DevToolsDigest: Issue #316
This week's digest includes news and resources from Relta, Nile, Tailscale, and more.
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The Week in Developer Tools
The Best Open-Source AI Models: All Your Free-to-Use Options Explained
Open-source AI models offer several advantages, including customization, transparency, and community-driven innovation. These models allow users to tailor them to specific needs and benefit from ongoing enhancements. Additionally, they typically come with licenses that permit both commercial and non-commercial use, which enhances their accessibility and adaptability across various applications.
Framework: How AI Agents Will Transform the Decision-Making Funnel
"Whoever wins the personal agent, that’s the big thing, because you will never go to a search site again, you will never go to a productivity site, you’ll never go to Amazon again." These words paint a clear picture of where we’re headed: AI is no longer a sidekick, but rather a leading actor in the decision making process.
Amit Eyal Govrin of Kubiya & Jesse Robbins of Heavybit on CUBE Conversations
We're seeing a shift in the entire genAI approach from top to bottom. You have to have an underlying change in the tooling that gets you the ability to unlock, as we had to do at the beginning of the DevOps cycle, where you had infrastructure automation and infrastructure-as-code. Fundamentally, what we're seeing is an entire re-write of the stack and it's enabling a new category of data pipeline.
Industry Research
Reliable and Secure Natural Language Interfaces for SaaS
When software developers realized GPT3.5 could write syntactically correct SQL, the race was on to build text-to-SQL into everything. While the accuracy of these models keeps increasing in academic benchmarks, the features built on text-to-SQL are mediocre at best and annoying at worst. It is at a point where some are questioning if users even want these features at all, even though there are few if any solutions that actually work.
Building Successful Multi-Tenant RAG Applications
Many popular business apps that have AI capabilities use the common RAG architectures pattern to generate more relevant and accurate results. Aside from being RAG apps, all have something else in common: they are all multi-tenant applications, and in any given interaction, they only retrieve data for the current tenant. This makes sense when you think about it. No marketing team wants to send personalized emails based on customer's interactions with a different company.