October 40, 2024 - What's in your stack?

The Breakpoint

Hey all, welcome back to The Breakpoint — our weekly roundup of the most interesting full-stack developer tools that have launched on the site. In this week’s edition: tools to improve your AI agents, an analysis on the best data stack, and some pro-tips from the developer community.

The Latest

Five of the coolest dev tools that have launched recently

APIPark: An open source AI gateway & API developer portal

APIPark is an open-source AI gateway and developer portal that lets you easily manage, integrate, and deploy all of your AI and API products. What’s handy is that it connects to different AI models so you can use it in any workflow. 

Canonical AI: Analytics for your voice AI agent

Canonical AI is a tool that helps voice AI developers improve their agents. It maps user journeys to show you where and why callers are dropping off so you can step in and fix any bugs, or latency issues, or just improve your agent’s human-ness. 

Vectorize: Build RAG pipelines that are optimized for your data.

Vectorize is a data platform for retrieval augmented generation (RAG). It combines RAG evaluation to identify the best way to vectorize your data with a cloud-scale RAG pipeline engine. Vectorize populates your vector database and keeps your vector data fresh.

Upsolve AI: Customer-facing analytics as a service

Upsolve AI allows you to build and deliver analytics to your end-users through embeddable dashboards. You can connect different services and build dashboards super quickly with no-code building blocks. 

Chat2DB Local: Write SQL & analyze data with AI.

Chat2DB Local lets you write and analyze SQL with AI. You can generate optimal SQL and get insights with simple prompts, and it connects to all the most popular database options.

The Big Idea

We recently published an article by Hex CEO Barry McCardel about the best data analysis tools on the market right now. Barry breaks down the state of the landscape and then gives his candid thoughts on the biggest players. A teaser: 

“A common way to refer to the collection of data tools at any organization is a “data stack,” and – as the name implies – they loosely align to “layers” that can integrate and build on each other.

The big deal in the last few years has been a pattern referred to as the modern data stack”, which was mostly a marketing buzzword signifying tools that assume a cloud data warehouse as the center of the universe.

To explain this, we’re going to work our way up the data stack, starting from the bottom. I’m going to give a high-level of description on each “layer”, mentioning leading tools in the area they’re best known for…”

Bonus

Workflows can always be better, here’s some pro-tips crowdsourced from the dev community:

When using Replit Agent, once the agent has finished the task you can open the AI tab and have GPT-4o or Claude 3.5 breakdown each step of the code to you. h/t to Jeff Burke for this tip. 

—- When using Cursor, you can ask it to recommend an optimum folder structure and then instruct it to build out that structure. This makes it easier to get started and it makes Cursor more accurate because it knows where to update files. h/t to Ian Nuttall for this tip.

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