AI Agent for Software Developers
You're already using Cursor, Claude Code, or Codex. They work — until they don't. The agent builds something, it's not quite right, you explain again, it tries again. Rework. The problem isn't the agent. It's what you gave it.
Tekk.coach is the planning agent that sits above your coding agent. It reads your actual codebase, asks informed questions, researches what it doesn't know, and produces a spec your coding agent can execute without flailing. You tell Tekk what to build. Tekk figures out exactly how. Then your agent builds it.
How Tekk.coach Works for Developers
Most developers using AI coding agents hit the same wall: the agent is capable but the output keeps missing. You ask for authentication, it builds the wrong one. You ask for an API integration, it guesses at your data model. You ask for a feature, it creates files in the wrong place. The agent doesn't know your codebase. You do — but translating that into a prompt that actually works is its own skill.
Tekk solves this at the source. Before generating anything, the agent connects to your repository (GitHub, GitLab, or Bitbucket) and reads it — semantic search via embeddings, file search, regex, full directory browsing, and repo profiling that understands your stack, patterns, and existing architecture. It asks 3-6 questions grounded in what it found, not generic boilerplate. If you're building something outside your expertise, it searches the web for current best practices and folds that knowledge into your spec.
The output isn't a chat message. It's a living document — a structured spec streamed in real-time into an editable editor. Every plan includes a TL;DR, explicit Building / Not Building scope boundaries, subtasks with acceptance criteria and file references, assumptions with risk levels, and validation scenarios. That's what you hand to your coding agent. That's why it ships.
If you're building with Claude Code, Cursor, Codex, or Gemini, Tekk is the planning layer that makes them dramatically more effective. It doesn't replace them — it makes every job they run start from a better position.
Key Benefits
Your coding agent stops flailing. Agents fail when they don't know your codebase and don't have a clear spec. Tekk handles both. The agent reads your repo before asking a single question. The spec it produces has file references, acceptance criteria, and scope boundaries. Your coding agent knows exactly what to build and where.
No more specs lost in chat threads. Plans stream into a persistent, editable document — not a chat message that disappears. Every task lives on a kanban board with its full planning session attached. You can read it, edit it, and hand it to your agent days later.
Build confidently outside your expertise. Implementing an AI agent? A data pipeline? A payment integration? Tekk researches the domain during your planning session, evaluates approaches against your specific codebase, and surfaces what you don't know before your coding agent starts writing code you'll have to redo.
Explicit scope protection on every task. Every plan has a "Not Building" section — what's explicitly out of scope. That's the conversation you needed to have with yourself before giving the agent a vague brief. Scope creep disappears when scope is defined before execution starts.
Expert review without a senior engineer. Run a security review, architecture review, or performance review on your codebase at any time. Tekk reads your actual code, searches for current best practices, and tells you what to fix — grounded in your specific stack, not generic checklists.
How It Works
Step 1: Connect your repo. Link GitHub, GitLab, or Bitbucket via OAuth. Takes 30 seconds. Tekk gets read access to your codebase — that's all it needs.
Step 2: Describe what you're building. Create a task. Describe the feature, bug, or integration in plain language. You don't need to write the spec — that's what Tekk is for.
Step 3: Tekk reads the codebase and asks questions. The agent searches your repository — semantically, by file, by regex. It understands your stack, your patterns, your existing architecture. Then it asks 3-6 questions grounded in what it found. If the domain is unfamiliar, it searches the web and brings back current best practices.
Step 4: You get options (when they matter). For complex decisions with real tradeoffs — architecture choices, integration approaches, data model options — Tekk presents 2-3 distinct paths with honest tradeoffs. You pick one.
Step 5: The spec is written. A complete, codebase-grounded specification streams into your task editor. TL;DR, scope boundaries, subtasks with acceptance criteria and file references, assumptions with risk levels, validation scenarios. This is the spec your AI coding agent needs to execute correctly.
Step 6: Hand it to your coding agent. Copy the spec to Cursor, Claude Code, or Codex. Or wait for Tekk's execution layer (coming next) to dispatch it directly. Your agent runs from a spec that fits your codebase — not a paragraph that doesn't.
Who This Is For
Developers who are already using AI coding agents and hitting friction. You use Cursor or Claude Code every day. They're part of your workflow. But complex features keep coming out wrong, or you spend as much time fixing as building. The bottleneck isn't the agent — it's the spec you're giving it. Tekk closes that gap. You'll spend less time explaining what you meant and more time reviewing what the agent built correctly the first time.
Developers building outside their expertise. You're a competent engineer but you haven't built this particular thing before — an AI integration, a caching layer, a search pipeline, a payment flow. Without Tekk: hours of research, a rough spec, and hope. With Tekk: the agent reads your codebase, researches the domain, and produces a spec that covers what you don't know yet. You go into execution knowing the architecture is sound.
Solo developers and small teams without senior coverage. No architect on call. No one to review before you execute. AI coding agents are your team. Tekk acts as the senior engineer in the planning session — interrogating assumptions, defining scope, surfacing risks, and producing a spec the team (you + your agents) can execute with confidence.
Tekk is not the right fit if you're a senior architect who already writes tight specs and knows exactly what to hand your agents. If you've solved the planning problem, you don't need it. But if the bottleneck is figuring out what to build and how to say it precisely — Tekk is built for you.
What Is an AI Agent for Developers?
An AI agent for software developers is a system that can take a task, understand context, make decisions, and act — without constant human direction at each step. Unlike a code autocomplete tool (which reacts to a single prompt), an AI agent reasons across multiple steps, remembers context, uses tools like code search or web browsing, and iterates toward a goal.
In 2026, the dominant coding agents — Claude Code, Cursor, Codex, GitHub Copilot with agent mode — operate at the repository level. They can read multiple files, make cross-file changes, run tests, and iterate. 55% of engineers use AI agents regularly. 70% use two to four tools simultaneously.
What's emerged as the real differentiator isn't which agent you use — it's how clearly you specify the task. Agents that receive vague, decontextualized instructions produce incorrect or incomplete output. The developers shipping consistently with AI agents are the ones who've solved the specification problem, not the ones who switched to a newer model. The ai coding assistant for developers that matters most might not be the one writing the code — it might be the one planning what the code should do.
Ready to Ship Without Rework?
Your coding agent is only as good as its spec. Give it a codebase-grounded plan — one that knows your stack, defines the scope, and has acceptance criteria on every subtask. That's what Tekk produces.
Connect your repo and run your first planning session free. No PRDs. No alignment meetings. Just a spec that works.