{"id":11676,"date":"2026-06-09T15:00:13","date_gmt":"2026-06-09T14:00:13","guid":{"rendered":"https:\/\/rewirenow.com\/?p=11676"},"modified":"2026-06-09T20:44:39","modified_gmt":"2026-06-09T19:44:39","slug":"enterprise-ai-are-you-sure-you-need-ai-agents","status":"publish","type":"post","link":"https:\/\/rewirenow.com\/en\/resources\/blog\/enterprise-ai-are-you-sure-you-need-ai-agents\/","title":{"rendered":"Enterprise AI: are you sure you need AI agents?"},"content":{"rendered":"\n\n<div class=\"at-spacer at-spacer--6a28714e9117a\" style=\"background-color: transparent\">\n<style>\n\/* Ultrawide *\/\n.at-spacer--6a28714e9117a {\n    height: 80px;\n}\n\n\/* Desktop *\/\n@media (max-width: 1920px) {\n    .at-spacer--6a28714e9117a {\n        height: 80px;\n    }\n}\n\n\/* Laptop *\/\n@media (max-width: 1024px) {\n    .at-spacer--6a28714e9117a {\n        height: 60px;\n    }\n}\n\n\/* Mobile *\/\n@media (max-width: 767px) {\n    .at-spacer--6a28714e9117a {\n        height: 40px;\n    }\n}\n<\/style>\n<\/div>\n\n\n<section class=\"container-block   \"  style=\"\" >\r\n        <div class=\"block  container  container--768  width-under--tablet width-under--laptop  wysiwyg\">\r\n        \n\n<p>The pressure to deploy is real, and so is the pattern of projects that stall or fail to reach production. Here are five things we&#8217;ve learned, across sectors and scales, about what makes implementing AI agents successful.<\/p>\n\n\n<section class=\"horizontal-rule-block  js-horizontal-rule-block block  remove-bottom-spacing\"  >\n    <div class=\"container\">\n        <hr class=\"wp-block-separator\"\/>\n                    <div>01 \u00b7 The first cut<\/div>\n            <\/div>\n<\/section>\n\n\n<p class=\"has-black-color has-text-color has-link-color wp-elements-557ef99f0ad4fe070eddd4404770a727\" style=\"font-size:25px\"><strong>Not everything that looks like an agent problem is one.<\/strong><\/p>\n\n\n\n<p>A significant share of what gets called an &#8220;agent project&#8221; is, at its core, a retrieval problem. The challenge is finding the right information and producing a coherent response. A well-designed RAG pipeline or carefully prompted LLM will solve that more reliably, more cheaply, and with far less operational complexity than an agent.<br>Agents earn their place when the system needs to decide what to do next and act on it: calling tools, triggering steps, changing state in the world. Reasoning alone doesn&#8217;t require an agent. Action does.<br>The distinction sounds obvious. In practice, it&#8217;s the difference between a well-scoped project and an over-engineered one. Before architecture, before tooling, ask what the system actually needs to do. If the answer is &#8220;find and generate&#8221;, adding an agent creates complexity without improving the output.<\/p>\n\n\n\n<p class=\"has-normal-font-size\" style=\"background-color: #0693e320;padding: 15px;border-radius: 0 4px 4px 0;border-left: 4px solid #0693e3\">The task is retrieval and synthesis? A RAG pipeline or prompted LLM will serve you more reliably. The task requires deciding <strong>what to do next<\/strong> and executing? That&#8217;s where agents justify their complexity.<\/p>\n\n\n\n<div style=\"background-color:#00000005;border-radius:4px;padding:10px 20px 20px 20px;font-family:system-ui,sans-serif;margin-bottom:40px;margin-top:40px\">\n  <p style=\"font-size:12px;letter-spacing:.1em;text-transform:uppercase;color:#555555;font-weight:500;margin-bottom:11px;margin-top:0\">Where the line is<\/p>\n\n  <!-- Top box -->\n  <div style=\"border-radius:4px;background-color:#cce6f8;padding:14px;text-align:center;margin-bottom:8px\">\n    <p style=\"font-size:13px;font-weight:500;color:#191919;margin:0\">Do you need to&#8230;<\/p>\n  <\/div>\n\n  <!-- Arrow down -->\n  <p style=\"text-align:center;font-size:18px;color:#555555;margin:8px 0;line-height:1\">&#8595;<\/p>\n\n  <!-- Two cards side by side -->\n  <table style=\"width:100%;border-collapse:separate\">\n    <tr style=\"vertical-align:top\">\n\n      <!