7 Prompt Chains for Decision Making, Self Correcting, Reliable AI Agents
ฝัง
- เผยแพร่เมื่อ 31 มี.ค. 2024
- AI Agents are the NAME of the SOFTWARE GAME. Knowing how to build POWERFUL AI Agents is everything in the AGE of AI.
Use these 7 Prompt Chains to build POWERFUL AI AGENTS with the help of Claude, Opus, Haiku or your favorite LLM.
The name of the game in software engineering is: How can I build agentic software where my AI Agents can do the heavy lifting for me? There are levels to this. You start with a single prompt, then you can chain prompts and code together to create powerful AI Agents that can do the heavy lifting for you. There are so many applications for this, from content creation to research to coding. Every single prompt chain is a potential 5,6,7 figure product. We're only scratching the surface with UIs like ChatGPT, Anthropic, Gemini and other Chat Based UIs. The future is bright for AI Agents and Agentic Applications.
Let's unlock the Prompt Chains that can enhance your prompt engineering abilities to elevate your software's capabilities. We're breaking down seven powerful prompt chains, complete with real-world examples, to show you exactly how to harness LLMs like Claude-3's Opus, Haiku, Sonnet, and whatever your favorite favorite LLM provider is. Discover how u create Agentic software that works tirelessly for you and your users, adding incredible value every step of the way.
The ideas we'll discuss are at the core of tools like Langchain, langgraph, Autogen, and CrewAI. While these tools are powerful, they're often overkill. Powerful AI Agents can be built simply by combining together several prompts in certain patterns and workflows. Call it prompt chaining, prompt orchestration, prompt graphs or whatever you like. From constructing compelling blog posts with the snowball prompt chain to building entire software modules via the worker pattern, this video is a goldmine for anyone looking to deploy AI in practical, impactful ways. Consider a free AI Prompt Engineering Course where we'll reveal several prompt orchestration patterns like the fallback prompt chain, a pattern than can save you time and money while ensuring your AI Agents are still reliable and effective.
It doesn't matter what you're building. AI Coding Assistants, Research Assistants, Personal AI Assistants, CLI Tools, all benefit from your ability to build prompts and your ability to compose prompts into useful patterns. Let's walk through seven distinct prompt chains, including the innovative snowball and worker patterns, showing you the path to automated content generation, sophisticated research tools, and even custom AI coding assistants. Discover how to make your software think, adapt, and solve problems with minimal input, unveiling a future where your software development process is as dynamic and intelligent as the market demands.
Composability, and Reusability are a big idea we focus on on the channel. AI Agents are no different. The more you can compose prompts together, the more powerful your AI Agents will be. The more you can reuse prompts, the more efficient your AI Agents will be. This is the future of software engineering. This is the future of AI Agents. This is the future of Agentic Applications.
✏️ Get These 7 Prompt Chains (Gist): gist.github.com/disler/409d96...
🗣️ When to use PROMPT CHAINS: • When to use Prompt Cha...
🐍 LLM Python Module: llm.datasette.io/en/stable/py...
🤖 LLM Claude Python Module: github.com/simonw/llm-claude-3
🛠️ How to Engineer Multi-Agent Tools: • How to Engineer Multi-...
🔮 2024 Predictions (AI, LLM, Coding, Agents): • 2024 Predictions for A...
📚 GPT Research (Worker Prompt Chain): github.com/assafelovic/gpt-re...
#aiagents #promptengineering #gpt - วิทยาศาสตร์และเทคโนโลยี
![How To Connect Local LLMs to CrewAI [Ollama, Llama2, Mistral]](http://i.ytimg.com/vi/0ai-L50VCYU/mqdefault.jpg)
Anybody else feeling overwhelmed with excitement? AI coding took over my life.
