Creao AI

The Agent App Era — Reusability Want workflows that compound instead of resetting? You need reusable agents. In CREAO 2.0, a successful run becomes an Agent App. Save it. Rerun it. Refine it. Scale it. Prompts were experiments. Agents are assets.

CREAO X Campaign is Live! We made it stupid simple: 2 tasks to enter. → Follow @CreaoAI → Like, RT & comment Once you’re in, turn it into a game: Invite people → climb the leaderboard → earn more from the $500 pool Join here: community.creao.ai/?ref=CX67GAZ2 ⚠️ Unlocks at 500 participants ⏳ 7 days only — Ends March 25 (11:59PM UTC) The biggest referrers win big. Who’s in?

A customer success manager was drowning in triage decisions. Every morning: 30+ support tickets waiting. Each one required the same assessment: - Check customer tier - Identify issue type - Route to the right team - Set priority level - Update the tracker Five decisions per ticket. 30 tickets. 150 micro-decisions before doing any actual customer work. She described the logic to a CREAO agent: "When a ticket arrives, check the customer's plan in our CRM. If enterprise, create high-priority task and notify the leads team. If standard, route to general support. Log everything in the tracker." Now the agent handles triage. She reviews the priority cases and focuses on solving problems, not sorting them. Same customers. Better outcomes. Because her decision-making energy goes to the conversations that matter, not the routing logic that doesn't.

Today at 10AM PST · 6PM UTC we launch a new series: Agent Showcase. What happens when AI starts interacting with other AI? Can agents actually push each other to produce better outputs? When agents respond to other agents instead of just humans, something interesting happens: • strategies evolve
• reasoning becomes iterative
• outputs improve across turns So we decided to run a small experiment. ⚔️ AI One-Up Battle Two CREAO agents.
One prompt. Each agent must outdo the previous answer: smarter, more creative, or more useful. Round after round, the responses evolve. The audience votes for the winner. It’s simple, but it reveals a lot about how agents behave when they interact instead of just responding to humans. Join the arena, live on Discord👇
discord.gg/creao-ai

CREAO is for operators who: ❌ Don't want to learn to code ❌ Are tired of juggling between tens of platforms ✅ Want to automate repetitive work ✅ Work across multiple tools that don't connect ✅ Do the same tasks over and over ✅ Can clearly describe their process If you've ever thought "I wish someone else could do this," that's what CREAO agents are for. You're the "someone else." Using an AI agent. And you just describe what you need done.

Real talk: Only 17% of workers trust AI to run reliably without human oversight. The rest need that human safety net for confidence. Yet teams are already seeing massive gains by using AI and keeping humans in the loop on decision workflows. See how one support team used decision workflows to cut response times by over 40% while keeping humans in the loop. They integrated AI to prep responses, sort/prioritize tickets, and suggest drafts/actions. But every medium/high-stakes reply required human review and final approval. Result? Response times dropped from hours to minutes in many cases, ticket volume handled rose without adding headcount, and customer satisfaction held steady or improved. No full handover. Just smarter prep + human judgment = faster, better outcomes. This hybrid approach is where the wins are happening now: AI handles the routine grind, humans own the critical calls.

Here are 3 proven ways to start small, build trust, and gradually give AI more responsibility: 1. Start with low-stakes prep tasks Let AI handle inbox sorting, draft responses, summarize reports, or flag priorities. Humans review/approve everything. Zero risk, fast wins → builds confidence fast. 2. Add human oversight gates Set clear thresholds: AI suggests next actions or drafts decisions, but requires human 'final click' for anything medium/high-stakes. As accuracy proves reliable (track metrics!), raise the bar: delegate more routine calls while keeping strategic ones human-led. 3. Scale gradually with proven feedback loops Pilot on one workflow → measure real results (time saved, errors down, team satisfaction up) → refine prompts & rules → expand slowly. Trust comes from data, not declarations. Many teams go from "AI assists" to "AI handles 80% routine" in just months this way. This isn't about handing over the reins. It’s about freeing humans for higher-value thinking while keeping accountability intact. Which step are you on right now? We’re currently moving toward #3 😎

CREAO Workshop — Inside CREAO: A First Look at the New Agent Engine Something new is coming to CREAO. This Thursday’s workshop (12PM UTC) will be a live preview of the testing version of our next-generation agent workflow. @Sonofpeace0001 and @Mr_Hy4 will walk through: • What the new environment looks like • How it differs from today’s Agent Apps • What it unlocks for builders This will be a behind-the-scenes session showing where the platform is heading. If you're curious about the next evolution of CREAO, come take a look inside. Join us live on Discord 👇 discord.gg/creao-ai

At CREAO, our tools empower exactly that: smart prep without overstep. But if you want AI to go even further and automate your entire workflow, we have the tools to leave that decision to you.

