UI

UI Bakery AI Agent – build secure internal tools by chatting

Hacker News

UI Bakery AI Agent – build secure internal tools by chatting

Hello HN community, Many of you have probably used drag-and-drop builders to create internal tools or dashboards. They’re great for quick prototypes - but as projects grow, the same problems always appear: 1) Performance issues. D&D builders add a lot of runtime overhead. Once you add more screens, logic, or connected data sources, things start to lag - and you have little control over optimization. 2) Limited flexibility. You’re restricted to the vendor’s components and configuration options. Anything custom usually turns into a hack. 3) Design overhead. You still spend a lot of time manually picking components, arranging layouts, and tweaking spacing before even connecting data - and the final result often looks… meh. 4) Maintenance pain. Opening an old project (or one handed off to a new teammate) often means digging around to find where things live. There’s no simple way to reason about structure or reuse. At UI Bakery, we kept asking ourselves how to fix these issues without losing the speed of a low code builder. First, we built an AI assistant trained on our docs. Then, about 1.5 years ago, we launched the AI App Generator, which could generate UI Bakery apps from text prompts. That helped, but under the hood it was still drag-and-drop - with all its inherent limits. That’s when we decided to rethink the foundation entirely. “What’s the most flexible, customizable project model possible?” The answer: code. So we rebuilt our approach and are now launching UI Bakery AI App Agent - a new way to build secure internal software by chatting. Key features: - Data connectors: Connect to SQL, NoSQL, REST APIs, and third-party services. - Speed: Start from a plain-text prompt - AI generates a fully functional app in minutes. - Code ownership: Access and edit the generated React code directly. - Security: RBAC, SSO, SOC 2 compliance, audit logs, and deployment either in our cloud or fully on-prem. - Customization: Use any React component you find online or build your own - it’s all just code. Who is it for? - Founders/CTOs automating internal processes. - Developers tired of rebuilding CRUD/admin UIs from scratch. - Enterprise teams needing internal tools with advanced security (on-prem, SSO, RBAC). We see UI Bakery as the next evolution beyond drag-and-drop builders — from "fast but limited" to "fast, customizable, and secure." We’d love to hear what the HN crowd thinks: If you’ve used drag-and-drop builders, what’s been your biggest pain scaling or maintaining them? Would you trust AI to generate internal tools that you can later expand like a normal codebase? Try it here: https://uibakery.io

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Actual performance

3points
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, model, apps · Missing: mac, agents, macos
97%97% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
95%95% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: builder · Missing: plus, platform, intuitive
45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: apps, way · Missing: mobile apps, ios, personal
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit
21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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