A Vision for True Agency
Language models can understand and synthesize information an order of magnitude faster than humans, but they lack the perceptual apparatus to get the data to synthesize or the ability to act on their findings.
They are like rocket engines with no fuel left; they are powerful, but go nowhere.
Today’s most successful AI products are conveyors, delivering materials to and from the AI’s “engine”. Claude, Gemini, and O3 - these models are smarter than us. In terms of raw intelligence, the “singularity” is behind us.
The challenge ahead has two parts -
How can we deliver exactly the right information to AI at exactly the right time?
How can we connect AI’s decisions to actions in the digital and physical worlds?
AI-assisted coding applications have shown us what can be done when LLMs are provided with the full recipe. Apps like Cursor and Windsurf can see your source code, modify it, run it, and check the results. This lets AI learn by trial and error.
It’s hard to express how powerful this mechanism really is. This process is how children learn and how tech companies iterate. Evolution itself is just trial and error repeated over a geological timescale. It’s clear in using the best AI products on the market that this process is not yet automatic. Cursor’s “agent mode” is like a poorly balanced top - after a few spins on its own, it loses momentum and falls flat.
An “agent” is something that works towards a goal on its own. No step-by-step instructions, no feedback in the middle of the process. Just results. Nothing that exists today is anything like a real agent. The process of trial and error does not repeat on its own. It’s still us, the users, who are the agents behind each trial.
Beyond functionality, the domain of the best tools remains technical. Most people do not write code. This isn’t due to some intellectual lapse on their part. Coding has become even easier to learn and is now almost trivial. Most people don’t code because they aren’t interested in it or are unaware of just how far we’ve come. This fact is easily missed by the people who build software products. What we do is not interesting to the majority of the population, yet almost all AI products to date have focused on coding, app building, product design, and so on.
Fundamentally, we use technology to extend our capabilities. To make us superhuman. Technology collapses the difficult or boring parts of life, turning hours of labor into a single button press. AI has promised, or rather threatened, to turn our occupations into these simple abstractions. Accounting, engineering, and even law have become point-and-click.
But it hasn’t happened. Yet.
Instead, the word “agent” has been converted into corporate newspeak. An “AI agent” is just a workflow in disguise, and it’s only for the already technical. At FXN, we’ve challenged ourselves to imagine where AI belongs in the lives of people with specialties other than software engineering and to push the boundary of how we can help them beyond rebranded workflows.
TikTokification
The best short form content follows the same formula:
An item is not working right
A few glamour shots of fixing it
Now the same item is shiny and new
This content condenses hours or days of work into 5-10 seconds. We experience the satisfying “glamour shots” without realizing the actual effort it would take to execute them ourselves.
The content this produces is satisfying to watch, even though we do not have the shiny thing. We’re merely happy because the thing has become shiny. The key realization of TikTok style content is that the processes involved in achieving these outcomes are often deeply unpleasant. Farming, welding, and building are tough, dirty jobs. Yet their difficulty is kept out of sight, so we can enjoy the outcome without ever confronting the effort behind them."
We all have items in our lives that aren’t quite working right. We all want to see those items shiny and new again, but we often aren’t willing to tolerate the dirty and difficult work needed to make that happen. Our goal with Mirra is to take on those dirty and difficult jobs, provide people with a few glamour shots of the tasks being completed, and then give them that item, shiny and new.
Our success is measured in the hours of meaningless work you don’t have to do.
The Lindy Effect
What does a software engineer do all day?
Most of us would answer - they write code. But the act of typing the code itself is a minor part of the overall schedule of an engineer. Attending meetings, writing Jira tickets, and tracing bugs - these tasks are way more time consuming, but we don’t describe them as “software engineering.”
Fire the engineer, and you lose all these "invisible" functions you didn't even realize were keeping your product alive.
The tasks we're required to do in our jobs extend far beyond what's written in the job description. While we focus on the headline work like code, strategy, and creative output, it’s the hidden Lindy tasks that quietly consume the most time. Administrative busy work, coordination, and maintenance that never make it into anyone's performance review.
Automation of Lindy tasks is the next frontier of productivity. Not in replacing the work we love doing, but in handling the work we hate. The stuff that has to get done through processes we do not enjoy surrounds the work we love.
Doing more of what you love
Our mission is to empower people from any walk of life to spend more time on what they love.
That means giving people access to the same kind of automation power traditionally reserved for engineers. Assembling the right tools, connecting them with your data, and using best-in-class AI services to execute tasks on your behalf automatically and transparently with zero learning curve.
Most AI tools today are still developer-first. Designed for people who know how to build software, they automate the creation of more software through iterated trial and error.
Bias towards developers is natural. They’re more willing to tolerate bugs and troubleshoot failures. But AI has progressed to the point of eclipsing most of us in raw intelligence and all of us in terms of execution speed. Lawyers buried in documents, parents juggling schedules, and frontline workers stuck in paperwork are being left behind.
Not knowing how to code should not exclude you from accessing the newest technology. ur goal is to connect people from any walk of life or field to the same tools currently reserved for developers.
Mirra is designed to be your action engine, not a playground. It doesn’t ask users to write prompts or string tools together. It understands what you need, assembles the right tools, and delivers results. No micromanaging. No manual orchestration. You get the payoff without the mess in between.
Eliminating the learning curve and delivering value with zero setup is essential to productivity. Overwhelmed users do not need more things to feel overwhelmed about. The strongest contributor is the one who sees what needs doing and gets it done without waiting for instructions.
Mirra - Powered by FXN
Making AI genuinely useful requires more than a single model or application. It depends on an ecosystem of systems working together.
With Mirra, we focus on coordination rather than reinvention. Our platform is built to connect existing services, tools, and “agents” so they can operate together in meaningful ways for real users.
The real challenge isn't only about making models smarter. It's about giving them the right data and context so they can act usefully. Much of what matters, from personal context to enterprise telemetry, is fragmented across systems that aren’t easily accessible or interoperable with general-purpose language models.
Mirra is built to work with this reality rather than against it. We support a distributed network of contributors, each offering something focused. Whether that’s a stream of domain-specific data, a purpose-built tool, a memory layer, or a decisioning service. These contributors can be mixed, matched, and composed into higher-order agents through the SuperSwarm: a growing network where useful outputs can be coordinated and rewarded.
The FXN protocol makes this possible by providing shared infrastructure for discovery, communication, and compensation. Developers don’t need to build full applications to participate. They can offer lightweight, modular services that plug into the broader system and deliver value contextually. This architecture scales by cooperation instead of centralization. As more participants contribute, the system becomes more capable without becoming more complex.
Building for tomorrow
There’s a lot of talk about AI replacing people. That’s not what we’re building.
Mirra is designed to take care of the things you don’t want to do, not the things you enjoy or the things that make you who you are. It’s about freeing up time, not replacing it.
The future we want to build isn’t one where people do less. It’s one where they get to focus more on what matters.
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