Coding agents flail when they execute without a plan. You type a sentence, the agent does something, and now you're debugging code that almost works. Tekk fixes this at the source.

Connect your repo. Tekk's loops read what changed in your code and bring you proposals; each one you greenlight becomes a spec with acceptance criteria before a single line of code runs. Then Claude Code, Codex, or Cursor picks the spec up through the Tekk MCP server and executes against something real.

Plan first. Execute once. Skip the rework.

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How Tekk.coach Does Plan and Execute

Most developers give their coding agent a sentence or two. The agent executes fast — and wrong. It doesn't know your conventions, which files to touch, or which architectural decisions you've already made. The output looks plausible for about five minutes.

Tekk is the plan half of plan and execute. Twelve loops watch your repository — Security, Backend, Payments, Performance, Testing and seven more. When your code changes, one wakes, reads what changed, and follows it to what it touches. It finds your patterns, your dependencies, your actual code. Then it brings at most one proposal, pointing at the files it concerns.

You greenlight it or decline it with a reason. Greenlit, it becomes a spec — not a chat message you paste into Cursor, but a document on your board with what to build, why, acceptance criteria, and a build-order checklist. Prefer to plan something yourself? Write the spec by hand; it lands on the same board.

You review it. You edit it. Then your coding agent reads it over MCP and builds it.

That spec is the difference between an agent that ships and one that flails.

The execute half is wired in too. Your agent works the board through the Tekk MCP server, and the pull request that says Closes TEK-123 completes the spec when it merges — once its checklist is done.

Key Benefits

Your coding agent gets a real spec, not a paragraph. Most agent failures trace back to weak input. As JetBrains notes, language models are excellent at pattern completion but need structured context — a detailed spec is exactly that context. Tekk's specs carry acceptance criteria and a build-order checklist, and a loop's spec points at the files it concerns. Your agent has what it needs to execute correctly instead of guessing.

The plan is grounded in your actual codebase. Loops read your repo before proposing anything. Every proposal references your specific files and patterns — not what a generic version of your stack probably looks like.

Done is defined before anyone writes code. Acceptance criteria and a checklist say when the spec is finished. A merge only completes it when the checklist agrees; otherwise it stays in progress with the open items counted.

The spec lives in a persistent workspace, not a chat thread. Tekk is not a chat interface. Each spec lives on a board, moves from todo to in progress to completed, and shows the pull requests that built it. Context doesn't evaporate between sessions. For teams planning across multiple features or a full roadmap, ai project planning keeps the big picture organized alongside the feature-level specs.

How It Works

1. Connect your repository Connect your repo and turn on the loops you want. This is what they read before they do anything else.

2. A loop wakes Your code changed, Sentry fired, or part of an area went unexamined too long. The loop that owns it wakes up.

3. The loop reads your codebase It reads what changed and follows it to what it touches — the way a senior engineer returning to a codebase does — then works one method from its shelf of skills. It doesn't re-audit the whole repository every time.

4. One proposal If it finds something real, it brings one proposal that explains what it noticed and what it would do. If not, it records an honest negative and moves on.

5. You greenlight or decline Greenlight it and it becomes a spec on your board. Decline it with a reason and the loops learn what's noise for your project. You can also write a spec by hand.

6. The spec What to build, why, acceptance criteria, and a build-order checklist. This is the document your coding agent executes against.

7. Execute with your coding agent Claude Code, Codex, or Cursor reads the spec through the Tekk MCP server and builds it. The PR that says Closes TEK-123 completes the spec when it merges. Your plan is done. Execution is their job. Teams running several agents at once can have the MCP server plan a collision-free batch — the dependency-aware side of ai agent orchestration, without a separate tool.

Who This Is For

Developers using Cursor, Claude Code, or Codex who are tired of rework. You've been burned by agents executing half-understood instructions. You've debugged plausible-looking code that turned out to be wrong in ways that took an hour to trace. You want to stop that.

Solo founders and small teams without dedicated architects. You're touching domains where you don't have deep expertise — auth systems, data pipelines, payment integrations. Tekk's Security, Backend, and Payments loops fill the knowledge gap during planning, not after you've already built the wrong thing.

Small teams (1–10 people) who need structured specs but don't want the overhead of PRDs, alignment meetings, and backlog grooming. Connect a repo, greenlight a proposal, get a spec. That's the whole process.

Tekk is not the right fit if you're a senior architect who already writes airtight specs from memory and reviews every change yourself. Or if you need enterprise workflow governance: approval chains, custom Jira-style process configuration. Tekk is opinionated and lightweight by design.

What Is Plan-and-Execute?

Plan-and-execute is a two-phase approach to AI-assisted software development. Phase one: produce a complete, written plan. Phase two: execute it. The planning phase is separate — it reasons about the codebase without touching it. Only when the plan is reviewed and approved does any code run.

This isn't a new idea in software engineering. Design-before-implementation has been standard advice for decades. What AI coding agents changed is the cost of skipping it. Give Cursor or Claude Code a one-sentence prompt and they execute immediately, without understanding your conventions, your constraints, or the decisions you haven't made yet. The output looks right and then falls apart in ways that waste hours.

The practice got formal names in 2025. ThoughtWorks called spec driven development "one of the most important practices to emerge in 2025." AWS Kiro built an explicit Specify → Plan → Execute flow into their IDE. GitHub released an open-source Spec Kit. Traycer staked out "spec-first development" as their core phrase. Plan first development started showing up across developer blogs as people documented what was actually working for them.

What all of these have in common: the spec is the first thing you build with AI. Not the code. The spec IS the first artifact.