Most engineers using Cursor, Codex, or Claude Code hit the same wall: the agents are capable, but nothing coordinates them. Tasks conflict. Context gets lost. You become the orchestrator — manually routing work, resolving dependencies, tracking progress across chat windows. As one practitioner put it, running multiple agents simultaneously is like walking multiple dogs at once — if you don't know where you're going, you'll get tangled. That's not orchestration. That's overhead.

Tekk.coach doesn't route work between agents for you. It gives them a board to coordinate on: twelve loops find the work in your code and bring proposals, greenlit proposals become specs with files and dependencies, and through the Tekk MCP server your own agents plan collision-free batches and run them as parallel sessions.

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Key Benefits

Your agents get specs, not paragraphs. Every coding agent produces better output when given precise, codebase-grounded inputs. Tekk's specs — written by its loops from what changed in your code, or by you — are what make your agents effective. The quality of orchestration is bounded by the quality of the inputs.

Dependency ordering built in. A feature becomes a parent spec with one Sub-task per buildable part, and dependsOn is a hard gate: a spec waiting on a prerequisite can't be batched until that prerequisite is genuinely finished. The API contract lands before the frontend component; the migration before the service layer. This is the structural discipline that prevents agent cascade failures — a problem a comprehensive arXiv survey on multi-agent orchestration identifies as the primary failure mode in uncoordinated multi-agent systems.

Scope enforcement by default. Every spec says what it builds and what it doesn't, and touches declares the files it will modify — so two specs that would edit the same code never land in the same batch. Scope creep is structurally prevented, not aspirationally hoped for.

One board for finding and tracking. Goals aim the loops; proposals wait for your call; specs move To Do / In Progress / Done, and a merged closing PR moves them for you. No more scattered markdown files across chat windows.

BYO agents. No lock-in. Claude Code, Codex, Cursor — any MCP-capable client connects to the Tekk MCP server. You keep your existing agent subscriptions, and your agents do the building. Platforms like Cursor are scaling autonomous agent execution and Codex now supports parallel subagents — Tekk's board works with all of them.

How It Works

Step 1: Connect your codebase. Link your GitHub repository and turn on the loops you want. They start reading on your next change — the files that changed, and what those files feed into.

Step 2: Let the loops find the work — or describe it yourself. Twelve loops — Security, Payments, Reliability, AI engineering and more — wake when your code changes or Sentry fires, and each run brings at most one proposal. You can still write a spec by hand, in plain language: "Add magic link authentication."

Step 3: Greenlight or decline. Accept a proposal and it becomes a spec on your board — what changes, which files, acceptance criteria. Decline it with a reason and the loops learn what's noise for your project.

Step 4: Structure it for parallel work. Split a feature into Sub-tasks, each with its own touches (the files it will modify) and dependsOn (what must finish first). Your agent can do this over MCP when it creates the spec.

Step 5: Run the fleet from your agent. In Claude Code, blitz reads your open specs, works out the biggest collision-safe batch, and opens a coding session per spec; fleet_status shows what each agent is doing. Each Sub-task carries its own PR. A PR that says Closes TEK-123 completes its spec on merge once the checklist is done, and the parent completes when its children do.

Who This Is For

Founders and solo builders shipping with AI coding agents. You're using Cursor or Claude Code but you're manually managing what gets built and when. That's coordination overhead you shouldn't be carrying. Put it on a board your agents read and run.

Small engineering teams (1–10 people) without a dedicated architect. You're touching domains — auth, payments, AI pipelines — where you don't have deep expertise. Tekk's specialist loops — Security, Payments, AI engineering — read every change and bring you what a specialist would have caught. Those findings and the parallel run live on the same board.

Developers who are tired of rework. The third time you rebuild the same feature because the spec was vague is the last time. Tekk's specs are grounded in your actual codebase, and they close only when their checklist is done.

It's not for enterprise teams that need Jira-style workflow governance, custom approval chains, or 47 sidebar items. Tekk is opinionated and lightweight by design.

What Is AI Agent Orchestration?

AI agent orchestration is the coordination of multiple AI agents — each with distinct capabilities and tool access — to accomplish complex tasks no single agent can complete alone. An orchestrator decomposes a complex goal into subtasks, assigns them to appropriate worker agents, manages execution dependencies, and aggregates results.

In software development, this pattern has become essential because modern codebases are too large and complex for single-agent loops. Gartner predicts 40% of enterprise applications will integrate task-specific AI agents by end of 2026, up from less than 5% in 2025. A feature might require a security review, API design, frontend implementation, database migration, and test generation — each suited to a different specialized agent.

The field has two distinct layers. The execution layer consists of the coding agents themselves: Cursor, Codex, Claude Code, Gemini. The orchestration layer sits above them — decomposing tasks, routing work, managing dependencies, tracking progress. The ai agent workflow that connects these two layers is what determines whether agents execute with precision or produce expensive rework. As Addy Osmani writes in The Code Agent Orchestra, the hard problem isn't making agents smarter — it's making them work together. Most developers have execution agents. Few have an orchestration layer. That gap is where rework, conflicts, and manual coordination overhead live.