> For users who access Kiro with Pro or Pro+ tiers once they are available, your content is not used to train any underlying foundation models (FMs). AWS might collect and use client-side telemetry and usage metrics for service improvement purposes. You can opt out of this data collection by adjusting your settings in the IDE. For the Kiro Free tier and during preview, your content, including code snippets, conversations, and file contents open in the IDE, unless explicitly opted out, may be used to enhance and improve the quality of FMs. Your content will not be used if you use the opt-out mechanism described in the documentation. If you have an Amazon Q Developer Pro subscription and access Kiro through your AWS account with the Amazon Q Developer Pro subscription, then Kiro will not use your content for service improvement. For more information, see Service Improvement.
Is there a way to confirm this works or do we just have to trust that settings will be honored?
consumer451 · 42m ago
You could place some unique strings in your code, and test it to see if they appear as completions in future foundation models? Maybe?
I am nowhere near being a lawyer, but I believe the promise would be more legally binding, and more likely to be adhered to, if money was exchanged. Maybe?
Clearly, companies view the context fed to these tools as valuable. And it certainly has value in the abstract, as information about how they're being used or could be improved.
But is it really useful as training data? Sure, some new codebases might be fed in... but after that, the way context works and the way people are "vibe coding", 95% of the novelty being input is just the output of previous LLMs.
While the utility of synthetic data proves that context collapse is not inevitable, it does seem to be a real concern... and I can say definitively based on my own experience that the _median_ quality of LLM-generated code is much worse than the _median_ quality of human-generated code. Especially since this would include all the code that was rejected during the development process.
Without substantial post-processing to filter out the bad input code, I question how valuable the context from coding agents is for training data. Again, it's probably quite useful for other things.
janstice · 11m ago
I suspect the product telemetry would be more useful - things like success of interaction vs requiring subsequent editing, success from tool use, success from context & prompt tuning parameters would be for valuable to the product than just feeding more bits into the core model.
consumer451 · 1h ago
There is company, maybe even a YC company, which I saw posting about wanting to pay people for private repos that died on the vine, and were never released as products. I believe they were asking for pre-2022 code to avoid LLM taint. This was to be used as training data.
This is all a fuzzy memory, I could have multiple details wrong.
NathanKP · 10h ago
Hello folks! I've been working on Kiro for nearly a year now. Happy to chat about some of the things that make it unique in the IDE space. We've added a few powerful things that I think make it a bit different from other similar AI editors.
In specific, I'm really proud of "spec driven development", which is based on the internal processes that software development teams at Amazon use to build very large technical projects. Kiro can take your basic "vibe coding" prompt, and expand it into deep technical requirements, a design document (with diagrams), and a task list to break down large projects into smaller, more realistic chunks of work.
I've had a ton of fun not just working on Kiro, but also coding with Kiro. I've also published a sample project I built while working on Kiro. It's a fairly extensive codebase for an infinite crafting game, almost 95% AI coded, thanks to the power of Kiro: https://github.com/kirodotdev/spirit-of-kiro
This, along with the "CHALLENGE.md" and "ROADMAP.md" document, is an incredibly cool way to show off your project and to give people a playground to use to try it out. The game idea itself is pretty interesting too.
It would be awesome if I ... didn't have to deal with AWS to use it. I guess maybe that might be a good use case for agentic coding: "Hey, Kiro - can you make this thing just use a local database and my Anthropic API key?"
Complaining aside though, I think that's just such a cool framework for a demo. Nice idea.
NathanKP · 5h ago
Thanks a lot! I plan to fork the project and make a generic version that runs entirely locally using your GPU to do everything. My early tests ran pretty well on NVIDIA 5070. So that's next on my project list to open source in my free time. The only thing more fun that building an AI agent, is using it to build your own ideas!
underlines · 4h ago
5070Ti user here: We are 150 people in a SME and most of our projects NDA for gov & defense clients absolutely forbid us to use any cloud based IDE tools like GitHub Copilot etc. Would love for this project to provide a BYOK and even Bring Your Own Inference Endpoint. You can still create licensing terms for business clients.
hedgehog · 4h ago
What models do you use that you've found to be powerful enough to be helpful?
postalcoder · 9h ago
I don't know if this is feedback for Kiro per se or more feedback for this category of applications as a whole, but I've personally noticed that the biggest barrier holding me back from giving an earnest look at new coding agents are the custom rules I've set up w/ my existing agents. I have extensively used Copilot, Continue, Cursor, Cline, Aider, Roo Code, and Claude Code. I've just finished porting my rules over to Claude Code and this is something I do not want to do again [even if it's as simple as dragging and dropping files].
