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Save the date for Code BEAM America 2025 - the Erlang and Elixir Conference!

More info soon!

Get access to the Very Early Bird tickets - the waiting list is open https://codebeamamerica.com

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Call for Talks will start in October

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We meant August :nerd_face:

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First two keynote speakers are with us!
Join them as part of the Code BEAM America lineup - our Call for Talks is still open

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You have it till the end of the week to submit your talk!

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Lineup: up :white_check_mark:
Ticket sale: on :white_check_mark:
Diversity & Inclusion Programme: open :white_check_mark:
Call for Volunteers: on :white_check_mark:
See you in: March :partying_face:

CodeSync

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Early Birds discount is still on!
Book your spot before 21 Jan: codebeamamerica.com

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The Erlang Ecosystem Foundation Programme is on! Apply here: Code BEAM America

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If you’re not sure what to do once you come to San Francisco, check out our free guide with tips and discounts :slightly_smiling_face:

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The first Code BEAM America keynote is live! https://youtu.be/R9JRhIKQmqk?si=grsk6jREKgoYQlTz
LLMs are incredible. I would argue that, at times, LLMs can feel like magic. Some would capitalize on that argument by pointing out that modern “magic is performed by tricksters and illusionists—implying that LLMs do nothing more than give the illusion of intelligence. The truth is LLMs are magicians, but their greatest trick is not writing code or perfectly formatting your e-mail, it’s convincing founders, executives, product managers, etc. to make their products less useful by adding LLM-based features nobody asked for. Many of these features are unnecessarily complex because they attempt to shoehorn LLMs to work in systems that were designed decades before the Transformer even existed.

LLMs deserve better. Your products deserve better. We all deserve better. To truly unlock the potential of LLMs, we need to start thinking about how to design systems that are LLM-native. In this talk, I will discuss what it means for a system to be LLM-native, what you need to consider when building LLM-based systems, and demonstrate LLM-native alternatives to decades old software solutions.

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