-- Card 1: Find &amp; generate -->\n      <td style=\"width:50%;vertical-align:top\">\n        <div id=\"wl0\" style=\"border-radius:4px;border:1px solid #cccccc;cursor:pointer\">\n          <div style=\"padding:14px 14px 7px 14px\">\n            <p style=\"font-size:13px;font-weight:500;color:#191919;margin:0 0 4px 0;line-height:1.2\">Find &amp; generate<\/p>\n            <span id=\"wl0-chev\" style=\"text-align:right;font-size:12px;color:#555555\">&#9660; more<\/span>\n          <\/div>\n          <div id=\"wl0-detail\">\n            <div style=\"padding:10px 14px;min-height:90px\">\n              <p style=\"font-size:13px;color:#444444;font-weight:400;line-height:1.4;margin:0\">Your AI needs to retrieve and synthesize, find the right information or produce a coherent response.<\/p>\n            <\/div>\n            <div style=\"padding:0 14px;min-height:100px\">\n              <p style=\"font-size:12px;font-weight:600;color:#555555;margin:0 0 6px 0\">Examples<\/p>\n              <div>\n                <span style=\"font-size:12px;padding:2px 8px;border-radius:20px;font-weight:400;border:1px solid #cccccc;color:#555555;margin:0 3px 3px 0\">Q&amp;A<\/span>\n                <span style=\"font-size:12px;padding:2px 8px;border-radius:20px;font-weight:400;border:1px solid #cccccc;color:#555555;margin:0 3px 3px 0\">Summarisation<\/span>\n                <span style=\"font-size:12px;padding:2px 8px;border-radius:20px;font-weight:400;border:1px solid #cccccc;color:#555555;margin:0 3px 3px 0\">Document synthesis<\/span>\n                <span style=\"font-size:12px;padding:2px 8px;border-radius:20px;font-weight:400;border:1px solid #cccccc;color:#555555;margin:0 3px 3px 0\">Search<\/span>\n              <\/div>\n            <\/div>\n            <div style=\"padding:14px\">\n              <div style=\"border-radius:4px;background-color:#eeeeee;padding:10px;text-align:center;min-height:80px\">\n                <p style=\"font-size:13px;font-weight:600;color:#333333;margin:0 0 2px 0\">Use LLM and RAG.<\/p>\n                <p style=\"font-size:12px;font-weight:300;color:#555555;margin:0;line-height:1.2\">An agent adds complexity without improving the output.<\/p>\n              <\/div>\n            <\/div>\n          <\/div>\n        <\/div>\n      <\/td>\n\n      <!-- Card 2: Act on the world -->\n      <td style=\"width:50%;vertical-align:top\">\n        <div id=\"wl1\" style=\"border-radius:4px;border:1px solid #0693e340;background-color:#0693e308;cursor:pointer\">\n          <div style=\"padding:14px 14px 7px 14px\">\n            <p style=\"font-size:13px;font-weight:500;color:#191919;margin:0 0 4px 0;line-height:1.2\">Act on the world<\/p>\n            <span id=\"wl1-chev\" style=\"font-size:12px;color:#0693e3\">&#9660; more<\/span>\n          <\/div>\n          <div id=\"wl1-detail\">\n            <div style=\"padding:10px 14px;min-height:90px\">\n              <p style=\"font-size:13px;color:#444444;font-weight:400;line-height:1.4;margin:0\">Your AI needs to identify what to do next and execute: calling tools, triggering multi-step processes, changing state.<\/p>\n            <\/div>\n            <div style=\"padding:0 14px;min-height:100px\">\n              <p style=\"font-size:12px;font-weight:600;color:#0693e3;margin:0 0 6px 0\">Examples<\/p>\n              <div>\n                <span style=\"font-size:12px;padding:2px 8px;border-radius:20px;font-weight:400;border:1px solid #0693e340;color:#0693e3;margin:0 3px 3px 0\">Multi-step execution<\/span>\n                <span style=\"font-size:12px;padding:2px 8px;border-radius:20px;font-weight:400;border:1px solid #0693e340;color:#0693e3;margin:0 3px 3px 0\">Tool use<\/span>\n                <span style=\"font-size:12px;padding:2px 8px;border-radius:20px;font-weight:400;border:1px solid #0693e340;color:#0693e3;margin:0 3px 3px 0\">State changes<\/span>\n                <span style=\"font-size:12px;padding:2px 8px;border-radius:20px;font-weight:400;border:1px solid #0693e340;color:#0693e3;margin:0 3px 3px 0\">Real-world effects<\/span>\n              <\/div>\n            <\/div>\n            <div style=\"padding:14px\">\n              <div style=\"border-radius:4px;background-color:#cce6f8;padding:10px;text-align:center;min-height:80px\">\n                <p style=\"font-size:13px;font-weight:600;color:#0693e3;margin:0 0 2px 0\">Use agentic AI.