One team. One approved context.

Everyone has an AI assistant. Nobody's assistants agree.

AI made individuals faster, not teams. People rebuild context in every chat, drafts revive options you already rejected, and nobody can say which decision is current. We design the team workflow and run it on teamctx, our open-source context layer, so people and their AI agents work from the same approved decisions.

  • Fixed cost
  • Operator-led
  • Open-source teamctx
  • CEO / COO / CPO / team leads
ScopeFixed cost, milestone-billed. No hourly billing.
Built forCEOs, COOs, CPOs and team leads
Works withClaude, ChatGPT, Gemini and MCP-compatible AI tools
You leave withTeams that ship more, with decisions that stick
When this is the right service

Pick this when everyone has AI but the team isn't faster.

01

Your team uses AI, but every draft misses what you decided.

Drafts revive options you already rejected and ignore constraints you set last week.

02

You delegate work, then rebuild the context.

Every handoff starts with another round of background and corrections.

03

The team agreed on a change, but old thinking keeps coming back.

Decisions live in a chat, a doc or someone's head, and get relitigated.

04

Context leaves when people do.

A teammate or contractor moves on, and what they taught their AI goes with them.

05

People use different AI tools, and none of them agree.

Each assistant holds its own version of the project.

Sound familiar?

That's usually where our first conversation starts.

Start a conversation →
What you get

In-depth team and AI-workflow experience across modern tech.

One outcome for each situation above, numbered to match.

01For: drafts that miss the point

A shared, approved context every AI tool works from.

Goals, decisions, rules and assumptions are written once, approved by the accountable manager, and retrieved by every person's AI.

02For: delegation that loses context

Delegation that carries its reasoning.

Each person and their AI gets the approved background for their role, so a task arrives with the why, not only the assignment.

03For: relitigated decisions

Decisions that stick, with full accountability.

Each decision has an owner, a reason and its exceptions. Proposed changes are reviewed and approved before they become shared context.

04For: handoffs and onboarding

Handoffs and onboarding without lost context.

Approved project context lives in your Git repository, not in private chats, so new teammates and contractors start from the same facts.

05For: tools that disagree

One source of truth across every AI tool.

Approved context reaches each assistant through MCP or generated briefs, so everyone's AI works from the same version.

See it in practice

Results from a global strategy consulting firm's product teams.

See client impact ↓
How it works

Build → Operate & Optimize → Train & Transfer

Applied to team AI. People and AI do the work; your managers approve what the team treats as true.

Start here

Design & Prove

We pick one team and one consequential workflow, measure rework, repeated review and reversed decisions today, and prove the approach on real work before you commit.

You getA baseline, and the first workflow proven on real work.
Step 1

Build

We design the team workflow: who decides, what each AI agent does, and where exceptions go. Then we set up teamctx in your Git repository with the goal, workstreams, roles and first approved decisions.

You getA team workflow and a shared, approved context.
Step 2

Operate & Optimize

We run it with the team on real work: reviewing proposed changes, tightening rules, and tracking rework, review cycles and decision stability until the gains hold.

You getProductivity and decision quality that hold up against the baseline.
Step 3

Train & Transfer

We train your managers to review and approve context and your team to contribute, and hand over the workflows, records and operating rhythm. teamctx and its history stay in your own repository.

You getA team that runs it, and improves it, without us.
Proof

Client impact

Customer Success Apparel & Fashion

12 months of innovation planning, down to weeks.

A Fortune 500 apparel and lifestyle company benchmarked agentic AI against its own 18-month innovation process. A 40+ agent system, grounded in proprietary data, compressed roughly 12 months of planning and cross-functional coordination toward weeks — and leadership operationalized it.

40+Orchestrated agents
Months → weeksPlanning compressed
AdoptedInto the workflow
Read full case study →
FAQ

Questions about AI Productivity

Our AI platform already has shared projects. Why add anything?

Shared projects hold files and instructions inside one AI platform, and anyone with access can change them. teamctx adds what a team needs on top: proposed changes that the accountable manager reviews before they count, a version history in your Git repository, and the same approved context for people who use different AI tools.

A shared doc already holds our decisions. Isn't that enough?

Docs and chats are where the discussion happens, and they should stay. The gap is turning the outcome into something every person's AI can use: the current decision, its reason, the rule it creates and the exceptions to it, scoped to each role. teamctx captures the approved outcome from those tools so nobody has to rebuild it from a conversation.

AI can summarize our decisions. Why do we need a workflow?

A summary is a snapshot, and it drifts the moment something changes. Nobody has approved it, and it isn't what the next person's AI reads. The workflow decides who can change what the team treats as true, records why, and delivers the approved version to everyone's AI, so a reversed decision is reversed everywhere.

Will our AI always follow the approved decisions?

No tool can guarantee that. teamctx makes approved decisions, rules and exceptions available to every person's AI, but it doesn't force an assistant to follow them or silently rewrite conversations that are already open. People still exercise judgment and review the work. What changes is that everyone starts from the same approved context.

Do we have to buy teamctx?

No. teamctx is open source under the MIT licence, with no licence to buy, and you can install it yourself. The engagement covers what software can't: choosing the right team and workflow, setting the first goal, decisions and rules, training managers to review, and measuring the result. Everything stays in your Git repository when we leave.

Where does our data go?

Project state and history live in your Git repository, under your access controls. The command-line tool and local MCP server run on your machine. teamctx's own AI processing calls Anthropic, OpenAI or Gemini with your API key. Optional web hosting has its own access settings.

How do we know it's working?

We baseline rework, repeated review and reversed decisions before we start, and measure them again as the workflow runs. In our case study with a global strategy consulting firm, teams saw more consistent decisions and less repeated review.

Which teams is this for?

Product, GTM, marketing and operations teams where people already use AI and a lead or manager is responsible for the combined result: teams that delegate across people using different AI tools, bring in contractors, or hand work over when people change roles.

Who does the work?

Senior operators only. Our team has built and shipped AI products, agents and platforms at SaaS, health technology, consulting and fintech companies, so the workflow reflects how teams really work with AI, not how it looks in a demo.

How is this scoped?

Fixed cost, milestone-billed against named deliverables. We do not bill hourly. If scope changes mid-engagement, we re-quote in writing before any new work begins.

What happens after the engagement ends?

Train & Transfer ends when your team runs the workflow without us; ongoing optimization is optional. Many clients then add AI Optimization to govern agents, cost and data across the company, or a GTM System build to apply the same discipline to go-to-market. There is no obligation either way.

Ready to get your team and its AI on the same page?

30 minutes to look at how your team and its AI tools work today and whether this is the right service.

Start a conversation
TEAMCTX.EXE

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