talk: finish pres and yt script

slides/why_llms_dont_make_choices/index.md

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+---
+title: Why LLMs Don't Make Decisions
+theme: default
+layout: center
+class: text-center
+fonts:
+  sans: "CaskaydiaCove Nerd Font Mono"
+---
+
+# Why LLMs don't make decisions
+
+---
+layout: center
+---
+
+# The Narrative vs. The Reality
+
+<div class="grid grid-cols-2 gap-12 mt-16 text-left">
+<v-click>
+    <div class="border-l-4 border-purple-500 pl-6">
+        <h3 class="text-purple-400 text-2xl font-bold mb-2">The "Agentic" Narrative</h3>
+        <ul class="list-disc pl-4 text-gray-400 space-y-2">
+            <li>"The agent <span class="text-white">decided</span> to call the tool."</li>
+            <li>"The model <span class="text-white">assessed</span> the PRD."</li>
+            <li>"It <span class="text-white">chose</span> the execution path."</li>
+        </ul>
+    </div>
+</v-click>
+<v-click>
+    <div class="border-l-4 border-green-500 pl-6">
+        <h3 class="text-green-400 text-2xl font-bold mb-2">The Engineering Reality</h3>
+        <ul class="list-disc pl-4 text-gray-400 space-y-2">
+            <li>It is <span class="text-white">completing a pattern</span>.</li>
+            <li>It is <span class="text-white">statistically mapping</span> tokens.</li>
+            <li>It is <span class="text-white">following constraints</span>.</li>
+        </ul>
+    </div>
+</v-click>
+</div>
+<v-click>
+    <div class="mt-12 text-center text-gray-400 italic">
+        "We mistake highly accurate mapping for decision making."
+    </div>
+</v-click>
+
+---
+layout: center
+---
+
+# The Domino Analogy
+
+<div class="mt-10">
+    <p class="text-2xl leading-relaxed">
+        "If I set up a long row of dominos... and the last domino falls and hits a bell..."
+    </p>
+    <v-click>
+    <div class="text-4xl font-bold text-red-400 mt-8 mb-8">
+        Did the last domino <span class="underline decoration-white">decide</span> to ring the bell?
+    </div>
+    </v-click>
+    <v-click>
+        <p class="text-xl text-gray-400">Of course not.</p>
+    </v-click>
+</div>
+
+---
+layout: default
+---
+
+# The functional reality of LLMs
+
+If we strip away the magic, an LLM is effectively a **pure, stateless function**.
+
+```csharp {all|1|3-6|8}
+ProbabilityDistribution PredictNext(int[] contextTokens, float[] fixedWeights)
+{
+    // 1. Input: Static sequence of integers (Tokens)
+    // 2. Process: Fixed graph of matrix operations (Weights)
+
+    // Matrix Multiplication Magic...
+
+    return probabilities; // 3. Output: Probability scores
+}
+```
+
+<div class="grid grid-cols-2 gap-8 mt-8">
+    <v-click>
+        <div class="bg-gray-800 p-4 rounded border-t-2 border-blue-400">
+            <div class="font-bold mb-1">No "Pondering"</div>
+            <div class="text-sm text-gray-400">There is no loop where it weighs pros and cons. It is a single, deterministic forward pass.</div>
+        </div>
+    </v-click>
+    <v-click>
+        <div class="bg-gray-800 p-4 rounded border-t-2 border-green-400">
+            <div class="font-bold mb-1">The "Choice" is External</div>
+            <div class="text-sm text-gray-400">The <b>Sampler</b> picks the token based on temperature. The model just provides the stats.</div>
+        </div>
+    </v-click>
+</div>
+
+---
+layout: center
+---
+
+# Where the logic actually lives
+
+<div class="flex flex-col items-center justify-center mt-8">
+    <div class="grid grid-cols-2 gap-4">
+        <div class="p-6 border border-gray-700 rounded-lg bg-gray-900 text-center">
+            <h3 class="text-blue-400 font-bold text-xl mb-2">Prompt Engineering</h3>
+            <p class="text-sm text-gray-400">Rigging the machine so it pays out the exact token we need 99% of the time.</p>
+        </div>
+        <div class="p-6 border border-gray-700 rounded-lg bg-gray-900 text-center">
+             <h3 class="text-green-400 font-bold text-xl mb-2">The Agentic Loop</h3>
+             <p class="text-sm text-gray-400">Engineering the context so the "next token" is useful JSON, not hallucinated poetry.</p>
+        </div>
+    </div>
+</div>
+
+---
+layout: center
+---
+
+# Why the distinction matters
+
+<div class="mt-8 space-y-6">
+    <v-click>
+        <div class="flex items-start gap-4">
+            <div class="bg-blue-500 text-white rounded-full w-8 h-8 flex items-center justify-center font-bold shrink-0">1</div>
+            <div>
+                <h3 class="text-xl font-bold text-blue-400">Constrain the Context</h3>
+                <p class="text-gray-400">Reduce the search space so the "right" token is the only probable one.</p> 
+            </div>
+        </div>
+    </v-click>
+    <v-click>
+        <div class="flex items-start gap-4">
+            <div class="bg-purple-500 text-white rounded-full w-8 h-8 flex items-center justify-center font-bold shrink-0">2</div>
+            <div>
+                <h3 class="text-xl font-bold text-purple-400">Rig the Inputs</h3>
+                <p class="text-gray-400">Format prompts so the pattern that <i>needs</i> to be completed leads to your output.</p>
+            </div>
+        </div>
+    </v-click>
+    <v-click>
+        <div class="flex items-start gap-4">
+            <div class="bg-green-500 text-white rounded-full w-8 h-8 flex items-center justify-center font-bold shrink-0">3</div> 
+            <div>
+                <h3 class="text-xl font-bold text-green-400">Verify the Output</h3>
+                <p class="text-gray-400">It didn't "choose" based on belief. It made a statistical guess. Always validate.</p>
+            </div>
+        </div>
+    </v-click>
+</div>
+
+---
+layout: center
+---
+
+# Conclusion
+
+<div class="text-2xl mt-10 mb-10 mx-auto text-gray-300">The "Decision" is just the inevitable result of the constraints and context <b>you</b> fed into the prediction engine.</div>

