chore: update ADL

Author: patwlan

static/adl/index.html

@@ -104,9 +104,9 @@
             background-size: 0% 100%;
             background-position: 0 88%; /* Lower it slightly so it looks like an underline/highlight */
             padding: 0 4px;
-            animation: highlight 8s ease-in-out infinite; /* 5s total cycle */
+            animation: highlight 10s ease-in-out infinite; /* 5s total cycle */
             animation-delay: 3s;
-            border-radius: 4px;
+            border-radius: 5px;
         }
     </style>
 </head>
@@ -148,21 +148,23 @@
     <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 relative">
         <div class="lg:grid lg:grid-cols-12 lg:gap-8">
             <div class="sm:text-center md:max-w-2xl md:mx-auto lg:col-span-6 lg:text-left">
-                <h1 class="text-4xl tracking-tight font-extrabold text-nature-dark sm:text-5xl md:text-6xl">
-                    <span class="block"><span class="supercharge-highlight">Supercharge</span> your</span>
-                    <span class="block text-nature-accent accent-glow">Prompt Engineering</span>
+                <h1 class="text-4xl tracking-tight font-extrabold text-nature-dark sm:text-5xl md:text-6xl supercharge-highlight">
+                    <span class="block text-nature-accent accent-glow">Agent Programming</span>
+                    <span class="block">Not Prompting</span>
                 </h1>
-                <p class="mt-3 text-base text-stone-600 sm:mt-5 sm:text-lg sm:max-w-xl sm:mx-auto md:mt-5 md:text-xl lg:mx-0">
-                    The Agent Definition Language (ADL) combines natural language with structural tokens to make AI
-                    agents predictable, robust, and manageable at scale.
-                </p>
+                <div class="mt-3 text-base text-stone-600 sm:mt-5 sm:text-lg sm:max-w-xl sm:mx-auto md:mt-5 md:text-xl lg:mx-0">
+                    <ul class="list-disc list-inside space-y-1">
+                        <li>Prompting is not a production model.</li>
+                        <li>Production agents must exhibit bounded, deterministic behavior.</li>
+                        <li> ADL defines programmable agent logic with enforced execution rules.</li>
+
+                    </ul>
+           
+                </div>
                 <div class="mt-8 sm:max-w-lg sm:mx-auto sm:text-center lg:text-left lg:mx-0">
-                    <p class="text-base font-medium text-stone-800">
-                        Build complex behaviors with stateful conversations.
-                    </p>
                     <div class="mt-5 sm:flex sm:justify-center lg:justify-start gap-4">
                         <a href="#usecases"
-                           class="flex items-center justify-center px-8 py-3 border border-transparent text-base font-medium rounded-md text-white bg-nature-primary hover:bg-nature-light md:py-4 md:text-lg transition">
+                           class="flex items-center justify-center px-8 py-3 border border-transparent text-base font-medium rounded-md text-white bg-nature-primary hover:bg-nature-light md:py-4 md:text-lg transition shadow-lg shadow-nature-primary/20">
                             Learn ADL
                         </a>
                         <a href="#run-adl-server"
@@ -267,7 +269,7 @@ <h2 class="text-base text-nature-primary font-semibold tracking-wide uppercase">
             <div class="lg:col-span-7 mb-8 lg:mb-0">
                 <div class="relative rounded-xl shadow-2xl border border-stone-200 overflow-hidden group">
                     <div class="absolute inset-0 bg-nature-primary/5 transition duration-500 group-hover:bg-transparent"></div>
-                    <img src="/lmos/adl/images/studio.png" alt="ADL Studio Interface" class="w-full h-auto object-cover transform bg-stone-100 min-h-[300px]" onerror="this.src='https://placehold.co/800x600/e7e5e4/3a5a40?text=ADL+Studio+Screenshot'"/>
+                    <img src="studio.png" alt="ADL Studio Interface" class="w-full h-auto object-cover transform bg-stone-100 min-h-[300px]" onerror="this.src='https://placehold.co/800x600/e7e5e4/3a5a40?text=ADL+Studio+Screenshot'"/>
                 </div>
             </div>
 
@@ -282,10 +284,10 @@ <h2 class="text-base text-nature-primary font-semibold tracking-wide uppercase">
                                     <path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M11 5H6a2 2 0 00-2 2v11a2 2 0 002 2h11a2 2 0 002-2v-5m-1.414-9.414a2 2 0 112.828 2.828L11.828 15H9v-2.828l8.586-8.586z" />
                                 </svg>
                             </div>
-                            <p class="ml-12 text-lg leading-6 font-medium text-nature-dark">Advanced Prompt Authoring</p>
+                            <p class="ml-12 text-lg leading-6 font-medium text-nature-dark">Reliable Agent Logic Authoring</p>
                         </dt>
                         <dd class="mt-2 ml-12 text-base text-stone-600">
-                            Craft and manage complex prompts with a powerful, structured editor designed for clarity and control.
+                            Author human-maintainable agent logic with enforced behavioral structure.
                         </dd>
                     </div>
 