<\/p>\n                <p style=\"font-size:12px;font-weight:400;color:#0693e3;margin:0;line-height:1.2\">An agent is the right solution.<\/p>\n              <\/div>\n            <\/div>\n          <\/div>\n        <\/div>\n      <\/td>\n\n    <\/tr>\n  <\/table>\n<\/div>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p><\/p>\n<\/blockquote>\n<\/blockquote>\n\n\n<section class=\"horizontal-rule-block  js-horizontal-rule-block block  remove-bottom-spacing  remove-top-spacing\"  >\n    <div class=\"container\">\n        <hr class=\"wp-block-separator\"\/>\n                    <div>02 \u00b7 The ceiling to be broken<\/div>\n            <\/div>\n<\/section>\n\n\n<p class=\"has-black-color has-text-color has-link-color wp-elements-feee23aed17870fefbfc09d515b38b15\" style=\"font-size:25px\"><strong>Workflow automation has a ceiling. You designed it.<\/strong><\/p>\n\n\n\n<p>When you automate a workflow, you codify how work currently gets done. Every step is designed by you, and the intelligence lives in that design. You can make it faster to go through every step of the process but won&#8217;t find smarter ways to reach the same outcome. In a workflow, the optimization ceiling is the process itself.<br>Agentic systems can break this ceiling by finding smarter ways to reach the goal you define. For well-defined tasks, that ceiling is a feature, not a flaw \u2014 workflows are predictable, consistent, and easier to audit. The ceiling only becomes a problem when the task genuinely can&#8217;t be reduced to a fixed path.<\/p>\n\n\n\n<div style=\"background-color:#00000005;border-radius:4px;padding:10px 20px 20px 20px;font-family:system-ui,sans-serif;margin-bottom:40px;margin-top:40px\">\n  <p style=\"font-size:11px;letter-spacing:.1em;text-transform:uppercase;color:#555555;font-weight:500;margin-bottom:11px;margin-top:0\">Fixed path vs flexible routes &#8212; the ceiling is different by design<\/p>\n\n  <table style=\"width:100%;border-collapse:collapse\">\n    <tr>\n      <!-- WORKFLOW BLOCK -->\n      <td style=\"width:50%;vertical-align:top;padding-right:8px;height:1px\">\n        <div style=\"border-radius:4px;border:1px solid #cccccc;padding:16px;height:100%\">\n          <p style=\"font-size:10px;letter-spacing:.08em;text-transform:uppercase;color:#555555;font-weight:500;margin:0 0 8px 0\">Workflow automation<\/p>\n          <div id=\"wf-canvas-wrap\" style=\"position:relative;height:320px\"><\/div>\n          <p style=\"font-size:13px;color:#666666;font-weight:300;margin:8px 0 0 0;line-height:1.4\">Cannot exceed the process you designed.<\/p>\n        <\/div>\n      <\/td>\n      <!-- AGENTIC BLOCK -->\n      <td style=\"width:50%;vertical-align:top;padding-left:8px;height:1px\">\n        <div style=\"border-radius:4px;border:1px solid #0693e340;background-color:#0693e308;padding:16px;height:100%\">\n          <p style=\"font-size:10px;letter-spacing:.08em;text-transform:uppercase;color:#0693e3;font-weight:500;margin:0 0 8px 0\">Agentic AI<\/p>\n          <div id=\"ag-canvas-wrap\" style=\"position:relative;height:320px\"><\/div>\n          <p style=\"font-size:13px;color:#0693e3;font-weight:300;margin:8px 0 0 0;line-height:1.4\">Discovers paths you didn&#8217;t design &#8212; ceiling is the goal.<\/p>\n        <\/div>\n      <\/td>\n    <\/tr>\n  <\/table>\n<\/div>\n\n\n\n<p class=\"has-normal-font-size\" style=\"background-color: #0693e320;padding: 15px;border-radius: 0 4px 4px 0;border-left: 4px solid #0693e3\">&#8220;When you give an agent a goal and guardrails, it decides the path. That freedom is where it finds cross-process synergies, uncovers patterns, and surfaces opportunities you wouldn&#8217;t have found by designing every step. The value of agents isn&#8217;t pure efficiency. It&#8217;s discovery.&#8221;<\/p>\n\n\n\n<p>Breaking that ceiling requires more than deploying an agent. It requires your organisation to be ready to act on what the agent finds \u2014 and willing to change how work gets done as a result.