Traycer AI - Plan-first AI coding for real codebases
Traycer helps devs plan-first, code-faster with spec‑driven development. It breaks down high-level intents into structured plans, hands off to your favorite AI agent, then verifies changes so your large codebase stays solid.
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Traycer AI
Hey Product Hunt! 👋 We’re building Traycer, the spec layer for coding agents.
We built Traycer after watching LLM‑assisted code “work once” and then fall apart in real repos. Traycer plans like a senior engineer, implements with your favorite agent, and verifies changes so you can ship with confidence.
Why we’re building this
Most agentic coding tools jump straight to “code.” That works for small snippets, but in real repos it’s easy to lose context, skip steps, or ship regressions. Traycer separates planning from execution, so your agents stay aligned with what actually needs to happen.
How it works
1. Specification first. You describe the change; Traycer creates phases and a concrete plan (what to touch, why, and in what order).
2. Execute anywhere. Hand off the plan to Cursor, Claude Code, Windsurf—whatever you already use. We don’t replace your agent; we upgrade it with a better spec.
3. Verify & iterate. When the agent proposes changes, Traycer verifies them against the plan, highlights gaps, detects regressions, and suggests corrections. Rinse and repeat until it’s solid.
What this means for you
* Less prompt wrangling, more predictable outcomes.
* Safer changes in large or unfamiliar codebases.
* A clear path from intent -> plan -> diff -> verification.
Who it’s for
Built for developers who want precision and control while harnessing the power of agentic coding.
We keep our roadmap public and would love your feedback. Drop ideas in the comments; we’re around to answer questions and ship improvements. 🚀
— The Traycer team
Product Hunt
@tanveer_gill1 cool launch! I am a heavy user of @Claude Code. Would love to learn why I should consider Traycer! Claude Code has plan vs coding separation with Plan Mode.
@tanveer_gill1 Great product but I would like to understand how is it different from Kiro, because Kiro was published with the exact same intent. But the only problem I face with Kiro is that it is unnecessarily takes too much time to plan and then execute. Even after waiting for so long if it doesn't do the required thing, it feels like a big waste of time.
Love this idea. I’ve been working on a similar problem. How are you handling context across multiple files or refactors? Is it persistent or regenerated per run?
Traycer AI
@lak7 Glad to know that you liked the idea and have also been working around the same problem.
We have used different techniques to include only relevant files in the context and to make iterations on the proposed plans easier, enabling users to quickly generate a new version based on their changes.
@masikh yes, you can. In fact you can use any AI tool. Because they offer to simply click and run in claude in the terminal (or codex, gemini, etc) but also you can copy the prompt and execute it anywhere.
Sellkit
Very cool. Sounds like a real safeguard for big projects. Does it integrate with GitHub PRs for validation?
Traycer AI
@roozbehfirouz Thanks so much for the kind words! 🙏
You’re spot on — one of our main goals was to make collaboration on large projects smoother and safer. Right now, we support in-IDE review and validation workflows, but not GitHub PR reviews yet. Tools like @CodeRabbit are already doing an amazing job in that space.
Humans in the Loop
@roozbehfirouz spot on. there are great products for rapid prototyping and small codebases. however, larger codebases are still a challenge for most of them.
@Traycer AI just fixed it.
I've been using it for several weeks now, and I can confirm this is the current workflow that works for me for vibe coding. Specially for new or big features.
Traycer AI
@leech that's great! We always love to hear from our users
How is this different from Kiro?
Traycer AI
@ace_at_neuralicity Traycer is a deep research agent. Traycer's planning goes much deeper than Kiro. A single plan request fans out to multiple models under the hood, like Sonnet-4.5, GPT-5-Codex. Traycer uses techniques like sub-agents and large file summarization to minimize context pollution, unlike most products that use a single agent in a loop.
In addition to planning, Traycer would verify each changeset from the agent, ensuring it follows your intent and is free of any regressions.
It does not require you to switch IDEs :)
Traycer AI
@rbluena thank you 🙌
Lobe
Definitely found that the quality of the plan makes or breaks the implementation!
Traycer AI
Yes! Planning and Verification are the two main bottlenecks in leveraging coding agents effectively. Traycer is attacking these bottlenecks head on!
Humans in the Loop
"AI code is fast; AI planning makes it deliberate."
Remember this discussion on the vibe coding process with @gabe: Is it best to jump straight to code or plan it out first?
It feels like @Traycer AI fixed it and pushed vibe coding to the next level. We're no longer supervisors using coding agents as junior developers, enhancing prompts and fine-tuning outputs. We're now conductors, guiding AI agents that scope, execute, review, and shape production-ready apps.
S/O to the team, keep up the great work 👏👏
Traycer AI
@fmerian Incredible reflection—thank you!
We love how you put it: from supervisors to conductors. That shift is precisely what we hope to unlock: AI that collaborates with intent, not just speed.
Cool product- can users edit the plans?
Traycer AI
@yichen_guo1 Yes, users can iterate the plan with the help of AI until satisfied.