talk: finish pres and yt script

2026-02-09 13:51:03 -06:00
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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."
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+[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."
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+"If I set up a long row of dominos... and the last domino falls and hits a bell..."
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+[CLICK]
+
+"Did the last domino decide to ring the bell?"
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+[CLICK]
+
+"Of course not. It just followed the physics of the environment I built."
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+"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."
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+[CLICK]
+
+"You give it a static sequence of tokens."
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+[CLICK]
+
+"It pushes those integers through a fixed graph of matrix operations."
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+[CLICK]
+
+"And it returns a probability distribution. Not a choice. A list of percentages."
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+[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."
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+"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."
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+"Second, The Agentic Loop. We engineer the context so that the only statistically probable next token is useful JSON, not hallucinated poetry."
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+[CLICK]
+
+"This distinction matters because it changes how you build software."
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+[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."
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+[CLICK]
+
+"You Rig the Inputs. You format your prompts so the pattern that needs to be completed inevitably leads to your desired output."
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+[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."
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+"You are the decision maker. The model is just the domino."
+
+"Thanks for watching."