Amazon Web Services (AWS) has introduced Kiro powers, a system that allows software developers to give their AI coding assistants instant, specialized expertise in specific tools and workflows — addressing what the company calls a fundamental bottleneck in how AI agents operate today.
AWS announced Kiro powers at its annual re:Invent conference in Las Vegas. The capability marks a departure from how most AI coding tools work today. Typically, these tools load every possible capability into memory upfront — a process that burns through computational resources and can overwhelm the AI with irrelevant information. Kiro powers takes the opposite approach, activating specialized knowledge only at the moment a developer actually needs it.
"Our goal is to give the agent specialized context so it can reach the right outcome faster — and in a way that also reduces cost," Deepak Singh, VP of developer agents and experiences at Amazon, told VentureBeat in an exclusive interview.
The launch includes partnerships with nine technology companies: Datadog, Dynatrace, Figma, Neon, Netlify, Postman, Stripe, Supabase and AWS's own services. Developers can also create and share their powers with the community.
Kiro powers comes amidst growing tension in the AI development tool market.
Modern AI coding assistants rely on Model Context Protocol (MCP) to connect with external tools and services. When a developer wants their AI assistant to work with Stripe for payments, Figma for design and Supabase for databases, they connect MCP servers for each service.
The problem: Each connection loads dozens of tool definitions into the AI's working memory before it writes a single line of code. According to AWS documentation, connecting just five MCP servers can consume more than 50,000 tokens — roughly 40% of an AI model's context window — before the developer even types their first request.
Developers have grown increasingly vocal about this issue. Many complain that they don't want to burn through their token allocations just to have an AI agent figure out which tools are relevant to a specific task. They want to get to their workflow instantly — not watch an overloaded agent struggle to sort through irrelevant context.
This phenomenon, which some in the industry call "context rot," leads to slower responses, lower-quality outputs and significantly higher costs — since AI services typically charge by the token.
Kiro powers addresses this by packaging three components into a single, dynamically-loaded bundle.
The first is a steering file, POWER.md, which functions as an onboarding manual. It tells the AI agent what tools are available and, crucially, when to use them. The second component is the MCP server configuration itself — the actual connection to external services. The third includes optional hooks and automation that trigger specific actions.
When a developer mentions "payment" or "checkout" in their conversation with Kiro, the system automatically activates the Stripe power, loading its tools and best practices into context. When the developer shifts to database work, Supabase activates while Stripe deactivates. The baseline context usage when no powers are active approaches zero.
"You click a button and it automatically loads," Singh said. "Once a power has been created, developers just select 'open in Kiro' and it launches the IDE with everything ready to go."
Singh framed Kiro powers as a democratization of advanced development practices. Before this capability, only the most sophisticated developers knew how to properly configure their AI agents with specialized context — writing custom steering files, crafting precise prompts and manually managing which tools were active at any given time.
"We've found that our developers were adding in capabilities to make their agents more specialized," Singh said. "They wanted to give the agent some special powers for a specific problem. For example, they wanted ... the agent to become an expert at backend-as-a-service."
This observation led to a key insight: If Supabase or Stripe could build the optimal context configuration once, every developer using those services could benefit.
"Kiro powers formalizes things that only the most advanced people were doing, and allows anyone to get those kinds of skills," Singh said.
The announcement also positions Kiro powers as a more economical alternative to fine-tuning, or the process of training an AI model on specialized data to improve its performance in specific domains.
"It's much cheaper" compared to fine-tuning, Singh. "Fine-tuning is very expensive, and you can't fine-tune most frontier models."
This is a significant point. The most capable AI models from Anthropic, OpenAI and Google are typically "closed source," meaning developers cannot modify their underlying training. They can only influence the models' behavior through the prompts and context they provide.
"Most people are already using powerful models like Sonnet 4.5 or Opus 4.5," Singh said. "Those models need to be pointed in the right direction."
The dynamic loading mechanism also reduces ongoing costs. Because powers only activate when relevant, developers aren't paying for token usage on tools they're not currently using.
Kiro powers arrives as part of a broader push by AWS into what the company calls "agentic AI" — AI systems that can operate autonomously over extended periods.
At re:Invent, AWS also announced three "frontier agents" designed to work for hours or days without human intervention: Kiro autonomous agent for software development, AWS security agent and AWS DevOps agent. These represent a different approach from Kiro powers — tackling large, ambiguous problems rather than providing specialized expertise for specific tasks.
The two approaches are complementary. Frontier agents handle complex, multi-day projects that require autonomous decision-making across multiple codebases. Kiro powers, by contrast, gives developers precise, efficient tools for everyday development tasks where speed and token efficiency matter most.
The company is betting that developers need both ends of this spectrum to be productive.
The launch reflects a maturing market for AI development tools. GitHub Copilot, which Microsoft launched in 2021, introduced millions of developers to AI-assisted coding. Since then, a proliferation of tools — including Cursor, Cline and Claude Code — have competed for developers' attention.
But as these tools have grown more capable, they've also grown more complex. MCP, which Anthropic open-sourced last year, created a standard for connecting AI agents to external services. That solved one problem while creating another: The context overload that Kiro powers now addresses.
AWS is positioning itself as the company that understands production software development at scale. Singh emphasized that Amazon's experience running AWS for 20 years, combined with its own massive internal software engineering organization, gives it unique insight into how developers actually work.
"It's not something you would use just for your prototype or your toy application," he said. "If you want to build production applications, there's a lot of knowledge that we bring."
AWS indicated that Kiro powers currently works only within the Kiro IDE, but the company is building toward cross-compatibility with other AI development tools, including command-line interfaces, Cursor, Cline and Claude Code. The company's documentation describes a future where developers can "build a power once, use it anywhere" — although that vision remains aspirational for now.
For the technology partners launching powers today, the appeal is straightforward: Rather than maintaining separate integration documentation for every AI tool on the market, they can create a single power that works everywhere Kiro does. As more AI coding assistants crowd the market, that kind of efficiency becomes increasingly valuable.
Kiro powers is available now for developers using Kiro IDE version 0.7 or later at no additional charge beyond the standard Kiro subscription.
The underlying bet is a familiar one in the history of computing: The winners in AI-assisted development won't be the tools that try to do everything at once, but those that are smart enough to know what to forget.