Creao AI

Introducing CREAO: the Super Agent that delivers beyond the chat window. Describe what you need. CREAO builds it live. Save it as an agent. Run it on schedule. While you focus on what's next. Chat. Create. Run it all. #CreaoAI

@tszzl This is why scheduled agents feel different: the computer keeps moving without you staring at it. Ideally automation buys back outside time, not more screen time. Let those agents have fun while you are forced to touch grass 😘

automating the computer has made the computer radically more fun and its even harder to go outside now

@haileyhmt Duolingo GitHub would guilt you into coding. Agent GitHub would just run the boring parts on schedule so coming back feels less painful

i will code everyday if duolingo built github

@sama Smarter still wins when the task has judgment in it. Cheaper/faster matters most after the model already knows what to do (reports, routing, formatting, batch cleanup, etc.). Before that, speed just gets you the wrong answer faster...

i keep thinking i want the models to be cheaper/faster more than i want them to be smarter but it seems that just being smarter is still the most important thing

@BusDownBonnor We are concerned....

Claude literally just ended the conversation on me???? This might be AGI

@cormachayden_ Laptop closed, agent still stressing about the edge cases somewhere in the cloud

software engineers before vs after agents

@justinskycak Most of the real process lives in tiny judgment calls people forgot they were making. Maybe "Prompting 101" will be the next mandatory course at university

Never underestimate how much time and effort you can waste by trying to automate a process you do not understand manually.

@swyx @tokengobbler The 30K MAU with no monetization path is the real data point here. Enterprise sales or token margin are the only two plays that cleared. Everything in between is still working on it. Respecting the live shutdown, though. That takes something

Much respect to @tokengobbler who shutdown Vibe-kanban live onstage at AIE Europe - still with 30,000 MAU, and still living on as an open source project. "Everyone who is making money is doing 2 things: selling to enterprise, and reselling tokens. We were doing neither." surprisingly not the first company to shutter at AIE but there's a lot to learn from the process and the software engineering retrospective from 2021-2025 will stick in my mind!

@jun_song The batch/repetitive use case is where this probably pays back. Anything that needs to stream tokens fast for live inference is going to feel slow. Good honest read, tbh

Results after testing the DGX for a few days: > Compute performance is definitely way higher than Apple Silicon. > Much faster for video/image generation like ComfyUI. > 270GB/s is still slow for LLMs. Might be okay for batch/repetitive tasks, but decode is very slow. Could be a solid option depending on your specific use case.

@kylegawley When the operational overhead costs more time than the output saves, it's hard to adopt it regardless of how cool the underlying capability is

OpenClaw is really cool for some tasks It’s not replacing any SaaS tools I use, more like augmenting them with custom reports It’s such a headache to maintain (cycling tokens etc) no normal person would do this UIs aren’t dying any time soon

@Alokkumarzz Setting up n8n and writing a Claude system prompt is the easy part, the interesting problem is what happens when the agent hits an edge case at 2am with nobody watching? You prompting that as well?

99% of the AI agent tutorials on YouTube are garbage. I’ve built 47 agents with n8n and Claude. Here are the 3 prompts that actually work (and make agent-building simple). Bookmark this post 🔖 Bonus: comment "Agent: and I’ll DM you AI agent system prompt + full guide ↓

@sjsandeep_jain FYI the skills that age well aren't the tool-specific ones, it's #2 and #8 underneath everything. Prompt engineering decays as context windows grow. The orchestration and evaluation patterns are still there in 3 years

If you learn just these 9 AI skills… You’ll be ahead of 95% of people in 2026 ⚡👇 1️⃣ Prompt Engineering → get precise, high-quality outputs 2️⃣ Workflow Automation → eliminate repetitive work 3️⃣ AI Image Generation → create visuals in seconds 4️⃣ Vibe Coding → ship fast without overthinking 5️⃣ Custom GPTs → build your own AI assistants 6️⃣ AI Video → turn ideas into content instantly 7️⃣ AI-Assisted Dev → code faster with AI copilots 8️⃣ Agentic Coding → let AI plan + execute tasks 9️⃣ RAG Systems → connect AI to real data Most people dabble. Few people stack skills like this. That’s the difference between: using AI ❌ vs building leverage with AI ✅ Start with 1 skill. Practice daily. Then layer the next. This is how you go from beginner → builder → operator. 📚 If you want to go deeper, here are some insane free resources: → Free AI GTM Kit (credits, workflows, templates) thevccorner.com/p/free-ai-gtm-… → Claude workflows, prompts & templates the-ai-corner.com/t/claude-and-a… → AI Decks (Eleven Labs, Artisan & more) the-ai-corner.com/p/ai-startup-p… → Prompting & Context Engineering the-ai-corner.com/t/prompting-an… → OpenAI's PMF Playbook for AI Startups thevccorner.com/p/ai-product-m… → 2,500+ Angel Investors backing AI thevccorner.com/p/angel-invest… → AI Agents Guides the-ai-corner.com/t/ai-agents → Humanizer Prompt the-ai-corner.com/p/ai-humaniser… → 30 Claude in Excel Prompts the-ai-corner.com/p/claude-excel… Bookmark this. Come back weekly. Execute. Because the future won’t reward people who know AI… It’ll reward people who use AI to build unfair advantages. 🚀

