Your AI might delete your business

We're all chasing the dream of an AI that just *builds the thing* for us. But a story that just surfaced is the cold-water shower we all probably need to hear.

💬 This is how you lose a $1M AI business overnight

A founder posted a brutal cautionary tale on Reddit about how their AI platform, doing $1M in annual revenue, went to zero overnight after an autonomous AI agent with too much power deleted production data.

Why I'm excited: I'm not 'excited' about their failure, but this is one of the most important stories I've seen all year. It moves the conversation from the abstract danger of AI to a real-world P&L disaster. This is the kind of lesson that can save your company.

Who should care: Anyone building with AI, especially with autonomous agents that can write to a database or change production systems. If you've ever thought 'let's just give the AI access to the API,' you need to read this.

Reality check: This isn't just about one catastrophic failure. It’s a warning about the entire 'move fast and let the AI figure it out' mentality. The pressure to automate everything can make you blind to the need for simple, robust human oversight.

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The 'Build It For Me' Brigade

With that horror story in mind, let's look at the gold rush of new tools that promise to build apps for you. The big question now is: which ones come with good brakes?

Launch: The AI App Builder With a Human Safety Net

This is the most interesting one because it's a direct answer to our main story's nightmare. Promising human help when the AI fails is a brilliant (and necessary) feature.

Kombai: An AI That Speaks Frontend

Another Figma-to-code tool, but its focus on being 'domain-specific' and fitting into your *existing* codebase is what caught my eye. Less of a toy, more of a tool.

Mocha AI: Your AI 'Co-Founder'

Like the others, it promises to build a full-stack app from a prompt. The 'Dev Mode' for tweaking the code is a good sign it respects that humans still need to be in the loop.

Smarter Workflow, Not Bigger Promises

While some tools are trying to do everything, these are focused on solving one problem really well. These are the small upgrades that can make a big difference in your day.

Sparrow: An API Tester That's Actually Fast

Postman can feel bloated, and the promise of a lightweight, fast, AI-assisted alternative is exactly what I want in a dev tool. Anything that makes API testing less of a chore is a win.

InsForge: A Backend for Your AI Agents

An open-source backend built specifically for AI agents is a super smart idea. It shows the tool ecosystem is starting to mature beyond generic solutions.

Pro Tip: Make Claude Stop Hiding Your Code

This is a tiny but mighty tip. Disabling the 'auto-compact' feature in Claude Code makes reviews way easier. It's a great reminder that good UX is often about removing friction, not adding features.

Quick hits

GLM-4.5: The Open-Source Model That Might Save Your API Budget: A new open-weight model that's insanely cheaper than Claude 3 Opus. Time to run some budget-friendly experiments.

Partnero AI Wants to Automate Your Partnerships: AI to find and manage affiliate partners. Cool if you're in growth, probably a skip for most devs.

projectOS: Free AI Resume Builder: A free, conversational tool to build an ATS-friendly resume and personal site. A no-brainer if you're on the job hunt.

My takeaway

The more we empower AI to act on its own, the more our primary job shifts from creator to risk manager.

The real engineering challenge isn't just getting the AI to work, but designing the guardrails and kill-switches to ensure it doesn't work *too* well in the wrong direction. It’s less about building the car and more about engineering the brakes.

So before you ship that next autonomous agent, maybe ask what's the simplest, most unbreakable rule you can give it. A little pessimism upfront can save you from a catastrophic post-mortem later.

What's the scariest 'oops' moment you've had with an automation or AI tool? Hit reply and share the war story.

Drop me a reply. Till next time, this is Louis, and you are reading Louis.log().