Token Limit Exceeded is a consulting practice for teams putting AI agents to work: automation that runs unattended, model costs that don't surprise you, and systems that know when to stop and ask a human.
Most AI projects stall between a promising prototype and a system someone can trust without watching it. That gap is the whole job.
Multi-agent workflows that pick up work, do it, check it, and write the result back where your team already looks.
Right-size the model for each job, stop paying frontier prices for lookup work, and put ceilings on spend before it happens.
A clear-eyed look at where AI earns its keep in your operation, where it quietly makes things worse, and what to do first.
Set your engineers up to work alongside coding agents like Claude Code and Codex, with shared skills, guardrails and review habits.
A fixed-scope engagement to map your workflows, data and constraints, and agree on the one or two automations worth building first.
We build in your environment, with your credentials never leaving your control. Every step is verified by running it, not by a model saying it worked.
Runbooks, monitoring and a walkthrough, so the system keeps working after we leave. Ongoing support is available but never required.
We run our own multi-agent operations stack in production. These are the rules it taught us.
Whatever fits the job and your policies: Anthropic Claude, OpenAI, Google Gemini and local models, plus agent tooling such as Claude Code, Codex and the Model Context Protocol. We don't resell anything, so the recommendation isn't tied to a vendor.
Only as much as the work requires, and on your terms. Builds happen in your accounts and environments, secrets stay in your vaults, and access is removed at the end of the engagement.
Most start with a short, fixed-scope audit. From there, builds are scoped one automation at a time, so you see a working result before committing to more.
Because every serious AI system eventually hits a limit: a rate limit, a context window, a budget, or the edge of what the model can do reliably. Designing for that moment is most of the work.
Tell us what it is, what it touches, and what happens today when it goes wrong. We'll reply with whether we can help and what a first step looks like.
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