slides/why_llms_dont_make_choices/script.md

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+[Face to Camera]
+
+"There is a dangerous idea spreading in software engineering right now. It's the idea that Large Language Models are 'Decision Makers'."
+
+"We treat them like junior employees. We think they 'choose' to call a tool, or 'decide' how to fix a bug."
+
+[Switch to Presentation]
+
+"But today, I want to show you why that mental model is wrong—and how it leads to fragile software."
+
+[CLICK]
+
+"We need to distinguish between the Narrative and the Reality."
+
+[CLICK]
+
+"The narrative—the marketing fluff—says things like: 'The agent decided to call the tool.' Or 'The model assessed the PRD and chose a path.'"
+
+"This language implies agency. It implies intent."
+
+[CLICK]
+
+"But the engineering reality is boring. The model is simply completing a pattern. It is statistically mapping tokens based on weights. It is following constraints we set."
+
+[CLICK]
+
+"We mistake highly accurate mapping for decision making."
+
+[CLICK]
+
+"Think of it this way."
+
+"If I set up a long row of dominos... and the last domino falls and hits a bell..."
+
+[CLICK]
+
+"Did the last domino decide to ring the bell?"
+
+[CLICK]
+
+"Of course not. It just followed the physics of the environment I built."
+
+"The 'decision' to ring the bell wasn't made by the domino. It was made by the person who set it up."
+
+[CLICK]
+
+"If we strip away the magic, an LLM is effectively a pure, stateless function."
+
+[CLICK]
+
+"You give it a static sequence of tokens."
+
+[CLICK]
+
+"It pushes those integers through a fixed graph of matrix operations."
+
+[CLICK]
+
+"And it returns a probability distribution. Not a choice. A list of percentages."
+
+[CLICK]
+
+"There is no 'pondering' inside that function. There is no while loop where it weighs the pros and cons. It is a single, deterministic forward pass."
+
+[CLICK]
+
+"The actual 'choice' happens outside the model. The Sampler picks the token based on temperature. The model didn't 'decide' to output a JSON bracket; it just assigned it a 99% probability because you rigged the prompt."
+
+[CLICK]
+
+"So if the model isn't deciding, where does the logic actually live?"
+
+"It lives in two places."
+
+"First, Prompt Engineering. This isn't 'whispering to AI'. It is rigging the slot machine so it pays out the exact token we need 99% of the time."
+
+"Second, The Agentic Loop. We engineer the context so that the only statistically probable next token is useful JSON, not hallucinated poetry."
+
+[CLICK]
+
+"This distinction matters because it changes how you build software."
+
+[CLICK]
+
+"If you know it's not a decision maker, you focus on Constraining the Context. You reduce the search space so the 'right' token is the only probable one."
+
+[CLICK]
+
+"You Rig the Inputs. You format your prompts so the pattern that needs to be completed inevitably leads to your desired output."
+
+[CLICK]
+
+"And crucially, you Verify the Output. You never trust the model's 'belief', because it has none. It made a statistical guess. You must validate it."
+
+[CLICK]
+
+"The bottom line is this: The 'Decision' is just the inevitable result of the constraints and context you fed into the prediction engine."
+
+"You are the decision maker. The model is just the domino."
+
+"Thanks for watching."