Companies would benefit a lot by creating better onboarding flows that migrate users from other applications. It should either bring in the rules 1:1 or have an llm agent transform them into a format that works better for the agent.
NathanKP · 9h ago
You will be happy to find out that Kiro is quite good at this! One of my favorite features is "Steering Rules". Kiro can help you write steering rules for your projects, and the steering rules that it auto generates are actually super great for large projects. You can see some examples of auto generated steering files here in one of my open source projects: https://github.com/kirodotdev/spirit-of-kiro/tree/main/.kiro...
Also these steering rules are just markdown files, so you can just drop your other rules files from other tools into the `.kiro/steering` directory, and they work as is.
adastra22 · 6h ago
“I really don’t want to do X”
“Kirk is actually quite good at this: you just have to do X”
“…”
NathanKP · 5h ago
At the prompt: "I have extensively used Copilot, Continue, Cursor, Cline, Aider, Roo Code, and Claude Code. I do not want to move my files over again for Kiro [even if it's as simple as dragging and dropping files]. Do it for me"
Kiro will do it for you automatically.
adastra22 · 4h ago
And then you have two separate specifications of your intent, with the ongoing problems that causes. It’s not the same thing.
NathanKP · 4h ago
Yeah it would be nice if there was one way to specify the rules and intent, but you know how these things go: https://xkcd.com/927/
In all seriousness, I'm sure this will become more standardized over time, in the same way that MCP has standardized tool use.
I've long been interested in something that can gather lightweight rules files from all your subdirectories as well, like a grandparent rule file that inherits and absorbs the rules of children modules that you have imported. Something kind of like this: https://github.com/ash-project/usage_rules
I think over time there will be more and more sources and entities that desire to preemptively provide some lightweight instructive steering content to guide their own use. But in the meantime we just have to deal with the standard proliferation until someone creates something amazing enough to suck everyone else in.
helpfulContrib · 4h ago
Porting rules is one of the responsibilities of keeping them.
newman314 · 4h ago
It would sure be nice to have some standardized conventions around this. AGENTS.md etc. It seems insane to have to have multiple files/rules for essentially the same goals just for different tools.
tln · 2h ago
Thats the convention I am using.
My CLAUDE.md and GEMINI.md both just say "See AGENTS.md".
mkw5053 · 2h ago
Same
seunosewa · 2h ago
How about:
Creating a MCP server that all the agents are configured to retrieve the rules from?
esafak · 5h ago
There should be a standard rule format in a standard place, like ~/.config/llms/rules.md
brulard · 4h ago
this. We need a common file for all these tools. It's not like they can not read the format of each other.
apwell23 · 15m ago
> have an llm agent transform them into a format that works better for the agent.
you can do this today though.
theshrike79 · 7h ago
I just have a “neutral” guidance markdown setup written in a repo.
Then I add it as a git submodule to my projects and tell whatever agents to look at @llm-shared/ and update its own rule file(s) accordingly
sys13 · 6h ago
Agents.md is at least used by both codex and GitHub copilot. VSCode has its own thing for instruction files and Claude.md is also its own thing :(
ffsm8 · 9h ago
Or a proper standard like MCP was for agentic tool use, this time for context setup...
chrisweekly · 7h ago
Problems w auth / security in MCP skeeve me out. For that reason, I really don't want to invest in workflows that depend on MCP and have steered clear. But I'd be grateful for well-informed comments / advice on that front.
