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for teams already running AI

You're paying for the whole model. Are you using it?

Most teams run AI at a fraction of what it can do, then blame the model. It's usually the setup. We fix the setup.

what most teams get out of AI todaywhat the same model can already dothe gap we close

02 / worked example

Our agents read 42% less on every call and get more right

Here's one we can show you in full, because it's ours. Most setups keep every instruction in one file. All of it loads on every call, whether it applies or not.

42%

less loaded into context on every call, with nothing removed from what the agent can reach

before

One file, everything in it

  • Every project's rules, loaded every time
  • Decisions and history you rarely need
  • Grows every time you add a project
  • The model reads it all to answer anything

after

Tiers, loaded on demand

  • Core rules stay lean and always on
  • Project rules sit in the folders they apply to
  • Skills load only when something invokes them
  • A linked wiki, read on request

Nothing got deleted. It moved to where it gets looked up instead of loaded. Same for facts and past decisions: they're there when we ask, out of the way when we don't. Shorter context, cheaper calls and the model stops getting distracted by rules that don't apply.

See how the tiers work

measured on the same instructions file, before and after

03 / the problem

It's rarely the model

When AI gives you vague or inconsistent answers, the instinct is to upgrade the model or add a tool. That's usually the expensive way to fix the wrong thing.

The model reads too much

Every call carries context that doesn't apply. You pay for those tokens, you wait for them and they crowd out what matters.

Nothing runs the same way twice

Prompting by hand means a new answer every session. Without structure, you can't tell a good result from a lucky one.

The knowledge lives in one person

One person on the team knows the prompts that work. That's not a system, and it leaves with them.

05 / how this goes

No discovery phase, no slide deck

01

We look at what you run now

A short call, then we read your actual setup. Prompts, files, whatever's wired together.

02

We show you where it leaks

A written findings note. What's costing you, what's unreliable and what we'd change first.

03

You decide what to fix

Do it in-house, or we build it. Both are fine, and we'll tell you which one we'd pick.

about

We run these systems daily

We're not reselling somebody else's dashboard. We build and run agents for our own work first, and what survives contact with real use is what we recommend.

So you get advice that's already failed a few times somewhere it didn't matter, instead of advice that reads well in a proposal.

Want to know what your setup is costing you?

Tell us what you run now. If there's nothing worth fixing, we'll say so and you'll have lost 30 minutes.

Questions people actually ask

Do we need to switch models or tools?

Usually not. Most of what we find is in how context gets assembled, not in which model is answering. If a switch is worth it, we'll show you the numbers first.

What if there's nothing to fix?

Then we tell you that. It happens, and it's a much cheaper answer than the alternative.

How technical does our team need to be?

For an audit, not at all. Someone needs to be able to show us the setup. For the training, anyone comfortable in a terminal will keep up.

Can our team run this after you leave?

That's the point of the training. If you still need us in 6 months, we did it wrong.

Do you work with companies outside Spain?

Yes. Everything here runs remotely, and most of our work already does.