<\/p>\n\n\n\n\n<div class=\"at-spacer at-spacer--6a28714e92861\" style=\"background-color: transparent\">\n<style>\n\/* Ultrawide *\/\n.at-spacer--6a28714e92861 {\n    height: 30px;\n}\n\n\/* Desktop *\/\n@media (max-width: 1920px) {\n    .at-spacer--6a28714e92861 {\n        height: 30px;\n    }\n}\n\n\/* Laptop *\/\n@media (max-width: 1024px) {\n    .at-spacer--6a28714e92861 {\n        height: 30px;\n    }\n}\n\n\/* Mobile *\/\n@media (max-width: 767px) {\n    .at-spacer--6a28714e92861 {\n        height: 30px;\n    }\n}\n<\/style>\n<\/div>\n\n\n<section class=\"horizontal-rule-block  js-horizontal-rule-block block  remove-bottom-spacing  remove-top-spacing\"  >\n    <div class=\"container\">\n        <hr class=\"wp-block-separator\"\/>\n                    <div>03 \u00b7 The overlooked risk<\/div>\n            <\/div>\n<\/section>\n\n\n<p class=\"has-black-color has-text-color has-link-color wp-elements-f7b6c48ffdb004918ff92bc2cc2c63a5\" style=\"font-size:25px\"><strong>The risk isn&#8217;t that it fails. It&#8217;s that it succeeds in ways you&#8217;re not ready for.<\/strong><\/p>\n\n\n\n<p>The agent will find things no one asked it to look for \u2014 and that is the point. But most organisations are built to execute on known plans, not to act on unexpected discoveries.<br>A diagnostics agent might identify a new combination of signals that predicts a technical issue earlier and more accurately than the indicators engineers currently rely on. The insight is only useful if an engineer is willing to test it \u2014 and that requires a different mindset than monitoring a known dashboard. It means trusting an unfamiliar pattern, designing a validation approach, and being open to changing how diagnosis is done.<\/p>\n\n\n\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<p class=\"has-normal-font-size\" style=\"background-color: #0693e320;padding: 15px;border-radius: 0 4px 4px 0;border-left: 4px solid #0693e3\">Even if the agent succeeds, the organisation needs to be ready to incorporate the change it brings.<\/p>&nbsp;\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<div style=\"background-color:#00000005;border-radius:4px;padding:10px 20px 20px 20px;font-family:system-ui,sans-serif;margin-bottom:40px;margin-top:40px\">\n  <p style=\"font-size:12px;letter-spacing:.1em;text-transform:uppercase;color:#555555;font-weight:500;margin-bottom:11px;margin-top:0\">How ready is your organisation?<\/p>\n  <!-- Card 1 -->\n  <div id=\"rc0\" style=\"border-radius:4px;border:1px solid #cccccc;margin-bottom:6px;cursor:pointer\">\n    <div style=\"padding:14px\">\n      <table style=\"width:100%;border-collapse:collapse\">\n        <tr>\n          <td style=\"width:36px;vertical-align:top;padding-right:12px;padding-top:2px\">\n            <div id=\"rc0-ind\" style=\"width:32px;height:32px;border-radius:50%;border:1px solid #cccccc;text-align:center;line-height:1.9;font-size:16px;color:#cccccc\">&#10003;<\/div>\n          <\/td>\n          <td style=\"vertical-align:middle\">\n            <p style=\"font-size:14px;font-weight:500;color:#191919;margin:0;line-height:1.2\">We are willing to let agent outcomes reshape our processes, not just speed them up<\/p>\n          <\/td>\n          <td style=\"width:20px;text-align:right;vertical-align:middle\">\n            <span id=\"rc0-chev\" style=\"font-size:12px;color:#555555\">&#9660;<\/span>\n          <\/td>\n        <\/tr>\n      <\/table>\n    <\/div>\n    <div id=\"rc0-detail\" style=\"border-top:1px solid #eeeeee;padding:14px;padding-top:10px\">\n      <p style=\"font-size:13px;color:#444444;font-weight:400;line-height:1.4;margin:0\">This is the hardest condition to meet. It means being willing to act on what the agent discovers, even if it challenges how work is currently structured. <strong style=\"color:#191919;font-weight:500\">Organisations that deploy agents on processes they refuse to change get the worst of both worlds.<\/strong><\/p>\n    <\/div>\n  <\/div>\n  <!