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Models improve where data flows. ⬟ The Playground lets builders share prompts, datasets, and execution tips. Reusable prompt sets. Community-tested configurations. Build once. Share signal.

Nesa

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23,332 Aufrufe • vor 7 Monaten •via X (Twitter)

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Save these drills to improve your ball control and overall handle 💯 Once you get the hang of it— do 3 sets of 1 minute each 🔥 Share this with your trainer or coach/ trainer and try it in your next workout 👊

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Start to explore 3rd person shooting game simulation by using Minimax H3. Here is what I have found: 01. A lot of fun. 02. Comparing to other models, H3 has a better understanding of the game mechanic. - Great 03. Be careful with prompt "QTE". Many models would treat QTE section as a CG scene. I think that is because of the training data. - Great 04. Prompt fine tuning needed. I began with my own prompts with many challengeable elements: QTE, 3rd person camera movement, high kick and execution kill. In the end, I used ChatGPT to refine the prompts by describing the fight scene as a more sequential, step-by-step progression. -Good PS: the character in this demo is XiXi ( from Error My Love ) Will share more examples later. Great work MiniMax Design (H3)

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Jim HuiHui

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I know a lot of people hate on AI. I get it. Be creative. But for those of use who can't draw or animate, this is more of a quick and cheap fix. and there's nothing wrong with that. I wish others were more open about sharing what they've learned using AI and not hoard their knowledge like it's worth gold. The only way we can learn and improve is if others share what they've learned. I understand people are protective of what prompts they use. Ok fine, don't share them. But you can't even give a tip? Like "add this phrase to the prompt for better [fill in the blank]" or "use [blank] for a more realistic atmosphere]. Just pisses me off. I'm happy to share all I've learned with anyone who askes. Same happened in the 3d printing community with crushable printed houses. No one wanted to share anything. So I gave up on that. #sizetwitter #giantess #AIart #giantessai #Sora2 #soraArt

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Carly {Amazingly Unavoidable}

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Donut and Devotions. Every other Thursday I meet with the guys during lunch. I open up the shed/meeting room and try to create a quiet space where they can relax, take a deep breath and reflect on what is good. We share where we are feeling unrest in our lives. We read from the wisdom found Proverbs and then we spend time in prayer. Afterwards the kids have access to the field to throw and hangout together. It’s the highlight of my week. Connect and build community. That’s the business we are in.

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❔ A Question for Our Community 👇 Would you rather build a trading strategy yourself or refine one suggested by AI? 🤖 Strategy creation always starts with an idea. The real work begins later: shaping the logic, adjusting parameters, defining risk, and deciding whether the setup is worth going live. AI can speed up the starting point. Backtesting shows whether the idea actually holds up. 💡 Want to test both paths before execution? Backtest your ideas here 👉 💬 Share how you usually approach strategy building.

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Kōda

69,388 Aufrufe • vor 3 Monaten

While building SEV0, I ran into moments where natural language prompting just wasn't enough - too vague, too indirect. So I started using a method that bridges that gap. I call it Bridged Prompting - a technique where you temporarily step out of the prompt-response loop to manipulate something directly using an AI-generated UI, then step back in. Think of it like GenUI, but more user-driven and transient. AI generates a UI on-the-fly, tailored to your prompt, and lets you manipulate the artifact directly before resuming the conversation. Sure, you could build a full tool, switch tabs, wire it up and round-trip your data. But with Bridged Prompting, the AI just spins up a temporary interface right in the flow. In the video below, I used it to construct the hallway system to closely match the layout of the severed floor. This is something I needed to do for this one project, this one time - I didn't need to make a whole separate app. Bridged Prompting lets you: - Make precise edits visually or structurally - "Hit save" to persist changes to local storage or a backend - Return to your natural language prompt

While building SEV0, I ran into moments where natural language prompting just wasn't enough - too vague, too indirect. So I started using a method that bridges that gap. I call it Bridged Prompting - a technique where you temporarily step out of the prompt-response loop to manipulate something directly using an AI-generated UI, then step back in. Think of it like GenUI, but more user-driven and transient. AI generates a UI on-the-fly, tailored to your prompt, and lets you manipulate the artifact directly before resuming the conversation. Sure, you could build a full tool, switch tabs, wire it up and round-trip your data. But with Bridged Prompting, the AI just spins up a temporary interface right in the flow. In the video below, I used it to construct the hallway system to closely match the layout of the severed floor. This is something I needed to do for this one project, this one time - I didn't need to make a whole separate app. Bridged Prompting lets you: - Make precise edits visually or structurally - "Hit save" to persist changes to local storage or a backend - Return to your natural language prompt

