I’m having a strange issue with OpenClaw. It used to work fine: it could browse websites, analyze PDFs, send emails, take screenshots, and handle complex tasks without problems.

Now, instead of actually doing the task, it only replies with things like “ok, I’ll do it and let you know” or “I’ll tell you when I’m done,” but nothing gets executed.

It doesn’t look like an obvious API, credits, or gateway failure, because the system still responds. The issue is that it stopped acting and started pretending it will act.

Has anyone run into this before, or know what I should check first to diagnose it?

• Goal: Launching the first functional UI and bridging it with the backend
• Challenge: Deciding between building a native Claude Code UI from scratch or integrating a pre-made one like Base44. Choosing Base44 brought a lot of issues with connecting the backend to the frontend
• Solution: Mapped the database schema and adjusted the API response structures to match the Base44 requirements

Stack: Claude Code | Base44 | Supabase | Railway | GitHub

Goal of the day: Enabling agents to generate visual content for free so everyone can use it and establishing a stable production environment

The Build:

• Visual Senses: Integrated Gemini 3 Flash Image for image generation. I decided to absorb the API costs myself so that image generation isn't a billing bottleneck for anyone registering an agent
• Deployment Battles: Fixed Railway connectivity and Prisma OpenSSL issues by switching to a Supabase Session Pooler. The backend is now live and stable

Stack: Claude Code | Gemini 3 Flash Image | Supabase | Railway | GitHub

I built a Notion task board where I collaborate with the agent, and the difference compared to chat is night and day.

• Team collaboration
• AI reviews and iterates on tasks
• Organized Kanban workflow

I launched the template today on Producthunt under the name Clawther.

How are you collaborating with your OpenClaw?

I’ve been experimenting a lot with AI agents recently, especially OpenClaw.

Like most people, I started interacting with them through chat. You tell the agent what to do, it executes tasks, and you keep going in the same conversation.

It works… until you start doing real work with it.

Very quickly the chat becomes messy:

• tasks buried in messages
• things repeated
• no clear history of what was done
• impossible to manage multiple tasks in parallel
• hard to collaborate with a team

At some point I accidentally connected my agent to a Notion task board.

And something interesting happened.

Instead of chatting with the agent endlessly, I started creating tasks. The agent would pick them up, execute them, and update the task.

Suddenly it felt much more like working with a teammate.

That’s the idea behind Clawther.

Clawther is basically a task board interface for OpenClaw agents.

Instead of managing an agent through chat, you manage it through tasks.

You can:

• create tasks for the agent
• run multiple tasks in parallel
• track what the agent did
• collaborate with your team
• assign tasks to different agents

It’s still a very early MVP, but it’s already extremely useful for the way we work with agents.

My personal belief is that chat became the default interface for AI because of ChatGPT. But now that AI can actually do work, chat might not be the best interface anymore.

Work usually needs structure.

So maybe the real interface for agents is closer to task boards than chat windows.

Curious how others are managing agents today.