As for a hypothetical new "context setup" protocol like you posit, I suspect it'd benefit from the "cognitive tools" ideas in this awesome paper / project: <https://github.com/davidkimai/Context-Engineering>
^ inspiring stuff
re5i5tor · 6h ago
Not Kiro related, but do your Claude Code version of rules end up as CLAUDE.md files in various locations?
namanyayg · 9h ago
in the early days of building something like that, would love to talk for 10 minutes and get your advice if you have the time? I couldn't find your email but mine is in my profile.
charlysl · 9h ago
Is it something similar to Harper Reed's "My LLM codegen workflow atm"?
Actually yes! I saw this post some months ago, and thought to myself: "Wow this is really close to what we've been building". Kiro uses three files though: requirements, design, and then tasks. The requirements doc is a bunch of statements that define all the edge cases you might not have originally thought of. Design looks at what is currently in the code, how the code implementation differs from the requirements, and what technical changes need to happen to resolve the difference. Then tasks breaks the very large end to end development flow up into smaller pieces that an LLM can realistically tackle. The agent then keeps track of it's work in the tasks file.
Realistically, I don't think that Harper's statement of "I get to play cookie clicker" is achievable, at least not for nontrivial tasks. Current LLM's still need a skilled human SDE in the loop. But Kiro does help that loop run a lot smoother and on much larger tasks than a traditional AI agent can tackle.
charlysl · 7h ago
Thank you, I will certainly check this out because this is something I've been sort of doing, manually, but I am still struggling to get the right workflow.
This recent OpenAI presentation might resonate too then:
Prompt Engineering is dead (everything is a spec)
In an era where AI transforms software development, the most valuable skill isn't writing code - it's communicating intent with precision. This talk reveals how specifications, not prompts or code, are becoming the fundamental unit of programming, and why spec-writing is the new superpower.
Drawing from production experience, we demonstrate how rigorous, versioned specifications serve as the source of truth that compiles to documentation, evaluations, model behaviors, and maybe even code.
Just as the US Constitution acts as a versioned spec with judicial review as its grader, AI systems need executable specifications that align both human teams and machine intelligence. We'll look at OpenAI's Model Spec as a real-world example.
Have you considered a fourth file for Implemented such that Spec = Implemented + Design?
It would serve both as a check that nothing is missing from Design, and can also be an index for where to find things in the code, what architecture / patterns exist that should be reused where possible.
And what about coding standards / style guide? Where does that go?
theusus · 8h ago
Why build an editor and not a CLI. VS code is really slow for me and I would have preferred a CLI.
> For users who access Kiro with Pro or Pro+ tiers once they are available, your content is not used to train any underlying foundation models (FMs). AWS might collect and use client-side telemetry and usage metrics for service improvement purposes. You can opt out of this data collection by adjusting your settings in the IDE. For the Kiro Free tier and during preview, your content, including code snippets, conversations, and file contents open in the IDE, unless explicitly opted out, may be used to enhance and improve the quality of FMs. Your content will not be used if you use the opt-out mechanism described in the documentation. If you have an Amazon Q Developer Pro subscription and access Kiro through your AWS account with the Amazon Q Developer Pro subscription, then Kiro will not use your content for service improvement. For more information, see Service Improvement.
https://kiro.dev/faq/
1. Open Settings in Kiro.
2. Switch to the User sub-tab.
3. Choose Application, and from the drop-down choose Telemetry and Content.
4. In the Telemetry and Content drop-down field, select Disabled to disable all product telemetry and user data collection.
source: https://kiro.dev/docs/reference/privacy-and-security/#opt-ou...
I am nowhere near being a lawyer, but I believe the promise would be more legally binding, and more likely to be adhered to, if money was exchanged. Maybe?
The "Amazon Q Developer Pro" sub they mention appears to be very inexpensive. https://aws.amazon.com/q/pricing/
Clearly, companies view the context fed to these tools as valuable. And it certainly has value in the abstract, as information about how they're being used or could be improved.
But is it really useful as training data? Sure, some new codebases might be fed in... but after that, the way context works and the way people are "vibe coding", 95% of the novelty being input is just the output of previous LLMs.
While the utility of synthetic data proves that context collapse is not inevitable, it does seem to be a real concern... and I can say definitively based on my own experience that the _median_ quality of LLM-generated code is much worse than the _median_ quality of human-generated code. Especially since this would include all the code that was rejected during the development process.
