AI agents are becoming a regulatory problem

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351→ 400 Only 49 more. I’ve done my part for today 🥹 Al/ML, SaaS, Data Science,Coders,Developers,Founders,Startups. Let’s join 🤝 The ship is in your hands now. 🫡

Hot take: most companies don't have an AI problem. they have a workflow problem disguised as an AI problem.

These “humanoid robots” look like they were assembled from a $49 AliExpress kit and a prayer. Every time one tips over, a guy in a black shirt rushes in like he’s the pit crew at a remote-control toy race. Skill issue? Or just cheap hardware?

Google is giving Argon to cyber defenders first so they can find and patch the holes before the rest of us get it. That’s a different playbook. 👏🏻

Argon is so good at cybersecurity they won’t even let regular developers touch it yet. The model is currently in witness protection.

Finally, some peace. 😭 @X Analytics is back. We spent way too much time refreshing the page, hoping the numbers would finally appear. They’re back.

A query takes 8 seconds. You add an index. Now it takes 800 ms. Users still say the application feels slow. What did you actually optimize?

People on X choose who they follow and what they like for a reason. We need to earn their attention, trust, and engagement by consistently providing content that adds real value.

Mutuals, let’s actually help each other out 🤝 If you see someone from this list in your timeline, give them a follow, say hi, or support their work when you can. Frontend • Backend • Full-stack • DevOps • AI/ML • Data • SaaS • Startups • Building in public Let’s make this network useful, not just another follower count.

Why do we evaluate AI agents mostly on successful tasks instead of the quality of the decisions they make along the way?

We measure models by benchmarks designed by humans. How much intelligence are those benchmarks actually capable of measuring?

The hard part of an “always-on” AI agent isn’t keeping it running. It’s knowing when to stop. OpenAI’s new Dots can work across 4,000+ apps and continue tasks in the background. But that creates a much harder problem: What happens when the agent makes a wrong assumption at 2 AM? The next generation of agents won’t just need: → better models → more tools → more autonomy They’ll need better boundaries.

I don’t pay for tokens. I pay for not having to babysit the last 10%. Most tools still sell me the babysitting.

Why would I give an AI permission to keep working after I’ve left the conversation?

Model releases are getting so frequent that the durable advantage may shift from choosing a model to switching models quickly.

The next SaaS competitor might not be another SaaS company. It might be an AI agent that completes the workflow directly.

the AI market is quietly moving from: tokens → tasks bcoz nobody ultimately wants 1 million tokens. They want the job finished

Which platform is most effective for consistently acquiring paying customers: @X , @LinkedIn , or @Reddit ?