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Fix typo in factor-01: Change 'Hey Jeff' to 'Hey Terri' in memo #77

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Fix typo in factor-01: Change 'Hey Jeff' to 'Hey Terri' in memo #77

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Fix typo in factor-01: Change 'Hey Jeff' to 'Hey Terri' in memo
HarinderG Oct 6, 2025
9af30f5
Fix additional typos: 'Jeff' -> 'Terri' in code example and 'libriari…
HarinderG Oct 6, 2025
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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -180,7 +180,7 @@ Anyways back to the thing...

### Design Patterns for great LLM applications

After digging through hundreds of AI libriaries and working with dozens of founders, my instinct is this:
After digging through hundreds of AI libraries and working with dozens of founders, my instinct is this:

1. There are some core things that make agents great
2. Going all in on a framework and building what is essentially a greenfield rewrite may be counter-productive
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4 changes: 2 additions & 2 deletions content/factor-01-natural-language-to-tool-calls.md
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Expand Up @@ -22,7 +22,7 @@ to a structured object that describes a Stripe API call like
"product": "prod_8675309",
"price": "prc_09874329fds",
"quantity": 1,
"memo": "Hey Jeff - see below for the payment link for the february ai tinkerers meetup"
"memo": "Hey Terri - see below for the payment link for the february ai tinkerers meetup"
}
}
}
Expand All @@ -36,7 +36,7 @@ From there, deterministic code can pick up the payload and do something with it.
# The LLM takes natural language and returns a structured object
nextStep = await llm.determineNextStep(
"""
create a payment link for $750 to Jeff
create a payment link for $750 to Terri
for sponsoring the february AI tinkerers meetup
"""
)
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