Without substantial post-processing to filter out the bad input code, I question how valuable the context from coding agents is for training data. Again, it's probably quite useful for other things.
This is all a fuzzy memory, I could have multiple details wrong.
In specific, I'm really proud of "spec driven development", which is based on the internal processes that software development teams at Amazon use to build very large technical projects. Kiro can take your basic "vibe coding" prompt, and expand it into deep technical requirements, a design document (with diagrams), and a task list to break down large projects into smaller, more realistic chunks of work.
I've had a ton of fun not just working on Kiro, but also coding with Kiro. I've also published a sample project I built while working on Kiro. It's a fairly extensive codebase for an infinite crafting game, almost 95% AI coded, thanks to the power of Kiro: https://github.com/kirodotdev/spirit-of-kiro
This, along with the "CHALLENGE.md" and "ROADMAP.md" document, is an incredibly cool way to show off your project and to give people a playground to use to try it out. The game idea itself is pretty interesting too.
It would be awesome if I ... didn't have to deal with AWS to use it. I guess maybe that might be a good use case for agentic coding: "Hey, Kiro - can you make this thing just use a local database and my Anthropic API key?"
Complaining aside though, I think that's just such a cool framework for a demo. Nice idea.
Companies would benefit a lot by creating better onboarding flows that migrate users from other applications. It should either bring in the rules 1:1 or have an llm agent transform them into a format that works better for the agent.
Also these steering rules are just markdown files, so you can just drop your other rules files from other tools into the `.kiro/steering` directory, and they work as is.
“Kirk is actually quite good at this: you just have to do X”
“…”
Kiro will do it for you automatically.
In all seriousness, I'm sure this will become more standardized over time, in the same way that MCP has standardized tool use.
I've long been interested in something that can gather lightweight rules files from all your subdirectories as well, like a grandparent rule file that inherits and absorbs the rules of children modules that you have imported. Something kind of like this: https://github.com/ash-project/usage_rules
I think over time there will be more and more sources and entities that desire to preemptively provide some lightweight instructive steering content to guide their own use. But in the meantime we just have to deal with the standard proliferation until someone creates something amazing enough to suck everyone else in.
My CLAUDE.md and GEMINI.md both just say "See AGENTS.md".
Creating a MCP server that all the agents are configured to retrieve the rules from?
you can do this today though.
Then I add it as a git submodule to my projects and tell whatever agents to look at @llm-shared/ and update its own rule file(s) accordingly
As for a hypothetical new "context setup" protocol like you posit, I suspect it'd benefit from the "cognitive tools" ideas in this awesome paper / project: <https://github.com/davidkimai/Context-Engineering>
^ inspiring stuff
https://harper.blog/2025/02/16/my-llm-codegen-workflow-atm/
Realistically, I don't think that Harper's statement of "I get to play cookie clicker" is achievable, at least not for nontrivial tasks. Current LLM's still need a skilled human SDE in the loop. But Kiro does help that loop run a lot smoother and on much larger tasks than a traditional AI agent can tackle.
This recent OpenAI presentation might resonate too then:
Prompt Engineering is dead (everything is a spec)
In an era where AI transforms software development, the most valuable skill isn't writing code - it's communicating intent with precision. This talk reveals how specifications, not prompts or code, are becoming the fundamental unit of programming, and why spec-writing is the new superpower.
Drawing from production experience, we demonstrate how rigorous, versioned specifications serve as the source of truth that compiles to documentation, evaluations, model behaviors, and maybe even code.
Just as the US Constitution acts as a versioned spec with judicial review as its grader, AI systems need executable specifications that align both human teams and machine intelligence. We'll look at OpenAI's Model Spec as a real-world example.
https://youtu.be/8rABwKRsec4?si=waiZj9CnqsX9TXrM
Have you considered a fourth file for Implemented such that Spec = Implemented + Design?
It would serve both as a check that nothing is missing from Design, and can also be an index for where to find things in the code, what architecture / patterns exist that should be reused where possible.
And what about coding standards / style guide? Where does that go?