I recently got this message about using AI agents and other tools:
It seems so convoluted...! You need to install PI then OpenRouter and then select agents but depends on what you really need it or how much are you willing to spend... is it Cline a competitor to OpenRouter or PI ? so confusing....may be because we are at the beginning of a new world. For example why doesn't OpenRouter incorporate PI or vice versa or Cline then there is Cursor.....? it seems so complicated for no reason.
Here's my response:
It's not convoluted, there are just a lot of choices between competitive services and software offerings by different companies. Once you get the basics about how agents and LLMs work together, they all basically work the same way.
Pi is an agent (one choice of a piece of software called a 'harness'). OpenRouter is an LLM API service provider (one company that provides access to Large Language Models running on their GPU hardware). The LLM can be thought of as a 'brain', the agent can be thought of as a 'body' which gives the LLM brain access to work on your local computer hardware/OS. You install the harness on your computer and choose what resources it has access to.
There are plenty of other popular harnesses (Hermes, Codex, Claude Code, Open Code, Open Claw, Goose, Nanobot, etc. - all software you install to give an LLM brain access to work on your local PC) and there are plenty of other LLM providers (OpenAI (GPT), Anthropic (Claude), Deepseek, Grok, Kimi, GLM, Minimax, etc. - all different brains).
All the harnesses and LLMs do essentially the same thing, but there are options to satisfy every need, every type of work (for example, harnesses tuned to help with software development, operating system automation tasks, personal assistant tasks, etc.), every budget, every security profile, every performance level, etc.
Some LLM providers also build harness software tuned to work specifically with their particular LLMs (Cursor, Codex, Claude Code, etc.). There are open source and commercial models, small/fast/cheap models, large/slow/expensive models, etc.
In the past few months we've gotten models such as Deepseek V4 Flash which can complete most development and agentic tasks at a cost of 18 cents per million output tokens. Deepseek is free and open source - I run a copy of it on several of my local GPU server machines, and I also run it over APIs served by OpenRouter, Cline-pass, Deepseek, and others.
The agent harness is software you install on your PC, your phone, VPS accounts, etc., to enable an LLM (wherever it's running on GPU hardware - locally, or in some data center, over an API) to manipulate your local computing resources, to work unattended in iterative loops to complete software development tasks directly with code and tooling on your computer, and to get work accomplished for you, on systems where you run them (you can choose to provide your harness the credentials needed to log in to your accounts, to summarize and respond to emails/messages, to read and write documents on your system, to configure OS settings, to install software, to perform research about any local project you're working on, etc.)
An LLM brain is smart enough to understand it's working on your local machine. The harness tells the LLM brain about its environment, with every request it sends (along with sending the entire conversation you're currently involved in, in every session).
The harness program gives the LLM access to read and write files on your hard drive, execute OS commands, install software tools, etc. The harness additionally enables you to create memories and 'skills' about how to perform certain tasks you want to accomplish regularly. Those are typically just text files that you save on your machine. You can share skill files and use skills created by other people. You can also ask the LLM to create and save skill files anytime you successfully complete a task, so you don't have to go through the same long process of having the LLM figure out how to accomplish that goal every time. You can also have the harness save memories, which it loads automatically every session, so that it remembers your preferences and working habits.
Pi is a very simple agent, which sends only a minimal amount of information to the LLM every session, but it provides deep capability to not only use skills, but also to branch sessions, and to automatically extend itself with self-created extensions to its own internal software code. It avoids all the typical bloat found in other agent applications, but it's incredibly malleable and capable. You simply prompt it to build extensions - it gives the LLM all the information needed to write working extension code.
All the biggest LLM brains typically need to run on very expensive hardware, which may require more electricity than most people have available at their home or business location. So most people use remote LLM service providers, because they don't want own/run the expensive GPUs which are required to perform LLM inference. Users hook up their agent harness software to any provider which offers inference on the models they prefer to use, for fees they prefer to pay. Or they hook up their agents to models running on their local GPU server machines.
