zz5759

6 か月前議論

My personal site: https://dreamlux.ai — I’m building Dreamlux, an AI video generator / studio. It focuses on fast template-based creation (short clips, social formats) with a simple credit system. Would love feedback on UX/performance and what workflows you’d expect from a personal/indie-built tool.

zz5759

6 か月前議論

https://yesornoai.com

  A collection of free decision-making tools I built:                                             
  - Decision Wheel (customizable spinning wheel)                                                  
  - Coin Flip (yes/no decisions)                                                                  
  - Tarot Reading (with AI interpretations)                                                       
  - Magic 8 Ball                                                                                  
                                                                                                  
  Features: AI-powered result analysis (OpenAI), 10 languages, dark/light themes, mobile          
  responsive.                                                                                     
                                                                                                  
  Tech: Next.js 15, TypeScript, Tailwind CSS, Supabase.

zz5759

6 か月前議論

Maker here. Built this over 8 months after getting frustrated with watermarks on every "free" AI video tool.

Core idea: text or image in, video out, no watermarks even on free tier.

Direct links: - https://dreamlux.ai/image-to-video (animate any image) - https://dreamlux.ai/text-to-video (describe what you want)

Still working on longer video support and better human face generation. Feedback welcome – especially on output quality and whether the UI makes sense.

zz5759

6 か月前議論

I run a small team building Dreamlux.ai (AI video generation). AI changed my day-to-day in a few concrete ways:

Coding: I write less boilerplate and more “integration glue”. LLMs are great for scaffolding (Next.js routes, workers, SQL migrations) and translating logs/errors into hypotheses. Biggest win is speed from idea → working PR, not perfect code.

Debugging/ops: I paste real production symptoms (headers, cache status, curl repros, traces) and ask for ranked root-cause candidates + experiments. This reduced “blind poking” a lot, especially around CDN caching rules, 429s, image optimization, and edge-case billing/credits.

Planning/reviews: We now require “AI-assisted PR reviews” to include: risk list, test plan, rollback steps, and what metrics should move. It’s basically a checklist generator + reviewer #2. Humans still make the call.

What stuck: ChatGPT + a copilot in editor for daily work; LLM as a “rubber duck” for incident triage and for turning messy notes into specs.

What felt like hype: autonomous agents that “own” features end-to-end. Without tight scopes, they wander; with tight scopes, they’re just faster scripts. The sweet spot is human-led, AI-accelerated loops.

Curious: for managers, what’s your best process change that AI enabled (not just “wrote code faster”)?

zz5759

6 か月前議論

I’m building Dreamlux.ai, a lightweight AI video maker for creators who want quick results without a steep learning curve. The focus is: pick a template, drop in text/images, generate a short video in minutes. Currently optimizing reliability (credits/accounting edge cases, caching, performance). If you’re a heavy user of AI video tools, what’s the #1 workflow pain you still have? https://dreamlux.ai

zz5759

6 か月前議論

This doesn’t surprise me too much. Ad preview pipelines are often very different from core content moderation systems.

Especially for thumbnails, there’s usually a mix of heuristics, delayed review, and tolerance for false negatives to avoid blocking legitimate ads. The edge cases tend to leak through first.

zz5759

6 か月前議論

I’d frame this less as “decoupling from the US” and more as general risk diversification.

Single-vendor and single-jurisdiction dependencies are fragile regardless of politics. Designing systems that can move providers, jurisdictions, or currencies with limited friction seems like the only practical approach.

zz5759

6 か月前議論

This is interesting, but it also feels like one of those areas where guardrails matter more than raw automation.

How do you handle things like partial failures, rollback strategies, or environment-specific checks before merging to prod?

zz5759

6 か月前議論

I’m not convinced CAPTCHA is the right long-term solution anymore.

Most low-effort bots can already bypass basic CAPTCHA, while it mostly adds friction for legitimate users. HN’s strength is the quality of discussion, and that seems better protected by behavior-based signals (account age, posting patterns, community feedback) rather than one-time verification challenges.

zz5759

6 か月前議論

I learned that “vibe coding” works surprisingly well if you bias hard toward shipping. That approach helped me build and launch https://dreamlux.ai much faster than if I’d waited for a “perfect” plan.

zz5759

6 か月前議論

I’m currently building a fairly complex AI product this way, and the pattern has been the same: vibe-coding accelerates early progress dramatically, but production reliability only comes back once you re-introduce traditional engineering discipline.

zz5759

6 か月前議論

zz5759

6 か月前議論

I’m working on Dreamlux, an AI tool that helps creators generate short videos from text or images.

The goal is to make it easy to create social and marketing videos without video editing skills.

We’re currently experimenting with different generation styles and workflows, and would love feedback from builders here.

Website: https://dreamlux.ai

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Show HN: Dreamlux – Free AI video generator with no watermarks │

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