Cronacl started as a side project to see how far you can push agents and modern AI models when you wrap them in a simple, calm workspace. It turned out useful enough to share.
This didn't start as a grand vision or a pitch deck. It started as a way to experiment.
I wanted one place to talk to models, glue together a few tools, run small workflows, and see how far you can push high-quality work and content out of agents without turning everything into a research project.
Most tools I tried were either shiny demos or overcomplicated platforms. Cronacl sits in the middle: a straightforward workspace with a decent harness around agents, tools, and documents.
Good tools don't need a manifesto. They make it easier to do the work you already care about and then get out of the way.
Cronacl is not trying to reinvent how humans think, replace your job, or solve AGI. It's a workspace:
– A place to chat with models – A place to run small agents and workflows – A place to plug in your tools and documents
That's it. No grand promises. Just something that makes using modern AI a bit less annoying and a bit more productive.
The starting point was simple: what would I actually keep open all day while working?
So the first version was just: – A clean chat surface – A way to run repeatable tasks as agents – A way to plug in tools and APIs – A way to pull in documents when needed
From there it grew: integrations for the usual suspects, a more structured way to define agents, and a knowledge layer that lets you ask questions against your files without building your own RAG pipeline.
Nothing here is magical. It's just the plumbing and harness most people don't want to build themselves.
A focused place to talk to models, run tools, and see results. No prompt-engineering course required. Just type, iterate, and keep moving.
Turn the things you do over and over into simple agents. Describe the steps, plug in the tools, adjust as you go. No long setup, no flowchart hell.
Connect the services you already use—email, project tools, data stores—and call them from the same place you're thinking and writing.
Pull your PDFs, notes, and other files into the workspace and ask questions against them. Let the agents use that context without you hunting through folders.
Under the hood it's just a bunch of TypeScript, queues, and calls to modern language models from providers like OpenAI, Anthropic, and Google, plus whatever you plug in yourself.
Cronacl handles the boring parts: prompt wiring, context passing, basic orchestration, error handling, and tool calling. Models and providers can change over time; the workspace stays the place where you interact with them.
If you're technical, you can bring your own keys, models, and tools. If you're not, you can ignore this section completely.
There's no ten-year master plan. The rough direction is:
– More integrations for the tools people actually use – Smoother agent setup and iteration – Better ergonomics around documents and research flows – Maybe lightweight collaboration if it turns out people really want it
The bar is simple: if it makes day-to-day work with AI less fiddly and more useful, it probably belongs here. If it feels like a demo feature, it probably doesn't.
Cronacl started as a way for me to play with agents, routing, and different model providers, and to see how far you can push high-quality output from a fairly simple setup.
It wasn't meant to be a Big Idea. It was meant to be a small, solid workspace that makes working with modern AI less of a hassle.
If it helps you think, write, research, or ship a little faster, that's enough.
— Mohamed Achaq