-- Card 2 -->\n  <div id=\"rc1\" style=\"border-radius:4px;border:1px solid #cccccc;margin-bottom:6px;cursor:pointer\">\n    <div style=\"padding:14px\">\n      <table style=\"width:100%;border-collapse:collapse\">\n        <tr>\n          <td style=\"width:36px;vertical-align:top;padding-right:12px;padding-top:2px\">\n            <div id=\"rc1-ind\" style=\"width:32px;height:32px;border-radius:50%;border:1px solid #cccccc;text-align:center;line-height:1.9;font-size:16px;color:#cccccc\">&#10003;<\/div>\n          <\/td>\n          <td style=\"vertical-align:middle\">\n            <p style=\"font-size:14px;font-weight:500;color:#191919;margin:0;line-height:1.2\">Leadership is open to outcomes that look different from what was planned<\/p>\n          <\/td>\n          <td style=\"width:20px;text-align:right;vertical-align:middle\">\n            <span id=\"rc1-chev\" style=\"font-size:12px;color:#555555\">&#9660;<\/span>\n          <\/td>\n        <\/tr>\n      <\/table>\n    <\/div>\n    <div id=\"rc1-detail\" style=\"border-top:1px solid #eeeeee;padding:14px;padding-top:10px\">\n      <p style=\"font-size:13px;color:#444444;font-weight:400;line-height:1.4;margin:0\">Agents will surface patterns and paths no one designed for. If leadership expects the output to match the original plan, those discoveries will be dismissed rather than acted on. <strong style=\"color:#191919;font-weight:500\">The agent succeeds, but the value disappears.<\/strong><\/p>\n    <\/div>\n  <\/div>\n  <!-- Card 3 -->\n  <div id=\"rc2\" style=\"border-radius:4px;border:1px solid #cccccc;margin-bottom:12px;cursor:pointer\">\n    <div style=\"padding:14px\">\n      <table style=\"width:100%;border-collapse:collapse\">\n        <tr>\n          <td style=\"width:36px;vertical-align:top;padding-right:12px;padding-top:2px\">\n            <div id=\"rc2-ind\" style=\"width:32px;height:32px;border-radius:50%;border:1px solid #cccccc;text-align:center;line-height:1.9;font-size:16px;color:#cccccc\">&#10003;<\/div>\n          <\/td>\n          <td style=\"vertical-align:middle\">\n            <p style=\"font-size:14px;font-weight:500;color:#191919;margin:0;line-height:1.2\">We have a mechanism to incorporate what the agent discovers back into how we work<\/p>\n          <\/td>\n          <td style=\"width:20px;text-align:right;vertical-align:middle\">\n            <span id=\"rc2-chev\" style=\"font-size:12px;color:#555555\">&#9660;<\/span>\n          <\/td>\n        <\/tr>\n      <\/table>\n    <\/div>\n    <div id=\"rc2-detail\" style=\"border-top:1px solid #eeeeee;padding:14px;padding-top:10px\">\n      <p style=\"font-size:13px;color:#444444;font-weight:400;line-height:1.4;margin:0\">Discovery without a feedback loop is wasted. The organisations getting compounding value from agents have a clear path from agent output to operational change. <strong style=\"color:#191919;font-weight:500\">This is what turns a deployment into a learning system.<\/strong><\/p>\n    <\/div>\n  <\/div>\n  <!-- Score bar -->\n  <div>\n    <div style=\"background-color:#999999;border-radius:20px;height:6px;width:100%;margin-bottom:8px;line-height:1.2\">\n      <div id=\"rs-bar\" style=\"background-color:#888888;border-radius:20px;height:6px;width:0%\"><\/div>\n    <\/div>\n    <span id=\"rs-label\" style=\"font-size:13px;color:#444444;font-weight:400;line-height:1.2\">Click each condition to assess your readiness<\/span>\n  <\/div>\n<\/div>\n<\/div><\/div>\n\n\n<div class=\"at-spacer at-spacer--6a28714e92d83\" style=\"background-color: transparent\">\n<style>\n\/* Ultrawide *\/\n.at-spacer--6a28714e92d83 {\n    height: 30px;\n}\n\n\/* Desktop *\/\n@media (max-width: 1920px) {\n    .at-spacer--6a28714e92d83 {\n        height: 30px;\n    }\n}\n\n\/* Laptop *\/\n@media (max-width: 1024px) {\n    .at-spacer--6a28714e92d83 {\n        height: 30px;\n    }\n}\n\n\/* Mobile *\/\n@media (max-width: 767px) {\n    .at-spacer--6a28714e92d83 {\n        height: 30px;\n    }\n}\n<\/style>\n<\/div>\n\n\n<section class=\"horizontal-rule-block  js-horizontal-rule-block block  remove-bottom-spacing  remove-top-spacing\"  >\n    <div class=\"container\">\n        <hr class=\"wp-block-separator\"\/>\n                    <div>04 \u00b7 The reusability advantage<\/div>\n            <\/div>\n<\/section>\n\n\n<p class=\"has-black-color has-text-color has-link-color wp-elements-664ab84d2171fdb083b8392c774e6b4e\" style=\"font-size:25px\"><strong>The real compounding value isn&#8217;t the agent. It&#8217;s the skill library<\/strong>.