AI agents are the next frontier. Unlike chatbots that just respond, AI agents reason through problems, take action, and complete complex workflows without constant oversight. They're fundamentally changing how work gets done.
We built KickAaaS AI because most businesses don't have time to evaluate hundreds of tools launching every week. We vet every agent for reliability and real-world performance, then curate only what's proven to work.
The result is a marketplace where you can find solutions you can trust without drowning in noise. Follow along for implementation frameworks, strategic insights on which agents solve which problems, and practical guidance on AI strategy
"Is OpenClaw safe?" is the wrong question.
The right question: what have you given it access to?
We broke down the CVE, what's fixed, and the 5 things you need to verify before trusting it with anything sensitive.
Read more here: https://t.co/Es4AKFbWC1
The best AI agents for sales teams right now:
• Aomni → pre-call research at scale
• @getaisdr → outbound on autopilot
• @tryqualified → converts inbound 24/7
• Clay → enriches every lead automatically
Full breakdown on the KickAaaS blog →
https://t.co/GyC8mgdiJd
Running AI agents at scale has a math problem.
GPT-4o: $2.50/M tokens. At volume, that adds up fast.
Google just released Gemma 4 — open source, Apache 2.0, built for agentic workflows.
The marginal cost of the 10,000th conversation: $0.
Full breakdown: https://t.co/F5R5xH5opl
@Google just dropped an open-source model that:
• Beats models 20x its size
• Runs FREE on your machine
• Was built for agentic workflows
This changes what's possible for AI agents.
If you have a mac mini or other dedicated hardware for AI, give this a go.
The agent economy isn't coming. It's here.
Meet Gemma 4: our new family of open models you can run on your own hardware.
Built for advanced reasoning and agentic workflows, we’re releasing them under an Apache 2.0 license. Here’s what’s new 🧵
Running your own AI agent costs $0/month in API fees. The hardware pays for itself in under a year.
We broke down the honest math, the right hardware for your actual use case, and which local models are worth running in 2026.
https://t.co/r3QP8byC8b
You're not paying for AI. You're renting it.
Every workflow you run through a cloud API is a recurring bill. This is what running local models on dedicated hardware looks like.
While it feels hard to justify a $600+ purchase of a mac mini or even more advanced hardware, it can end up paying for itself -- quickly.
If you're running OpenClaw in production: check your gateway config, test your skill installs, and re-approve node command pairing before you touch the update button.
Full breakdown here: https://t.co/MAJvNMyjwI
@openclaw just shipped its biggest update in months.
> Security got serious
> background tasks finally make sense
> Slack teams got a big quality of life win
Here is what you need to know 🧵
@SlackHQ teams: you can now approve agent exec actions directly in Slack.
No terminal, no web UI, no context switching.
Just approve and move on.
Small change, big daily improvement.
“Claude Code now works from your phone.”
That’s the update most people missed.
Now it can:
→ receive Telegram instructions
→ run Discord-based workflows
→ schedule recurring automation
→ organize context using Projects
→ run with 1M token Opus memory
Your AI just became mobile.
Save this video, you’ll automate tasks from anywhere.
Want the SOP? DM me. 💬