Generative AI Thru This

June 26, 2023 by Jay Cuthrell

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Music: Daniel Bedingfield - Gotta Get Thru This (2001)

This week we take a look at Generative AI for platform engineering.

Getting Informed

If you’ve worked with me before then you might recall periodic emails/blogs on “What is Jay reading 📖”. This week, I’ll expand reading 📖 to listening 🎧 and watching 📺.

These are just a few sources from the past month where I see a potential for convergence and Generative AI for platform engineering:

• 📖 Speed 2: Control Your Cruise by Charles Stucki
• 📖 Increasing Awareness of Internal Tools by Abi Noda
• 📖 IBM Consulting unveils Center of Excellence for generative AI by Jonn Granger
• 📖 AWS plans to invest $100M to help companies build generative AI tools via Techmeme
• 🎧 The Need for a Developer Portal interview of OpsLevel CTO Ken Rose by Screaming in the Cloud Host Corey Quinn
• 🎧 Second Wave DevOps interview of System Initiative CEO Adam Jacob by Cloudcast Host Brian Gracely
• 🎧 Adventures in Automation interview of GTS DevOps Leader Jose Vincente Nunez, Apollo GraphQL Developer Advocate Patrick Arminio, and Red Hat Consultant Satyajit Lele by Compiler Hosts Johan Philippine, Brent Simoneaux, and Angela Andrews
• 📺 Is Your Platform Ready for AI? from Lightbend Developer Advocate Hugh McKee
• 📺 Enter the Machines: Reducing Friction in DevOps Using AI from Firefly CPO Eran Bibi

I close my eyes and it’s gone again 🎶

First, I remain bullish on the implications for forensic insights potentials of so-called big data and the convergence of platform engineering. Finding exhaustive productivity through inclusion of generative AI that augments in a human + machine partnership is the key.

Second, I believe that generative AI will be increasingly useful in getting started faster in more meaningful ways. Alliteration wise, said simply, this means syntactic sugar with scaffolding services suitable for solving or supplying a solution that has some semblance of sensible standards.

Third, I believe there are progressions ahead in domain-specific language (DSL) as a whole. We will find ourselves in a future with poets of, in, and for DSLs.

Fourth, these DSL poets will flourish. Perhaps one day, a prompt engineer will be the poet of essential abstractions for everything we once considered to be business as usual IT.

I’m gonna get through this 🎶

That said, I am certain someone somewhere is going to riff on “4-hour work week” themes and publish “4-prompt workweek” or similar… perhaps using generative AI based simulacrum based on a model of every major best-selling book of the personal productivity genre. Set a timer for when this concept becomes a SxSW Interactive panel — and if it hasn’t already been pitched, I just might.

Finally, a cautionary tale — online, a common acronym is IANAL (I am not a lawyer). Perhaps we should consider IANALLM (I am not a large language model) be added to the lexicon.^[1]

So, what will be the next big thing in generative AI and platform engineering?

Until then… Place your bets!

Disclosure

I am linking to my disclosure.

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1. Case 1:22-cv-01461-PKC Document 54 Filed 06/22/23
   🤓 ↩︎

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✍️ 🤓 Edit on Github 🐙 ✍️

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