YES!! Is there a support group? Because I would honestly love to talk to people who are as obsessed with coding random AI projects as I am lol
@@Lucky9_9 Agentic Coding Anonymous
@@vincentjean6756 very sad this isn’t an actual thing lol
Were you guys coders before ai came to be useful? What kind of projects do you build and what models/apps do you guys recommend? Happy to be among fellows.
@@TheExodusLostWell... I have been surrounded by code all my life. I am an options trader and entrepreneur since I was a teenager. Always built some tools to help my projects with some success. AI coding took my low quality projects to a level where I would actually pay thousands of dollars to a freelancer to do the same work.
I can now do it myself if a few hours where it would take weeks of back-and-forth to achieve the same work with a human coder.
People always think that they need some kind of "ideas" to make "new" tools to sell in order to make money with AI.
What people do not realize yet, is that they are their own customers. They power of AI is in ultra-personal and specific tools for a very niche work for maybe one or two individual (including yourself).
They are the customer of their own custom tool.
i love your work!
🎯 Key Takeaways for quick navigation:
00:28 *🌨️ Snowball Prompt Chain gradually develops information over multiple prompts, enhancing context with each iteration, and concluding with a summary or format prompt.*
03:14 *🛠️ Worker Pattern involves delegating tasks to individual prompts, processing them in parallel, and consolidating results into a final report, ideal for research tasks.*
07:26 *🔄 Fallback Prompt Chain allows switching between different prompts or models if one fails, ensuring continuous operation and reliability.*
12:50 *🤔 Decision Maker Prompt Chain enables AI agents to make decisions based on prompt results, guiding subsequent actions or prompt chains.*
15:07 *📝 Plan and Execute Prompt Chain involves planning tasks first, executing them based on the plan, and concluding the process.*
16:44 *🔄 Human in the Loop Prompt Chain integrates user feedback into the prompt chain, allowing iterative refinement until desired results are achieved.*
17:38 *💬 The chat GPT application operates on a prompt-response flow, highlighting the potential for entire products built around this interaction.*
18:32 *💡 There's an ongoing innovation push beyond chat interfaces, exploring diverse prompt chain applications like talk to your database's call-response format.*
19:01 *💬 The human-in-the-loop framework, commonly used in chat interfaces, can be expanded creatively by combining different prompt chains for varied user experiences.*
19:45 *🔁 The self-correction prompt chain involves executing a prompt, checking for correctness, and self-correcting if necessary, proving useful for coding, executing, and reviewing tasks.*
21:21 *🛠️ Seven prompt chains offer diverse workflows for building powerful AI agents and agentic systems, paving the way for innovative product development beyond conventional chat interfaces.*
Made with HARPA AI
Shout out HARPA AI devs.
having spent years espousing the benefits of functional programming, being able to use that same model for my agents is priceless.
Great job on this video Dan!
Exactly!!! Me too. Always loved functional programming and applying the same concepts here (just functions branching and piping) is very refreshing.
Keep going bro! Love your content. You are a pioneer in this space. No one else that I know on youtube is providing the value that you are providing to the development community.
Omg Dan! This was pure gold. Thank you.
Thank you Dan. Really appreciate the energy you thought you put into this!
bro, this video is pure gold
loving your videos dan , super excited to see your ai development
Great video. Love to hear about your AI assistant.
subprocess module looking nice lately
An absolute banger, thank you Dan for sharing these incredible insights ❤
Dan... AI MASTER! Thanks for your ideas.
Brilliant. Run the cheaper, faster models first! Good stuff, Dan.
The first 10 seconds, total wisdom 👍
Superb information! Thank you!!
Thanks Dan great work man!
Very good Video! Thanks for laying this out so well. Its been interesting to see what happens when you start combining system prompts into this as well.
Really awesome, man! tks 4 sharing
Pure quality content ❤💯
This is super awesome. We built a voice AI software intertwined with ghl on a ton of other AI. Trying to figure out a self-updating method. Can review certain number of transcripts figure out corrections and way to smooth out the bot double triple check that. Then update.
thank you so much, very high quality content as usuel
awesome tutorial! thank you!!
