
The AI Bottleneck Is Permission, Not Intelligence
Frontier AI is becoming a permissioned market. Mythos 5 and GPT-5.6 show why access, risk tiers, and approvals now matter…
Hey HN! My name is Christian, and I’m the co-founder of <a href="https://frigade.ai">https://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.<p>You can see the agent and tool-calling SDK in action here: <a href="https://www.youtube.com/watch?v=UPe0t3A1Vpg" rel="nofollow">https://www.youtube.com/watch?v=UPe0t3A1Vpg</a><p>How is this different from other AI customer support products?<p>Most AI "copilots" 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.<p>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).<p>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.<p>How does it work?<p>1. Invite [email protected] to your product. You can send multiple invitations based on distinct roles.<p>2. Our agent automatically explores and reasons about your application.<p>3. Attach any existing help center resources or training documentation to supplement the agent’s understanding. Totally optional.<p>4. Install the agent assistant Javascript snippet (just a few lines).<p>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.<p>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.).<p>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?
Reader rating
No ratings yet
You might also like
Ollama is a local AI platform for running, managing, and sharing open models on your own machine or private infrastructure. It makes it easy to pull models, serve them through an API, and integrate local inference into developer workflows without relying on a fully managed cloud stack. Teams use Ollama for privacy-sensitive assistants, internal tools, offline experimentation, and rapid testing of open-weight models across laptops, workstations, and servers. It is especially useful for developers, operators, and AI builders who want quick setup with less operational overhead. What makes Ollama distinctive is how approachable it is: it packages model runtime, distribution, and deployment into a streamlined experience that helps people get productive with local AI in minutes instead of spending days on configuration.
OpenAgentd is a self-hosted AI-agent OS that runs entirely on the user’s machine. It provides a web cockpit, streaming chat, persistent editable memory, tool use, workspace file browsing, image viewing, local voice transcription, scheduling and multi-agent teams with lead-worker delegation. Agents can read and write files, run shell commands, search the web, generate media, manage todos and extend capabilities via skills or MCP servers. The tool is for users who want a local, inspectable alternative to cloud-only agent workspaces. It is notable now because privacy, long-running autonomy and multi-agent coordination are converging into desktop systems rather than isolated chat tabs.
Together AI is an AI inference and training cloud platform that provides fast, cost-effective access to open-weight models. It offers fine-tuning, inference endpoints, and a startup program for early-stage companies building on open AI. Targeted at developers and startups who want an alternative to proprietary model APIs with transparent pricing and open-model support.
From the blog

Frontier AI is becoming a permissioned market. Mythos 5 and GPT-5.6 show why access, risk tiers, and approvals now matter…

AI agents are moving into real workflows. The next useful layer is approvals, logs, limits, and better checks before autonomy gets trusted…

Companies still want AI, but the honeymoon budget is ending. The next phase rewards workflows that prove value instead of burning tokens…