AWS App Studio
AWS launched AWS App Studio, a low-code app builder using AI. Users describe apps in natural language for quick enterprise-grade app creation. Features granular access control, cost savings, and use cases like automation and digitization.
Read original articleAWS has introduced AWS App Studio, a low-code application builder powered by generative AI. This service allows users to create enterprise-grade applications quickly without requiring extensive software development skills. Users can describe the application they want to build using natural language, and App Studio will generate a multi-page user interface, data model, and custom business logic accordingly. The platform handles deployment, operations, and maintenance, freeing up technical professionals to focus on innovation. App Studio offers granular access control policies, enhancing security and governance for IT teams. Additionally, the service provides cost savings by offering free application building and charging only when end users interact with published applications. Use cases for App Studio include claims processing automation, inventory management, project approval streamlining, audit digitization, and metrics and reporting consolidation. This tool aims to empower a new set of builders to develop applications efficiently and securely.
Related
The Death of the Junior Developer – Steve Yegge
The blog discusses AI models like ChatGPT impacting junior developers in law, writing, editing, and programming. Senior professionals benefit from AI assistants like GPT-4o, Gemini, and Claude 3 Opus, enhancing efficiency and productivity in Chat Oriented Programming (CHOP).
Figma AI: Empowering designers with intelligent tools
Figma AI enhances designers' workflow with AI-powered features like Visual Search, Asset Search, text tools, and content generation. It aims to streamline tasks, boost efficiency, and spark creativity while prioritizing data privacy.
Gen AI is passé. Enter the age of agentic AI
The article explores the shift from generative AI to agentic AI in enterprises, focusing on task-specific digital assistants. It discusses structured routes for enterprise agents, agentic AI in supply chain management, RPA's role, and customized systems for businesses, envisioning a goal-oriented AI future.
How I Use AI
The author shares experiences using AI as a solopreneur, focusing on coding, search, documentation, and writing. They mention tools like GPT-4, Opus 3, Devv.ai, Aider, Exa, and Claude for different tasks. Excited about AI's potential but wary of hype.
US intelligence community is embracing generative AI
The US intelligence community integrates generative AI for tasks like content triage and analysis support. Concerns about accuracy and security are addressed through cautious adoption and collaboration with major cloud providers.
> technical professionals without deep software development skills, such as IT project managers, data engineers, and enterprise architects,
Perhaps IT project managers get a pass, but imagine being an "enterprise architect" without deep software engineering skills. My first nightmare is to have to work with an enterprise architect that can't code. My second nightmare is maintaining software they built with AI.
> describe your desired app functionality, and GenAI will automatically build out the data models, user interfaces, workflows, and connectors.
Looks rushed, given typos on the page, and the pricing model seems weird: it's free to create the app, but you pay by the user-hour.
Can we trust that it is designed to generate apps that utilise the least AWS chargeable resources to run?
No, we can't.
AWS can't provide this service if there is a perceivable conflict of interest.
What is the big push for companies to NOT have professionals involved. These things are not trivial, at least to get right. Not having a professional involved is not the benefit they think it is.
Give project managers/sales/support desk/etc access to this. Let them build their thing, push it into limited use, evolve the design based on feedback, and then hand it over to developers to reverse engineer into a maintainable app based on the app's behavior and the chat logs that built it.
It's a WYSIWYG editor for the 21st century; we all know the code will be crap, but it's a decent enough starting point to build something real from.
Related
The Death of the Junior Developer – Steve Yegge
The blog discusses AI models like ChatGPT impacting junior developers in law, writing, editing, and programming. Senior professionals benefit from AI assistants like GPT-4o, Gemini, and Claude 3 Opus, enhancing efficiency and productivity in Chat Oriented Programming (CHOP).
Figma AI: Empowering designers with intelligent tools
Figma AI enhances designers' workflow with AI-powered features like Visual Search, Asset Search, text tools, and content generation. It aims to streamline tasks, boost efficiency, and spark creativity while prioritizing data privacy.
Gen AI is passé. Enter the age of agentic AI
The article explores the shift from generative AI to agentic AI in enterprises, focusing on task-specific digital assistants. It discusses structured routes for enterprise agents, agentic AI in supply chain management, RPA's role, and customized systems for businesses, envisioning a goal-oriented AI future.
How I Use AI
The author shares experiences using AI as a solopreneur, focusing on coding, search, documentation, and writing. They mention tools like GPT-4, Opus 3, Devv.ai, Aider, Exa, and Claude for different tasks. Excited about AI's potential but wary of hype.
US intelligence community is embracing generative AI
The US intelligence community integrates generative AI for tasks like content triage and analysis support. Concerns about accuracy and security are addressed through cautious adoption and collaboration with major cloud providers.