@@ -428,10 +430,11 @@ <h2 class="text-3xl font-extrabold text-nature-dark tracking-tight">Run ADL Serv
         <div class="text-center">
             <h2 class="text-base text-nature-primary font-semibold tracking-wide uppercase">Core Philosophy</h2>
             <p class="mt-2 text-3xl leading-8 font-extrabold tracking-tight text-nature-dark sm:text-4xl">
-                Why ADL?
+                Why Agent Programming?
             </p>
             <p class="mt-4 max-w-2xl text-xl text-stone-600 lg:mx-auto">
-                Prompting is difficult so don't prompt. Instead define your requirements and let ADL to the rest.
+                Prompt-based systems are not reliable or verifiable.<br>
+                ADL defines programmable agent behavior for production systems.
             </p>
         </div>
 
@@ -445,10 +448,10 @@ <h2 class="text-base text-nature-primary font-semibold tracking-wide uppercase">
                                   d="M19.428 15.428a2 2 0 00-1.022-.547l-2.384-.477a6 6 0 00-3.86.517l-.318.158a6 6 0 01-3.86.517L6.05 15.21a2 2 0 00-1.806.547M8 4h8l-1 1v5.172a2 2 0 00.586 1.414l5 5c1.26 1.26.367 3.414-1.415 3.414H4.828c-1.782 0-2.674-2.154-1.414-3.414l5-5A2 2 0 009 10.172V5L8 4z"/>
                     </div>
                     <h3 class="mt-8 text-xl font-bold text-nature-dark text-center group-hover:text-nature-primary transition">
-                        Robust Structure</h3>
+                        Formal Structure</h3>
                     <p class="mt-4 text-stone-600 text-center">
-                        Combining natural language with special tokens makes agent behavior predictable. Define
-                        boundaries, rules, and formats that LLMs actually respect.
+                        Agent behavior must be explicitly defined.<br>
+                        ADL enforces rules, boundaries, and execution structure.
                     </p>
                 </div>
 
@@ -461,10 +464,10 @@ <h3 class="mt-8 text-xl font-bold text-nature-dark text-center group-hover:text-
                         </svg>
                     </div>
                     <h3 class="mt-8 text-xl font-bold text-nature-dark text-center group-hover:text-nature-primary transition">
-                        Progressive Disclosure</h3>
+                        Controlled Complexity</h3>
                     <p class="mt-4 text-stone-600 text-center">
-                        Manage complexity by revealing concepts and instructions only when needed. Similar to how humans
-                        learn, agents perform better when focused.
+                        Agents execute within scoped instructions.<br>
+                        Behavior is constrained to reduce ambiguity and failure.
                     </p>
                 </div>
 
@@ -476,10 +479,10 @@ <h3 class="mt-8 text-xl font-bold text-nature-dark text-center group-hover:text-
                                   d="M8 12h.01M12 12h.01M16 12h.01M21 12c0 4.418-4.03 8-9 8a9.863 9.863 0 01-4.255-.949L3 20l1.395-3.72C3.512 15.042 3 13.574 3 12c0-4.418 4.03-8 9-8s9 3.582 9 8z"/>
                     </div>
                     <h3 class="mt-8 text-xl font-bold text-nature-dark text-center group-hover:text-nature-accent transition">
-                        Stateful Conversations</h3>
+                        Stateful Execution</h3>
                     <p class="mt-4 text-stone-600 text-center">
-                        Unlike stateless API calls, ADL agents maintain context awareness over time, enabling
-                        long-running workflows and coherent multi-turn interactions.
+                        Agents maintain structured state across interactions.<br>
+                        Workflows become persistent and verifiable.
                     </p>
                 </div>
             </div>
@@ -623,17 +626,20 @@ <h3 class="mt-2 text-3xl leading-8 font-extrabold tracking-tight text-nature-dar
                 </h3>
                 <div class="mt-6 text-lg text-stone-600 space-y-6">
                     <p>
-                        The idea behind ADL UseCases is a fundamental shift: instead of "prompting" the Agent and
-                        creating a black box,
-                        you define your requirements in the form of clear, structured UseCases.
+                        Instead of writing prompts and hoping the agent behaves correctly,
+                        you describe what you want in clear, structured UseCases.
+
+
+
+
+
                     </p>
                     <p>
-                        The ADL Engine processes these UseCases and ensures that the Agent behaves according to your
-                        specifications.
+                        ADL turns those UseCases into reliable behavior.
                     </p>
                     <p>
-                        Behind the scenes, the ADL Engine translates UseCases into optimized prompts or tools,
-                        manages conversation state, and enforces your business rules.
+                        The agent follows your rules, keeps context,
+and works the way you expect.
                     </p>
                 </div>
             </div>
@@ -692,7 +698,6 @@ <h4 class="text-sm font-bold text-nature-primary mb-2 flex items-center gap-2">
     </div>
 </section>
 
-
 <!-- ADL Technical Specification -->
 <section id="technical-spec" class="py-16 bg-nature-page border-t border-nature-border">
     <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">