<\/p>\n\n\n\n<p>Most implementations focus on the agent itself. The more durable advantage is in what the agent can draw from. Rather than programming specific sequences, you build a library of discrete, reusable capabilities: search, summarise, calculate, classify, generate. The agent selects and combines them dynamically to reach its goal.<br>Skills built for one use case become reusable assets across the organisation. A search-and-retrieve capability built for a client briefing agent serves a risk screening agent and a proposal drafting agent. This is where the economics of agentic AI compound \u2014 making the skill layer the foundational investment to get right first.<\/p>\n\n\n\n<div style=\"background-color:#00000005;border-radius:4px;padding:10px 20px 20px 20px;font-family:system-ui,sans-serif;margin-bottom:40px;margin-top:40px\">\n  <p style=\"font-size:12px;letter-spacing:.1em;text-transform:uppercase;color:#555555;font-weight:500;margin-bottom:11px;margin-top:0\">One library, any number of agents<\/p>\n  <table style=\"width:100%;border-collapse:collapse\">\n    <tr>\n      <td style=\"width:140px;vertical-align:top\">\n        <p style=\"font-size:12px;text-transform:uppercase;letter-spacing:.08em;color:#555555;text-align:center;margin:0 0 6px 0;font-weight:500\">Skill library<\/p>\n        <div id=\"rwv3-sk0\" style=\"padding:7px 10px;border-radius:20px;font-size:13px;font-weight:400;text-align:center;cursor:pointer;color:#333333;border:1px solid #bbbbbb;margin-bottom:5px\">Search &amp; retrieve<\/div>\n        <div id=\"rwv3-sk1\" style=\"padding:7px 10px;border-radius:20px;font-size:13px;font-weight:400;text-align:center;cursor:pointer;color:#333333;border:1px solid #bbbbbb;margin-bottom:5px\">Summarise<\/div>\n        <div id=\"rwv3-sk2\" style=\"padding:7px 10px;border-radius:20px;font-size:13px;font-weight:400;text-align:center;cursor:pointer;color:#333333;border:1px solid #bbbbbb;margin-bottom:5px\">Calculate<\/div>\n        <div id=\"rwv3-sk3\" style=\"padding:7px 10px;border-radius:20px;font-size:13px;font-weight:400;text-align:center;cursor:pointer;color:#333333;border:1px solid #bbbbbb;margin-bottom:5px\">Classify<\/div>\n        <div id=\"rwv3-sk4\" style=\"padding:7px 10px;border-radius:20px;font-size:13px;font-weight:400;text-align:center;cursor:pointer;color:#333333;border:1px solid #bbbbbb\">Generate draft<\/div>\n      <\/td>\n      <td id=\"rwv3-svgwrap\" style=\"position:relative;min-height:180px;vertical-align:top\"><\/td>\n      <td style=\"width:140px;vertical-align:top\">\n        <p style=\"font-size:12px;text-transform:uppercase;letter-spacing:.08em;color:#0693e3;text-align:center;margin:0 0 6px 0;font-weight:500\">Any agent<\/p>\n        <div id=\"rwv3-ag0\" style=\"padding:7px 10px;border-radius:20px;font-size:13px;font-weight:400;text-align:center;cursor:pointer;color:#0693e3;border:1px solid #0693e340;margin-bottom:5px\">Client briefing<\/div>\n        <div id=\"rwv3-ag1\" style=\"padding:7px 10px;border-radius:20px;font-size:13px;font-weight:400;text-align:center;cursor:pointer;color:#0693e3;border:1px solid #0693e340;margin-bottom:5px\">Risk screening<\/div>\n        <div id=\"rwv3-ag2\" style=\"padding:7px 10px;border-radius:20px;font-size:13px;font-weight:400;text-align:center;cursor:pointer;color:#0693e3;border:1px solid #0693e340\">Proposal drafting<\/div>\n      <\/td>\n    <\/tr>\n  <\/table>\n  <p style=\"font-size:13px;color:#444444;font-weight:400;line-height:1.2;margin:20px 20px 0 0\">The same skill serves multiple agents across entirely different contexts, without reprogramming.<\/p>\n<\/div>\n\n\n\n<p class=\"has-normal-font-size\" style=\"background-color: #0693e320;padding: 15px;border-radius: 0 4px 4px 0;border-left: 4px solid #0693e3\">&#8220;A common pitfall: teams lock skills and knowledge inside system prompts \u2014 one monolithic prompt per agent, per use case. This creates silos. The knowledge can&#8217;t be reused, the logic can&#8217;t be shared, and every new agent starts from scratch. The result is a fragile, expensive architecture that doesn&#8217;t scale.&#8221;<\/p>\n\n\n\n<p><br>The solution is modular skills: discrete, reusable capabilities that any agent can draw from, without reprogramming.