I have 7 machines with GPUs that get used for local inference (for data processing tasks which require HIPAA compliance, for example, involving personal health info that can't be sent to any public LLM API provider), but it's still very convenient, fast, and cheap for me to use a provider like OpenRouter or Cline-pass for everything else. I set up those LLM services so that agents on my phone and VPS accounts can work with a powerful brain, as long as they have an Internet connection. LLM API service providers make it easy to instantly hook up to a big brain, regardless of the local hardware your agent software runs on.
I use OpenRouter because they provide access to 500+ models - basically every commercial and open source LLM available in the industry. You create one account with OpenRouter, and can use models from basically every company that makes LLMs.
I also still use OpenAI's LLMs for lots of development pipelines that have been established for months, using their models. And I have a dedicated account with Deepseek, because my favorite V4 Flash model runs at 250 tokens per second at that API (extremely fast). I've started using Cline-pass lately because they provide access to all the most common open source LLMs, for the lowest prices I've seen anywhere. With Cline-pass I can get more token usage on a few of my favorite models, than I could run through, if I ran those models nonstop all day every day all month - and my favorite model runs at 200 tokens per second on that API (it runs much, much slower on my local machines) - all for less than $7 per month.
So I choose to use Pi and those commercial LLM provider services, but those configurations are all just my personal choices. Everyone has their own favorite choices.
All anyone really needs to do, though, is open an account with OpenRouter, create an API key, and install Pi, or any other single agent software.
The link below walks through every detailed step of setting up Pi & OpenRouter, and explains much more about all the other choices you'll find in the LLM ecosystem:
https://aibynick.com/thread/29
So, everything you can do with an LLM can be accomplished with an Openrouter API key and Pi. With OpenRouter, you can use every well known model, the instant each one becomes available. You don't need a bunch of expensive subscriptions. And you don't need to use expensive models - just use Deepseek for most work. I use the smaller Deepseek model called V4 Flash, for just about everything. It's basically as good as all the most expensive models, for most common tasks. It costs 18 cents per million tokens on most APIs, and it's much cheaper on Cline-pass. Plus it's extremely fast, and uses much less energy than most of the big frontier models. You can use Mimo 2.5 or one of the other inexpensive multimodal models for vision work. I explain everything about using all the other most useful inexpensive models, in the article linked above.
None of that has to be convoluted or complicated. With an Openrouter account, it takes less than a second to switch models in Pi (Pi automatically knows all the models available on Openrouter - you just type '/model' to select and switch instantly between them). And to install Pi, it just takes a few seconds of hands-on work. The instructions are completely covered in the link above.
I've got Pi running on 20+ PCs, multiple VPS hosting accounts, and my phone. If Pi feels too complicated, try PicoClaw - it requires zero installation on any PC, and they even release a universal APK that runs instantly on any Android device:
It's absolutely worth getting past the hump of learning to use an agent and an LLM provider. You can learn all about how to do it in a single sitting, and get completely comfortable with it all, in a day. Agents are made to be easy to use.
At this point, my LLM models are involved in helping me accomplish virtually every task I need to complete, every day. Today I had Pi on my phone build a beautiful 49th anniversary animated digital card for my parents, while I was driving to their house, totally hands off, using voice control. That's just one example of thousands of agentic tasks I've had agents perform.
LLMs help me much more quickly and easily handle most communications (emails with clients, IT teams, project managers). I have my agents manage all my billing (they summarize all the work I've done, the hours I've worked, and generate the invoices). Software development tasks are now basically fully automated, and each development step/revision in the course of large development projects, typically gets completed instantly.
Massively complex applications which would have taken dozens of man-years and cost millions of dollars to complete a few years ago, can now be completed in a few months by a single developer, without any pain or trouble (in many cases, much technical skill is no longer required to build software). I have clients with zero software development experience building and deploying their own real, valuable, customized applications, the likes of which would have been genuine time-consuming challenges for an experienced team of developers just 2 years ago.
In comparison, configuring an OpenRouter account and installing a harness application is not even close to being as complicated as writing even a few lines of code by hand, in any programming language.