How was the Universal Pictures 1936 opening logo created?

I know when you're vibe coding

I couldn't submit a PR, so I got hired and fixed it myself

Hey HN! My name is Christian, and I’m the co-founder of <a href="https:&#x2F;&#x2F;frigade.ai">https:&#x2F;&#x2F;frigade.ai</a>. We’ve built an AI agent that automatically learns how to use any web-based product, and in turn guides users directly in the UI, automatically generates documentation, and even takes actions on a user’s behalf. Think of it as Clippy from the old MS Office. But on steroids. And actually helpful.You can see the agent and tool-calling SDK in action here: <a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=UPe0t3A1Vpg" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=UPe0t3A1Vpg</a>How is this different from other AI customer support products?Most AI &quot;copilots&quot; are really just glorified chatbots. They skim your help center and spit out some nonspecific bullet points. Basically some ‘hopes and prayers’ that your users will figure it out. Ultimately, this puts the burden on the user to follow through. And assumes companies are keeping their help center up-to-date with every product change. That means constant screenshots of new product UI or features for accurate instructions.These solutions leverage only a fraction of what’s possible with AI, which can now reason about software interfaces extensively.With Frigade AI, we guide the user directly in the product and build on-demand tours based on the current user’s state and context. The agents can also take actions immediately on a user’s behalf, e.g. inviting a colleague to a workspace or retrieving billing information (via our tool calling SDK).This was only made possible recently. The latest frontier models (GPT 4.1, Claude 4, Gemini 2.5, etc.) are able to reason about UIs and workflows in a way that simply didn’t work just 6 months ago. That’s why we’re so excited to bring this technology to the forefront of complex legacy SaaS applications that are not yet AI enabled.How does it work?1. Invite agent@frigade.ai to your product. You can send multiple invitations based on distinct roles.2. Our agent automatically explores and reasons about your application.3. Attach any existing help center resources or training documentation to supplement the agent’s understanding. Totally optional.4. Install the agent assistant Javascript snippet (just a few lines).5. That’s it. Your users can now start asking questions and get on demand product tours and questions answered in real time without any overhead.This process takes only a few minutes. Once running, you can improve the agent by rating and providing feedback to the responses it provides. If you want to integrate further, you can also hook up your own code to our tool calling SDK to enable the agent to look up customer info, issue refunds, etc. directly. These calls can be made with just a few lines of code by describing the tool and its parameters in natural language and passing a single Javascript promise (e.g. make an API call, call a function in your app, etc.).Would love to hear what the HN crowd thinks about this approach! Are you building your own AI agent from scratch, or looking to embed one off the shelf?

Show HN: An AI agent that learns your product and guides your users

OpenAI's "Study Mode" and the risks of flattery

Hey HN,I tend to use printf-style debugging as my primary troubleshooting method and only resort to gdb as a last resort.While I like its ease of use printf debugging isn&#x27;t without its annoyances, namely removing the print statements once you&#x27;re done.I used to use trace-level logging from proper logging libraries but adding trace calls in every corner quickly gets out of control and results in an overwhelming amount of output.To scratch my own itch I created dlg - a minimal debugging library that disappears completely from production builds.
Its API exposes just a single function, Printf [1].dlg is optimized for performance in debug builds and, most importantly, when compiled without the dlg build tag, all calls are eliminated by the Go linker as if dlg was never imported.For debug builds it adds optional stack trace generation configurable via environment variables or linker flags.GitHub: <a href="https:&#x2F;&#x2F;github.com&#x2F;vvvvv&#x2F;dlg">https:&#x2F;&#x2F;github.com&#x2F;vvvvv&#x2F;dlg</a>Any feedback is much appreciated.[1]: Actually two functions - there&#x27;s also SetOutput.

How was the Universal Pictures 1936 opening logo created?

I know when you're vibe coding

I couldn't submit a PR, so I got hired and fixed it myself

Show HN: An AI agent that learns your product and guides your users

OpenAI's "Study Mode" and the risks of flattery

Show HN: Dlg – Zero-cost printf-style debugging for Go

The Art of Multiprocessor Programming 2nd Edition Book Club

Profiling without Source code – how I diagnosed Trackmania stuttering

ChatGPT users shocked to learn their chats were in Google search results

The Big Oops in Type Systems: This Problem Extends to FP as Well