<\/p>\n\n\n<div class=\"at-spacer at-spacer--6a28714e9319f\" style=\"background-color: transparent\">\n<style>\n\/* Ultrawide *\/\n.at-spacer--6a28714e9319f {\n    height: 30px;\n}\n\n\/* Desktop *\/\n@media (max-width: 1920px) {\n    .at-spacer--6a28714e9319f {\n        height: 30px;\n    }\n}\n\n\/* Laptop *\/\n@media (max-width: 1024px) {\n    .at-spacer--6a28714e9319f {\n        height: 30px;\n    }\n}\n\n\/* Mobile *\/\n@media (max-width: 767px) {\n    .at-spacer--6a28714e9319f {\n        height: 30px;\n    }\n}\n<\/style>\n<\/div>\n\n\n<section class=\"horizontal-rule-block  js-horizontal-rule-block block  remove-bottom-spacing  remove-top-spacing\"  >\n    <div class=\"container\">\n        <hr class=\"wp-block-separator\"\/>\n                    <div>05 \u00b7 The non-negotiable condition<\/div>\n            <\/div>\n<\/section>\n\n\n<p class=\"has-black-color has-text-color has-link-color wp-elements-ba5de9e566ceae057eba5310cf987b2c\" style=\"font-size:25px\"><strong>Telling the agent what to do vs having guardrails defining what it can&#8217;t.<\/strong><\/p>\n\n\n\n<p>The freedom that makes agents powerful is exactly where the risk lives. Agentic failure modes are genuinely difficult to foresee \u2014 an agent can take paths you didn&#8217;t anticipate, combine actions in ways that weren&#8217;t tested, and produce consequences that are hard to reverse.<br>Your deployment decision rests on one thing: the quality of your hard guardrails. The test: if the agent does something wrong within this boundary, the consequence is additional work \u2014 not damage. Mistakes become learning events. The system corrects, sharpens, and improves over time.<\/p>\n\n\n\n<p class=\"has-normal-font-size\" style=\"background-color: #0693e320;padding: 15px;border-radius: 0 4px 4px 0;border-left: 4px solid #0693e3\">&#8220;We cannot solve guardrails by throwing more AI at it. We need deterministic, infrastructure-level boundaries.&#8221;<\/p>\n\n\n\n<div style=\"background-color:#00000005;border-radius:4px;padding:10px 20px 20px 20px;font-family:system-ui,sans-serif;margin-bottom:40px;margin-top:40px\">\n  <p style=\"font-size:11px;letter-spacing:.1em;text-transform:uppercase;color:#555555;font-weight:500;margin-bottom:11px;margin-top:0\">Two types of guardrails<\/p>\n\n  <table style=\"width:100%;border-collapse:collapse\">\n    <tr>\n      <!-- Soft guardrail -->\n      <td style=\"width:50%;vertical-align:top;padding-right:8px;height:1px\">\n        <div style=\"border-radius:4px;border:1px solid #cccccc;padding:16px;height:100%\">\n          <p style=\"font-size:10px;letter-spacing:.08em;text-transform:uppercase;color:#555555;font-weight:600;margin:0 0 8px 0\">Soft guardrail<\/p>\n          <p style=\"font-size:13px;font-weight:500;color:#191919;margin:0 0 6px 0;line-height:1.3\">At the prompt level<\/p>\n          <p style=\"font-size:13px;color:#444444;font-weight:300;line-height:1.55;margin:0 0 12px 0\">An instruction telling the agent what not to do. Clear and easy to set up, but a sufficiently complex sequence of actions can work around it.<\/p>\n          <div style=\"border-radius:4px;background-color:#f0f0f0;padding:12px\">\n            <p style=\"font-size:11px;font-weight:600;color:#555555;margin:0 0 4px 0\">Example<\/p>\n            <p style=\"font-size:12px;color:#444444;font-weight:300;margin:0;line-height:1.4;font-style:italic\">&#8220;Please don&#8217;t use tool X.&#8221;<\/p>\n          <\/div>\n          <p style=\"font-size:12px;color:#888888;font-weight:300;margin:10px 0 0 0;line-height:1.4\">Can be circumvented by complex action sequences.<\/p>\n        <\/div>\n      <\/td>\n\n      <!-- Hard guardrail -->\n      <td style=\"width:50%;vertical-align:top;padding-left:8px;height:1px\">\n        <div style=\"border-radius:4px;border:1px solid #0693e340;background-color:#0693e308;padding:16px;height:100%\">\n          <p style=\"font-size:10px;letter-spacing:.08em;text-transform:uppercase;color:#0693e3;font-weight:600;margin:0 0 8px 0\">Hard guardrail<\/p>\n          <p style=\"font-size:13px;font-weight:500;color:#191919;margin:0 0 6px 0;line-height:1.3\">At the architecture level<\/p>\n          <p style=\"font-size:13px;color:#444444;font-weight:300;line-height:1.55;margin:0 0 12px 0\">A technical boundary enforced by infrastructure. The agent has no access to begin with \u2014 there is nothing to circumvent.