-props="{&amp;quot;335552541&amp;quot;:1,&amp;quot;335559685&amp;quot;:720,&amp;quot;335559991&amp;quot;:360,&amp;quot;469769226&amp;quot;:&amp;quot;Symbol&amp;quot;,&amp;quot;469769242&amp;quot;:[8226],&amp;quot;469777803&amp;quot;:&amp;quot;left&amp;quot;,&amp;quot;469777804&amp;quot;:&amp;quot;-&amp;quot;,&amp;quot;469777815&amp;quot;:&amp;quot;hybridMultilevel&amp;quot;}" data-listid="1" data-font="Symbol" data-leveltext="-" aria-setsize="-1"&gt;&lt;SPAN data-contrast="auto"&gt;Agents should&amp;nbsp;fit to&amp;nbsp;your data infrastructure, not force you to rebuild it.&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559739&amp;quot;:0,&amp;quot;335559740&amp;quot;:278}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;UL&gt;
&lt;LI data-aria-level="1" data-aria-posinset="4" data-list-defn-props="{&amp;quot;335552541&amp;quot;:1,&amp;quot;335559685&amp;quot;:720,&amp;quot;335559991&amp;quot;:360,&amp;quot;469769226&amp;quot;:&amp;quot;Symbol&amp;quot;,&amp;quot;469769242&amp;quot;:[8226],&amp;quot;469777803&amp;quot;:&amp;quot;left&amp;quot;,&amp;quot;469777804&amp;quot;:&amp;quot;-&amp;quot;,&amp;quot;469777815&amp;quot;:&amp;quot;hybridMultilevel&amp;quot;}" data-listid="1" data-font="Symbol" data-leveltext="-" aria-setsize="-1"&gt;&lt;SPAN data-contrast="auto"&gt;Agents should get better as you use them - not because the model improved, but because the harness&amp;nbsp;learned&amp;nbsp;your context.&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559739&amp;quot;:0,&amp;quot;335559740&amp;quot;:278}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-contrast="none"&gt;Our approach is centered on trust. The harness is where trust lives:&amp;nbsp;it’s&amp;nbsp;where guardrails stand strong and where the division of labor is enforced.&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-contrast="none"&gt;A&amp;nbsp;well-designed harness keeps the agent focused on execution, orchestration, optimization, and efficiency. This&amp;nbsp;reserves&amp;nbsp;the decisions that require judgement, taste, or brand preference for&amp;nbsp;its users.&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-contrast="none"&gt;A&amp;nbsp;poorly designed harness either&amp;nbsp;over-automates&amp;nbsp;(making consequential decisions without asking for your input)&amp;nbsp;or under-automates&amp;nbsp;(requiring so much hand-holding that you end up wondering why you even need an agent).&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-contrast="none"&gt;This is what&amp;nbsp;responsible&amp;nbsp;agent design looks like in practice. A truly trustworthy, reliable agent is not just a powerful model behind a chat interface;&amp;nbsp;it’s&amp;nbsp;a system that was designed to know where it&amp;nbsp;ends&amp;nbsp;and you begin.&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559738&amp;quot;:240,&amp;quot;335559739&amp;quot;:240,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;A href="https://communities.sas.com/t5/SAS-Customer-Intelligence/Agents-here-we-come-The-Agentic-Era-of-Marketing/m-p/986380#M2117" target="_self"&gt;&lt;SPAN data-contrast="auto"&gt;Learn&amp;nbsp;more about Customer Intelligence’s approach to Agentic AI&lt;/SPAN&gt;&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN data-ccp-props="{&amp;quot;201341983&amp;quot;:0,&amp;quot;335559739&amp;quot;:0,&amp;quot;335559740&amp;quot;:240}"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;</description>
      <pubDate>Tue, 28 Apr 2026 17:30:29 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Customer-Intelligence/The-anatomy-of-an-agent-matters-more-than-you-think/m-p/986916#M2119</guid>
      <dc:creator>Jennifer_SAS</dc:creator>
      <dc:date>2026-04-28T17:30:29Z</dc:date>
    </item>
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