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Less prompt, more engineering. Working on a thing.

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Kit Langton

19,467 subscribers

38,097 просмотров • 1 месяц назад •via X (Twitter)

ОбразованиеНаука и технологии
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*been working on a thing voice* So I’ve been working on a thing…the return of a character…more to come…
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*been working on a thing voice* So I’ve been working on a thing…the return of a character…more to come…

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This thing is a marvel in modern engineering! I can't imagine actually living and working on it though! 😬
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This thing is a marvel in modern engineering! I can't imagine actually living and working on it though! 😬

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RIP Prompting. Higgsfield’s new platform with Soul and Minimax has made prompt engineering a thing of the past. Here’s the breakdown:
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RIP Prompting. Higgsfield’s new platform with Soul and Minimax has made prompt engineering a thing of the past. Here’s the breakdown:

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.Andrew Mayne on: - creating the prompt engineering discipline - his journey from the circus to OpenAI (not a joke) - hitting the wall on AI progress - prompt engineering v2 - GPT-3 > GPT-5 ? - AI saving him from a shark Episode available at links below. Enjoy!
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.Andrew Mayne on: - creating the prompt engineering discipline - his journey from the circus to OpenAI (not a joke) - hitting the wall on AI progress - prompt engineering v2 - GPT-3 > GPT-5 ? - AI saving him from a shark Episode available at links below. Enjoy!

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🎨 Introducing Prompt Canvas — a novel UX for prompt engineering Building LLM applications requires new and dedicated tools for prompt engineering. With Prompt Canvas in LangSmith, you can: • Collaborate with an AI agent to draft, refine, and edit your prompts • Define custom quick actions to standardize prompting strategies used across the org ✍️ Learn more: ➡️ Try it out:
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🎨 Introducing Prompt Canvas — a novel UX for prompt engineering Building LLM applications requires new and dedicated tools for prompt engineering. With Prompt Canvas in LangSmith, you can: • Collaborate with an AI agent to draft, refine, and edit your prompts • Define custom quick actions to standardize prompting strategies used across the org ✍️ Learn more: ➡️ Try it out:

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“More or less the same thing…” 📺
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Nelly;

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I had a great time chatting with three of Anthropic's top prompt engineers: Amanda Askell, Zack Witten, and David Hershey. We covered a few topics like: - what makes a good prompt engineer - practical tips for writing better prompts - what's happening inside an LLM - jailbreaks - the future of prompt engineering - and more If you want to understand how we think about prompt engineering, this may be the best resource out there. Here's the entire one hour and sixteen minutes of our conversation. Enjoy!
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I had a great time chatting with three of Anthropic's top prompt engineers: Amanda Askell, Zack Witten, and David Hershey. We covered a few topics like: - what makes a good prompt engineer - practical tips for writing better prompts - what's happening inside an LLM - jailbreaks - the future of prompt engineering - and more If you want to understand how we think about prompt engineering, this may be the best resource out there. Here's the entire one hour and sixteen minutes of our conversation. Enjoy!

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This is a research preview. It requires more prompt engineering than previous models - but the generations are breathtaking. We’ll continue fine-tuning to improve reliability and control.
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Trump and his billionaire buddies are engineering a financial crisis to transfer even more wealth from working class Americans to themselves
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In this week’s Stability Seconds, we’re showing you how to use prompt weighting, a technique that helps you control which parts of your prompt have more or less influence on the final image. It’s a fast way to steer your image toward your desired output without rewriting your prompt. Here’s how to do it: 1️⃣ Emphasize elements: Put parentheses around the part of your prompt you want to focus on, then add a colon and a number. For example, (trench coat:1.5) tells the model to emphasize the trench coat. The higher the number, the more it stands out. 2️⃣ De-emphasize elements: Put parentheses around the part of your prompt you want to make less prominent, then add a colon and a number below one. For example, (background:0.5). The lower the number, the less it stands out. You can try prompt weighting with Stable Image Ultra here 👉
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In this week’s Stability Seconds, we’re showing you how to use prompt weighting, a technique that helps you control which parts of your prompt have more or less influence on the final image. It’s a fast way to steer your image toward your desired output without rewriting your prompt. Here’s how to do it: 1️⃣ Emphasize elements: Put parentheses around the part of your prompt you want to focus on, then add a colon and a number. For example, (trench coat:1.5) tells the model to emphasize the trench coat. The higher the number, the more it stands out. 2️⃣ De-emphasize elements: Put parentheses around the part of your prompt you want to make less prominent, then add a colon and a number below one. For example, (background:0.5). The lower the number, the less it stands out. You can try prompt weighting with Stable Image Ultra here 👉

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13,818 просмотров • 11 месяцев назад

Prompt engineering is hard. That's why we've been adding tons of features to the Anthropic Console to make the entire process easier for devs. Our goal is to cut the time you spend working on prompts by >90%. Here's a quick walkthrough:
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Prompt engineering is hard. That's why we've been adding tons of features to the Anthropic Console to make the entire process easier for devs. Our goal is to cut the time you spend working on prompts by >90%. Here's a quick walkthrough:

Alex Albert

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George Stoia III

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Most AI demos start with a prompt. I started with an entire startup. I gave MiniMax M3: • product docs • pricing • customer feedback • roadmap • competitor research Then dropped everything into Cursor and asked it to build the product. What impressed me wasn't the code. It was how well M3 connected information across all the documents and turned them into actual product decisions. Feels less like "AI coding" and more like working with a junior product + engineering team.
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Most AI demos start with a prompt. I started with an entire startup. I gave MiniMax M3: • product docs • pricing • customer feedback • roadmap • competitor research Then dropped everything into Cursor and asked it to build the product. What impressed me wasn't the code. It was how well M3 connected information across all the documents and turned them into actual product decisions. Feels less like "AI coding" and more like working with a junior product + engineering team.

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