<\/p>\n          <div style=\"border-radius:4px;background-color:#cce6f8;padding:12px\">\n            <p style=\"font-size:11px;font-weight:600;color:#0693e3;margin:0 0 4px 0\">Example<\/p>\n            <p style=\"font-size:12px;color:#0693e3;font-weight:300;margin:0;line-height:1.4;font-style:italic\">&#8220;API access to tool X is blocked.&#8221;<\/p>\n          <\/div>\n          <p style=\"font-size:12px;color:#0693e3;font-weight:300;margin:10px 0 0 0;line-height:1.4\">Enforced by architecture \u2014 the agent simply cannot cross it.<\/p>\n        <\/div>\n      <\/td>\n    <\/tr>\n  <\/table>\n<\/div>\n\n\n\n<p>The instinct is to solve this with more AI: a second model reviewing the first, a prompt telling the agent to be careful. These are soft guardrails. They matter, but a sufficiently complex action sequence can circumvent any instruction. The only boundary you can trust is deterministic and infrastructure-level \u2014 enforced before the model makes any decision.<br>The organisations that benefit most from agents are not those with the most sophisticated models. They are those that invested in defining an honest boundary and committed to operating within it.<\/p>\n\n\n\n<p class=\"has-medium-font-size\"><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<p><a class=\"\" id=\"_msocom_1\"><\/a><strong><span style=\"font-family: articulat-cf, sans-serif;font-size: 16px;font-weight: 700\">T<\/span>his article was written by Bruna Di Bisceglie (Program Manager), Gerben Rijpkema (Data Scientist), and Niels Mateijsen (Data scientist) at Rewire. <\/strong><\/p>\n\n\n\n<section class=\"cta-box-block  js-cta-box  block\" >\n    <div class=\"container\">\n        <div class=\"cta-box\" style=\"background: linear-gradient(25deg, rgba(255,244,0, 0.13), rgba(37,206,206, 0.13));\">\n                            <figure class=\"cta-box__image\">\n                        <span class=\"cta-box__img\" data-lazy style=\"background-color: #f1f1f1;\">\r\n        \r\n                    <img data-lazy-full=\"https:\/\/rewirenow.com\/app\/uploads\/2024\/02\/data-foundations-bg-980x600.jpg\" alt=\"\" data-is-lazy>\r\n            <\/span>\r\n\r\n                <\/figure>\n                        <div class=\"cta-box__content\">\n                                    <h4 class=\"cta-box__title\">Agents reward organisations that ask harder questions first.<\/h4>\n                                                    <p class=\"cta-box__description\">The organisations getting compounding value from agentic AI share one trait: they invested in getting the foundations right before scaling. The right problem. The right organisational posture. The right skill layer. The right boundaries.<br \/>\r\n<br \/>\r\nWe&#8217;ve built agent systems across financial services, energy, telecom, and public sector, from early proofs of concept to production systems running at scale. We&#8217;ve seen what separates the deployments that deliver from the ones that don&#8217;t.<\/p>\n                                                    <a class=\"cta-box__link btn btn--next\" href=\"https:\/\/rewirenow.com\/en\/contact\/\" target=\"_blank\" aria-label=\"Let's find the answers for your situation\">Let&#8217;s find the answers for your situation<\/a>\n                            <\/div>\n        <\/div>\n    <\/div>\n<\/section>\n\r\n    <\/div>\r\n<\/section>","protected":false},"excerpt":{"rendered":"<p>Five things we&#8217;ve learned, across sectors and scales, about what makes implementing AI agents successful.<\/p>\n","protected":false},"author":4,"featured_media":12620,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[178,149],"tags":[160,161],"class_list":["post-11676","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-agentic-ai-genai","category-data-and-ai-strategy","tag-data-interoperability","tag-data-semantics"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v22.3 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Enterprise AI: are you sure you need AI agents? 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