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Q Developer new signups are blocked; IDE plugins EOS 30 Apr 2027 per AWS. Start Kiro tonight on a tiny Python lab and review every change.
Amazon Q Developer helped many teams put AI into the IDE loop. AWS is now steering developers to Kiro, an agentic environment built for spec-driven development. Official Q page (with end-of-support notice): aws.amazon.com/q/developer. Kiro home: kiro.dev. EOS announcement: AWS DevOps Blog.
Per AWS: new Q Developer Free Tier signups and new Q Developer subscriptions were blocked starting 15 May 2026. Amazon Q Developer IDE plugins and paid subscriptions reach end of support on 30 April 2027. AWS Management Console and chat-app experiences for Q are called out separately as not part of that IDE sunset. If you still have an existing Pro subscription, AWS documents that you can keep using the plugins through the transition window and may still add seats on that subscription—but new learners after work should start on Kiro, not chase a closed Free Tier path.
This Hub guide is for evening Python practice: download Kiro, open a tiny lab, run one supervised task, and treat Q→Kiro as a forward path—not a nostalgia project.
Professionals who used (or considered) Amazon Q in VS Code / JetBrains and now need a clear next step. Also anyone who wants AWS-backed agentic tooling with specs, hooks, and CLI/IDE surfaces without inventing a migration date—use the dates AWS published.
Compare other evening agents in Top 10 AI agent tools for after-work Python. There is a separate Hub path for Kiro CLI deep-dives when you want terminal-first workflows; tonight is “get Kiro running on a practice folder.”
Skim the end-of-support announcement so you know what stops when. Then open kiro.dev and download the IDE (or install the CLI with the official install command on that site). Prefer AWS/Kiro download pages over random mirrors.
Create an account through Kiro’s official flow. Start with a personal practice folder—never your employer’s confidential repo on night one. Kiro shares .kiro/ configuration across IDE, CLI, and web surfaces; keep secrets out of steering files and chat.
# greet.py
def greet(name: str) -> str:
return f"Hello, {name}"
if __name__ == "__main__":
print(greet("world"))
Open that folder in Kiro IDE. Optionally write a short spec (requirements in structured natural language) that says: add greet_many, keep type hints, stdlib only, no new files. Spec-driven flow is Kiro’s differentiator versus “one more autocomplete plugin.”
In chat or agent mode, ask Kiro to implement the spec (or paste the same bounded prompt). Watch file edits. Accept only what matches the request. Then run:
python greet.py
If you previously used Q CLI, AWS/Kiro docs describe upgrading toward Kiro CLI (kiro.dev upgrade guides)—do that on a free evening after the IDE lab works, not before.
If your day job still runs Q plugins until 2027, keep a NOTES.md list: MCP servers, custom prompts, team conventions. Migrate those into Kiro steering / hooks when you are ready. Do not invent earlier cutoffs; follow your org and the AWS timeline.
Ask Kiro for normalize_name(s: str) -> str (strip + title-case) wired into greet, stdlib only. If you try a mini spec instead of a free-form chat, compare which review felt easier after work.
Migration anxiety expands to fill free time. Cap tonight at: official dates absorbed, Kiro installed, one practice file changed under supervision. You can schedule a second evening for CLI migration or team subscription upgrades. After-work learning fails when the first session tries to finish the whole AWS transition plan—success is a running Kiro lab and a short NOTES.md.
Kiro will move faster when you can state clear Python requirements. SoloQuant’s Intro to Python Programming fits after-work short lessons—so your specs describe real functions, not vague “make it better” wishes.