This is such good information! Thanks for making this, I've really been struggling with the design of my agent tasks.
Yes please, let's see the AI assistant you are building
Definitely interested in the AI assistant🎉❤ I'm building my own too
As usual great Stuff Dan!!! Please create the further videos in this series like Talk to your DB.
Great info. Subbed
Bro... you just gave us patterns!
Great !
Great job dan u should contribute to big agi they have a beam feature that integrates output from multiple llms and i think ur prompt structure would be a great addition to it
I will put a link to ur vid in their discord dope work
big thanks, I have my eyes on big-AGI. Development looks solid.
very nice
Great video.
I really like your content because there is no sh*tty general hype talk or "pay me to join our unique community" stuff. Anyways the content is solid and concrete
Great! Keep up the good work. Btw which Theme are you using? The transparency and colors... love it
if we have to choose between Agentic framework and prompt chaining which should we prefer ?
"The right sequence of prompts combined with your unique domain knowledge is an entire five six or seven figure product in itself." This powerful and seductive statement may well be true, but, just to make sure neither you nor your audience is hallucinating, **How do you know this? Where is your citation to the source for this statement? How can we verify it?** Academic studies, something from arXiv, Entrepreneur, Inc. Mag, The US Dept of Labor, anything? Thanks.
Congrats on 10k! I'm extremely interested in a personal AI assistant. I've been eyeballing OpenInterpreter and their 01OS for a bit, but haven't taken the plunge. I'd be interested in seeing what you're ideas for an assistant. OI is using STT/TTS for the 01 project using Arduino. However, I'd rather use a smart phone app as it can be installed on multiple phones easily and the phones already have the necessary, and additional, hardware for this part of the job.
I'm also on a quest for a personal AI Assistant. I'll bet there's a way to use the resources on a smartphone, one could easily use Devon or SWE to replace the Arduino code or convert. Connecting to OpenInterpreter could be done over wirelessIP or bluetooth.
huge thanks - we will 100% cover, design, build and discuss personal AI assistants on the channel. It is one of the most important Agentic applications any of us can build/use.
@@indydevdanI totally agree! I can't wait! Really looking forward to it!
Man, just thinking about all these different solutions makes me realize that all OS as we know it are just near future trash.
Been trying to get AG studio to run a workflow but the final stage agent keeps interrupting. Have you successfully got chaining and snowballing working on Autogen Studio?
gold
@indydevdan cool stuff, question; any partiicular reason for using Martin's LLM? it is nice but half plugins dont work anymore, it¨s maintained by a singel person, Could LLM be substituted with another package like ollama?
100% use any LLM package you prefer. I'm a fan of Simonw and his LLM package so I use it from time to time.
You should have called it Design Patterns for AI prompting. You'll be the new gang of 1. Or maybe Gang of 10k+
When are you gonna try instructor 1.0.0? Game changer with pydantic
Great call out - it's worth a whole video. Several cons and many pros to a tool like that but overall I agree with you. It's a total game changer with pydantic.
Hey, Dan, did you read what your snowball wrote, bud? You're a smart man, Dan, so I know you've heard about Dead Internet Theory. And yet you thought this video was a responsible decision to create. Are you that hard up for money, Dan? Are you?
"software now is"..., Welcome everyone to my vision into the future. 11 yrs earlier...🤷
I’m not going to subscribe until you Google upspeak.
solid feedback ty. Let's make a deal: Subscribe next video if I ship it with zero upspeak. Deal?
Deal. Sorry for being a jerk. I was grumpy. Want me to remove the comment?
i have programing background, started in 94. I cant undertand most of what you say because you removed all natural respiration and ponctuation and smashed all words. its unintellegible. rubbish
the hand movement is so distracting and the thump thump.
Great work - will have work this out in typescript 🎉