Chris Tate

42,558 Aufrufe • vor 1 Jahr

I just built a Claude Cowork skill that turns your Google Ads data into a visual performance dashboard in 60 seconds 🤯 One prompt → campaign breakdowns, CPA trends, spend vs conversions charts, and hourly conversion patterns, all rendered as an interactive HTML dashboard you open in Chrome. All inside Claude Cowork. Perfect for DTC brands and agencies who are pulling Google Ads data into spreadsheets every week, manually building charts, and spending an hour formatting a report that's outdated by the time you send it. If you're managing Google Ads and your weekly reporting workflow looks like this — export a CSV, open Google Sheets, build a pivot table, copy the numbers into a slide deck, manually create charts, format everything, realize you forgot a campaign, start over ... This skill does the whole thing in one prompt: → Connects to your live Google Ads data via MCP → Pulls spend, conversions, CPA, ROAS, CTR across every campaign → Builds an interactive HTML dashboard → Summary cards at the top: total spend, total conversions, avg CPA, avg ROAS → Bar chart comparing spend vs conversions by campaign → CPA trend line over the last 30 days → Campaign table ranked by performance, color-coded green/yellow/red → Opens in Chrome: hover over charts, compare campaigns, screenshot for your team No spreadsheets. No manual chart building. No hour-long formatting sessions. What you get: → A visual dashboard from live data in under 60 seconds → Campaign performance you can actually see, not just read in a table → CPA trends that show you where things are heading, not just where they are → A dashboard you can screenshot and drop into Slack, a client report, or a team standup → Reusable — run it weekly and the data updates automatically One prompt. Live data. A finished dashboard you open in your browser. I put together a playbook with the full skill file, the setup, and the exact prompts to customize the dashboard for your account. Want it for free? > Like this post > Comment "DASH" And I'll send it over (must be following so I can DM)

I just built a Claude Cowork skill that turns your Google Ads data into a visual performance dashboard in 60 seconds 🤯 One prompt → campaign breakdowns, CPA trends, spend vs conversions charts, and hourly conversion patterns, all rendered as an interactive HTML dashboard you open in Chrome. All inside Claude Cowork. Perfect for DTC brands and agencies who are pulling Google Ads data into spreadsheets every week, manually building charts, and spending an hour formatting a report that's outdated by the time you send it. If you're managing Google Ads and your weekly reporting workflow looks like this — export a CSV, open Google Sheets, build a pivot table, copy the numbers into a slide deck, manually create charts, format everything, realize you forgot a campaign, start over ... This skill does the whole thing in one prompt: → Connects to your live Google Ads data via MCP → Pulls spend, conversions, CPA, ROAS, CTR across every campaign → Builds an interactive HTML dashboard → Summary cards at the top: total spend, total conversions, avg CPA, avg ROAS → Bar chart comparing spend vs conversions by campaign → CPA trend line over the last 30 days → Campaign table ranked by performance, color-coded green/yellow/red → Opens in Chrome: hover over charts, compare campaigns, screenshot for your team No spreadsheets. No manual chart building. No hour-long formatting sessions. What you get: → A visual dashboard from live data in under 60 seconds → Campaign performance you can actually see, not just read in a table → CPA trends that show you where things are heading, not just where they are → A dashboard you can screenshot and drop into Slack, a client report, or a team standup → Reusable — run it weekly and the data updates automatically One prompt. Live data. A finished dashboard you open in your browser. I put together a playbook with the full skill file, the setup, and the exact prompts to customize the dashboard for your account. Want it for free? > Like this post > Comment "DASH" And I'll send it over (must be following so I can DM)

Mike Futia

38,846 Aufrufe • vor 4 Monaten

If you’ve been wanting to experiment with #generativeAI, check out PartyRock powered by Amazon Bedrock. With PartyRock, anyone can learn about prompt engineering/writing and build apps in just a few clicks. I built one to find the best bike trails in the Seattle area based on time of year, and best time to go to avoid crowds. You can build an app to create the perfect playlist based on your musical tastes, or one to recommend what to cook based on ingredients in your pantry. The list goes on. PartyRock is an easy and fun way to learn the fundamentals of foundation models and then collaborate with other developers. Anyone can access PartyRock through the website, and you don’t need an Amazon Web Services account. Share your PartyRock apps in the comments below!

If you’ve been wanting to experiment with #generativeAI, check out PartyRock powered by Amazon Bedrock. With PartyRock, anyone can learn about prompt engineering/writing and build apps in just a few clicks. I built one to find the best bike trails in the Seattle area based on time of year, and best time to go to avoid crowds. You can build an app to create the perfect playlist based on your musical tastes, or one to recommend what to cook based on ingredients in your pantry. The list goes on. PartyRock is an easy and fun way to learn the fundamentals of foundation models and then collaborate with other developers. Anyone can access PartyRock through the website, and you don’t need an Amazon Web Services account. Share your PartyRock apps in the comments below!

Adam Selipsky

86,425 Aufrufe • vor 2 Jahren