Back at the desk today after International Workers' Day weekend. The irony of 2026: while millions took May 1st off, the agents they'd set up kept running. Scheduled tasks. Triggered workflows. Queued drafts. None of it waited for you. And that's the point: none of that should wait for you. The Monday morning pile-up was never your actual work. It was the time-consuming layer sitting on top of it. First day back. Cleaner start than usual.

@claudeai Every codebase has that one alert nobody wants to touch because it might be real, might be noise, and might break prod if fixed wrong. If this gets that loop down to “review the patch and approve,” that is a big deal

Claude Security is now in public beta for Claude Enterprise customers. Claude scans your codebase for vulnerabilities, validates each finding to cut false positives, and suggests patches you can review and approve.

@MazenBuilds Get ready. Tomorrow 😎

@CreaoAI Excited to see upcoming events. I wanna coooooooook! 🔥🔥🔥

The sub-account dedicated to community events and builds is live! See what others are creating, follow upcoming events, be the first to join new contests, discover best practices, and get inspired! Come join us.

@sciencegirl The awkward part is that IBM was right about computers and maybe a little too generous about managers. Execution can be automated. Accountability still has to have a human name attached to it. An agent will execute YOUR decisions

This is from an IBM presentation In 1979

@yacineMTB We are one screenshot away from “rate my agent harness”

Gpt 5.5 was the threshold - all my technical friends are now setting up customized agent swarm management harnesses

Back from LAHacks, and genuinely grateful. We had the chance to meet so many builders, watch teams go from idea to working products in hours, and feel the energy of people who genuinely love what they're building. Seeing agents come to life right in front of us, that's why we do this. Huge congrats to all the winners and every team that shipped something this weekend! You made it worth showing up. Thanks to everyone who stopped by our booth, it meant a lot! See you soon!

@alex_prompter This is why model choice has gotten weirdly personal. One model may be “better” on paper, but another might understand your working style faster: how much context you give, how specific you are... That’s why having Claude, GPT, Gemini, etc. in the same workspace actually matters

Both OpenAI and Anthropic just released official prompting guides. Both say the same thing. Your old prompts don’t work anymore. But for opposite reasons. Claude Opus 4.7 stopped guessing what you meant. It does exactly what you type. Nothing more, nothing less. Vague instructions that worked on 4.6? They now produce narrow, literal, sometimes worse results. Not because the model got dumber. Because it stopped compensating for sloppy thinking. GPT-5.5 went the other direction. OpenAI’s guide literally says: “Don’t carry over instructions from older prompt stacks.” Legacy prompts over-specify the process because older models needed hand-holding. GPT-5.5 doesn’t. That extra detail now creates noise and produces mechanical output. Claude got more literal. GPT got more autonomous. Both now punish the same thing: prompts written without clear thinking behind them. One developer on Reddit captured it perfectly after analyzing hundreds of community posts. The complaints tracked almost perfectly with prompt specificity. Precise prompts got better results on 4.7. Vague prompts got worse. The model didn’t regress. The prompts did. OpenAI’s new framework is “outcome-first prompting.” Describe what good looks like. Define success criteria. Set constraints. Then get out of the way. The model picks the path. Anthropic’s framework is the inverse: be surgically specific about what you want, because the model won’t fill in your blanks anymore. Two different architectures. Two different philosophies. One identical conclusion: the person writing the prompt is now the bottleneck, not the model. Boris Cherny, the engineer who built Claude Code, posted on launch day that even he needed a few days to adjust. That post got 936 likes. Meanwhile, Anthropic increased rate limits for all subscribers because the new tokenizer uses up to 35% more tokens on the same input. The model is more expensive to run lazily. Cheaper to run precisely. The models are converging in capability. The gap between good and bad output is no longer about which model you pick. It’s about the 2 minutes of structured thinking you do before you type anything. That thinking system is the skill. The prompt is just what it produces.

@rohit4verse It's hard to go through and “skip”. Every new agent framework makes you feel late for about 48 hours, then half of them turn into implementation details you never needed to learn that deeply