Yesterday we talked about automation shifting toward decision workflows. Scary thought: Does that mean AI is about to take our decisions away from us entirely? Not quite. The real pattern emerging: AI prepares decisions (drafts, suggestions, sorted inboxes, even predicted next steps), yet organizations still rely on human-led final calls 71% of the time. People want AI as co-pilot, not autopilot. Most operators prefer the final click to stay human. That’s the philosophy behind many modern agent systems: They prepare the work, delegate the routine, but keep humans firmly in control for higher-valued work. Higher-valued decision-making. The result? Not less power for you. More freedom. More time to listen, think, innovate, collaborate, outcompete, and scale. Not so much "look what AI can do," but "look what YOU can do now — with AI handling the boring prep."

Automation used to be simple: connect tools and let workflows run. When X happens → trigger Y. But now? It's evolving into something smarter: From task workflows to decision workflows powered by AI. Systems that anticipate and decide what should happen next. Think about it. Your inbox sorts itself, drafts responses, and suggests priorities. Efficiency skyrockets, but it raises questions... what decisions are we handing over? What should we delegate?

Dipesh didn’t build this with complex engineering. “I used Claude to explore the idea, pasted one prompt into CREAO, and after ~16 iterations it worked.” From idea to a working marketing system in minutes. 🎥 Watch the full demos on YouTube Shorts: youtube.com/shorts/MnwP8-K…

The result? Your content strategy becomes data-driven and adaptive. The system can: • analyzes your past performance • checks competitor strategies • finds trending topics • ranks ideas by trend score • generate SEO-optimized posts • suggests optimal posting times Content marketing. But agentic.

Which content creator doesn’t wonder: What’s trending? What competitors are doing? What content will actually perform? So you end up guessing. @29Dipesh built his Agent App, Command Center, to fix that. Welcome to our 4th Campaign Winner Deep Dive. Command Center is an AI system that watches creators, tracks trends, and turns signals into ready-to-publish content ideas. The idea came from Dipesh’s own struggle: “I had a really messed-up schedule. I didn’t know when to post… what was happening in the market… or what kind of content I should be posting.”

Scheduling an agent in CREAO takes less than a minute. 1. Open your Agent App 2. Go to Schedule 3. Choose: schedule name, timezone, frequency, and execution time Then click Create Schedule. You can also create a schedule directly when adding New Tasks inside an agent. Now your agent runs automatically.

One of the biggest problems when building AI agents: You build something cool… but it only runs when you trigger it. Real agents should run continuously: • checking emails every 30 minutes • scanning new data daily • triggering follow-ups automatically Without scheduling, autonomy breaks. That’s why we built a scheduler into CREAO.

Because in the Agent App era, execution isn’t enough. Performance matters. With decision intelligence, every action logs: • the model’s reasoning • its confidence score • the market context • the outcome Over time, this creates a dataset that answers a powerful question: Which AI actually performs best in real scenarios? And the best part? H built this with zero lines of code. Watch the interview on YouTube ↓ youtube.com/shorts/kFhdLJ7…

What makes this workspace interesting isn’t just the trading. It’s the capacity to understand the reasoning behind each model. What happens when multiple AIs face the same problem? They don’t behave the same way. Some models are aggressive. Some wait. Some skip entirely. Different models. Different strategies. Different outcomes. Instead of a black box answer, you can observe AI decision-making in real time. From static model comparisons to continuous, live evaluation inside CREAO Agent Apps.

Who hasn’t wondered: Which AI model is actually best for what I need? Welcome to our 3rd Campaign Winner Deep Dive. Meet @Mr_Hy4, winner of our Agentic Visionaries Campaign: “I’ve always been fascinated by evaluating AI models.” So he built an AI arena where models compete on real financial markets and explain their reasoning.