You have Cursor. You have Claude Code. Maybe Codex. Each one can write code. None of them coordinate. You're the one deciding which agent gets which task, pasting context between tools, resolving the conflicts when two agents touched the same file. That's not a workflow — that's manual coordination with extra steps.
AI agent orchestration for coding means the agents work together, in the right order, with the right context, against a spec that was generated from your actual codebase. Tekk.coach is that orchestration layer — built specifically for the coding workflow, not retrofitted from a general-purpose agent framework.
How Tekk.coach Orchestrates Your Coding Agents
The core problem with agent orchestration for coding isn't execution — it's planning. Every major coding agent (Cursor, Codex, Claude Code, Gemini) assumes the spec already exists. They need structured, codebase-grounded inputs to execute correctly. They receive paragraphs.
Tekk solves this with a structured planning workflow that runs before any agent is dispatched. The agent reads your codebase first — using semantic search, file search, regex lookup, directory browsing, and full repository profiling. It asks 3-6 questions specific to what it found in your code. It presents architecturally distinct options when choices genuinely matter. Then it streams a complete spec into your task editor as an editable working document.
That spec includes subtasks with explicit acceptance criteria, file references, and dependency links. The dependency ordering is the key: which subtasks must complete before which others begin. This dependency graph is what makes parallel execution safe — independent subtasks run simultaneously, dependent subtasks sequence correctly.
Multi-agent execution dispatch — where Tekk routes those subtasks to appropriate agents (Cursor for code execution, Gemini for design-first tasks, Claude Code for MCP-capable tasks) in dependency-ordered parallel waves, all merging to a single feature branch — is coming next.
Today, Tekk's planning workflow, kanban board, review mode, and web research during planning are live. The execution dispatch layer is where this goes next.
Key Benefits
The spec that makes agents effective. Your agent is only as good as its inputs. Tekk generates inputs that are dramatically better than a paragraph — codebase-grounded, acceptance-criteria-complete, file-referenced specs that your coding agents can actually execute against without flailing.
Parallel waves, not sequential queues. Independent subtasks run simultaneously. Dependent subtasks sequence correctly. The right architecture prevents the cascade failures that come when agents edit related files without coordination.
No more manual routing. You stop deciding which agent gets which task. Tekk matches subtask requirements to agent capabilities — execution tasks to Cursor, design-first work to Gemini, MCP-capable tasks to Claude Code. (Coming next.)
BYO agents. Keep your subscriptions. Cursor, Codex, Claude Code, Gemini — connected via OAuth. You're not replacing your agents. You're coordinating them without building coordination infrastructure yourself.
One PR for human review. All agent work merges to a single shared feature branch. You review once. One clean diff, not five separate PRs from five separate agent sessions.
How It Works
Step 1: Connect your codebase. Link GitHub, GitLab, or Bitbucket. Tekk's semantic search indexes your repository so every planning question and every spec subtask references actual code — not generic patterns.
Step 2: Describe the feature. Plain language. "Add Stripe subscription billing." "Build a semantic search endpoint." "Refactor the auth layer to support multi-tenancy." The agent handles the rest.
Step 3: Answer informed questions. The agent asks 3-6 questions grounded in what it found in your code. Not templates. Questions that surface actual architectural constraints and trade-off points in your specific system.
Step 4: Review and edit the spec. Complete spec streams into the BlockNote editor in real-time. TL;DR, Building/Not Building scope, subtasks with acceptance criteria and file references, dependency ordering, risk-flagged assumptions, validation scenarios. Edit anything before execution.
Step 5: Execute with your agents. (Coming next.) Click Execute. Tekk decomposes approved subtasks by dependency, groups independent subtasks into parallel execution waves, and dispatches each to the right agent via OAuth. All jobs push to one shared feature branch. One PR for your review.
Who This Is For
Developers running multiple agents and manually routing work between them. If you're copy-pasting specs between chat windows, deciding which agent to use for each subtask, and managing merge conflicts from simultaneous agent sessions — Tekk removes all of that.
Founders and small teams without dedicated engineering coordination. You can't afford to spend half your day being the coordinator between your AI agents. Tekk is the coordination layer you don't have to build.
Engineers who've been burned by vague prompts. You know the failure mode: vague task, plausible-sounding code, wrong architecture, rework. Tekk's codebase-first planning workflow produces specs that prevent this at the source.
Not for senior architects who already know exactly how to spec every feature and just need an execution agent. Not for enterprise teams that need Jira-style workflow governance. Tekk is for builders who want to move fast with high precision and zero ceremony.
What Is AI Agent Orchestration for Coding?
AI agent orchestration for coding is the coordination of multiple AI coding agents — Cursor, Codex, Claude Code, Gemini — to execute a software feature with dependency-ordered parallelism. The orchestration layer sits above the coding agents and handles: task decomposition from a structured spec, dependency graph analysis, agent routing by capability, parallel wave execution, and branch/PR management.
The critical distinction from general AI orchestration is that coding requires a planning phase before execution. The quality of code produced by any agent is bounded by the quality of the spec it receives. Orchestrating bad inputs faster doesn't help — you need the planning layer to generate good inputs first.
This two-layer architecture — planning layer (Tekk) + execution layer (Cursor, Codex, Claude Code) — is the correct model. It mirrors how effective engineering teams work: you spec before you build, you sequence before you parallelize.
Ready to Try Tekk.coach?
Stop being the coordinator between your AI agents. Connect your repo, describe the feature, and get a codebase-grounded spec that your coding agents can actually execute against — in minutes.