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Beyond Vibe Coding: Spec-Driven Development with Kiro

Kiro Spec-Driven Development

A new two-day, instructor-led course teaches developers to bring structure, correctness, and governance to agentic software development — using AWS’s own agentic IDE.

KIRO spec-driven development

Every developer who has spent an afternoon “vibe coding” with an AI assistant knows the pattern: you describe what you want, the agent produces plausible-looking code, and twenty minutes later you’re untangling a feature that solved the wrong problem, missed an edge case, or quietly diverged from what the team actually needed. Prompting is fast. It just isn’t a substitute for planning — and as AI agents take on more of the actual engineering work, that gap turns into real technical debt.

Kiro, AWS’s agentic IDE, was built specifically to close that gap. Instead of jumping straight from prompt to code, Kiro has the agent work through requirements, design, and a sequenced task plan first — turning a request into a spec the agent (and your team) can actually review before a single line ships. As Kiro’s own site puts it: most tools are great at generating code, but Kiro gives structure to the chaos before you write a single line. Tech Reformers is now offering Spec-Driven Development with Kiro, a two-day hands-on course that teaches you exactly how to put that structure to work.


Spec-driven development is a discipline — but it lives or dies on the tooling that supports it, and Kiro was built around it from the ground up rather than bolting it on:

  • Specs as the unit of work. Every feature moves through Requirements, Design, and Tasks phases before implementation begins, using EARS notation to make requirements unambiguous and reviewable — by humans and by the agent.
  • Correctness you can trust. Kiro applies property-based testing — asserting rules that must hold across all inputs, closer to fuzz testing than traditional unit tests — to catch the edge cases a quick prompt-and-check cycle misses.
  • Agent behavior you control. Steering files, context providers, and Autopilot vs. Supervised execution modes mean you decide how much autonomy the agent gets, on a project-by-project or even task-by-task basis.
  • An ecosystem, not a walled garden. Kiro connects to your existing toolchain through Model Context Protocol (MCP) servers, the Agent Client Protocol, Skills.md, and Open VSX extensions — plus direct integrations with tools like Figma, Terraform, and Postman.
  • Built for teams, not just individuals. Agent hooks automate recurring workflows, agent skills package reusable expertise, and shared steering plus enterprise governance (MCP registry allowlisting, model governance, extension management) mean Kiro scales from a single developer to an organization.
  • Work where you already do. Kiro is available as a full IDE, a CLI, a web platform with cloud sandboxes, and a mobile interface — with the flexibility to choose Claude models, open-weight alternatives, or an Auto mode that balances capability and cost.

That combination — structured planning, verifiable correctness, controllable autonomy, and real governance — is what separates a tool for demos from a tool for production engineering. It’s also exactly what this course is built to teach.

Day 1 starts with the agentic coding paradigm and the five principles of effective agentic development, then goes hands-on with the core spec workflow: Requirements-First and Design-First approaches, EARS notation, and property-based testing for correctness. You’ll learn to control agent behavior with steering files, execution modes, and trusted commands, and close the day with Bugfix Specs — using the same disciplined, spec-first approach to root-cause analysis and regression-safe fixes. Labs are interleaved throughout, and you’ll progressively build a weather application using each capability as it’s introduced.

Day 2 moves from individual workflow to team- and platform-scale: connecting MCP servers and tools, installing and authoring Kiro Powers to solve the context-overload problem, and automating work with agent hooks, agent skills, and custom subagents. The day closes with team collaboration and enterprise governance — shared .kiro configuration, spec review conventions, and the controls that let an organization roll this out safely. You’ll apply it all by extending and team-enabling a pre-built micro-blogging application.

This course is intended for software developers and engineers, technical leads adopting AI-assisted development workflows, development teams moving into agentic coding practices, and DevOps engineers integrating AI agents into delivery pipelines.

Come in with some knowledge in at least one programming language, working knowledge of Git, a basic understanding of RESTful APIs and cloud application concepts, and foundational familiarity with generative AI concepts (LLMs, tokens, inference).

Upcoming sessions

All sessions run online, 9:00 AM – 5:00 PM Central Time, $1,000 per person for the two-day course.

DatesDaysTimeRegister
Aug 6–7, 2026Thu–Fri9am–5pm CDTRegister
Sep 3–4, 2026Thu–Fri9am–5pm CDTRegister
Oct 5–6, 2026Mon–Tue9am–5pm CDTRegister
Nov 3–4, 2026Tue–Wed9am–5pm CSTRegister

Taught by John Krull. Seats are limited per session — register early to lock in your preferred date.

Full course details, prerequisites, and registration are on the Spec-Driven Development with Kiro course page, or browse the full course catalog to see everything Tech Reformers offers.

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about author

John Krull

jkrull@techreformers.com

John is Founder and CEO of Tech Reformers, an AWS Advanced Services Partner and AWS Authorized Training Provider helping mid-market enterprises modernize on AWS. He founded Tech Reformers in 2019 to help organizations modernize their infrastructure and deploy production-ready AI on AWS.

John holds AWS certifications as a Solutions Architect Professional, Machine Learning Engineer, and Generative AI Fundamentals. He is an AWS Authorized Instructor Champion, teaching courses across the AWS developer and generative AI curriculum — including Developing on AWS and Advanced Generative AI Development on AWS.

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