A reminder from Atomic Habits by James Clear:
“It doesn't make sense to continue wanting something if you're not willing to do what it takes to get it. If you don't want to live the lifestyle, then release yourself from the desire. To crave the result but not the process is to guarantee disappointment.”
FOR THE FIRST TIME IN 53 YEARS, THE KNICKS ARE NBA CHAMPIONS 🏆
New York defeats San Antonio 4-1 in the NBA Finals, capturing their third championship in franchise history!
So many companies are rolling out new AI tools for developers while ignoring that in order for folks to be effective with these tools, they need to learn new skills.
@datadoghq's new Software Delivery Suite is aimed at helping developers better understand what's happening between code and production, so they can ship changes more safely.
And thankfully, they also put together a toolkit of learning resources including topics like...
- understanding LLM behavior, output quality, latency, cost
- using MCP to connect AI assistants to relevant context
- rolling out changes gradually as shipping velocity increases
- validating whether agent behavior is actually improving user experience
- ensuring your CI/CD pipeline doesn't become the bottleneck as you're producing features more frequently
➡️Download the toolkit here: fandf.co/3Rn3YX0
Thanks to Datadog for partnering on this post and more importantly for helping developers learn how to confidently ship software as AI increasingly becomes part of the dev workflow.
Hold up. $9.99 for this at @IKEA?
Chipotle Lime Chicken.
White rice.
Black beans.
Plantains.
I understand Costco got the $1.50 glizzy, but this right here?
Nah this is a new weekly stop for me.
DROP EVERYTHING
Everything you need to get started with Local AI completely FOR FREE
Hardware. Software. Anything in between.
> TheLocalAIBook DOT com
Local LLMs From Zero to Hero Articles
- Hardware foundations
- Software stacks
- Model mechanics
> BuyAGPU dot AI
The Buy a GPU Guide Thread
- How to build systems for Local AI
- Explains what to buy, for which use cases, etc
For inference. For training. For your use case.
The resources exist
No more excuses
Opensource / Local AI FTW