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alefore
edge
C++2020–2025
alefore / edge

edge

Edge - a text editor

3Distinct people
19Mentions
0Explicit recommenders
88GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Edge - a text editor

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 2:59:58 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year19 dated mentions

Observed mentions: 2020-03-24 18:12:12 UTC to 2025-10-18 16:40:55 UTC.

02468102020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 10 mentions; 1 submissions, 9 comments20202021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20222023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 5 mentions; 0 submissions, 5 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 3 mentions; 2 submissions, 1 comments2025

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC1019
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC101
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC505
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC000
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC321

What Hacker News says

3 sources
afc·Jul 20, 2025Submission

Show HN: Duende: Web UX for guiding Gemini as it improves your source code

I wrote a simple web UX in Python/JavaScript that spawns a conversation with Google Gemini with MCP commands that let it work on a specific coding task that you specify: http://github.com/alefore/duende The UX lets you observe the conversation and provide guidance (e.g. "don't implement Foo through Bar, that's suboptimal; instead …"). It supports a `--review` mode, where once the main conversation says "I'm done with the task", various "evaluation" conversations are spawned, each focusing on reviewing the change from a very specific angle (e.g. "does it introduce useless comments?"). In the future, I'm considering adding other workflows. I've used it mostly to develop itself (I started with a super rudimentary manual implementation and then mostly used Duende to extend its own implementation) as well as (with moderate success) to add a fe
Read the rest
w new features to [my C++ text editor](http://github.com/alefore/edge). It's been a lot of fun. I'm still developing my intuitions for what works and what doesn't, but I've already had plenty of experiences where I've been WOW'ed by what LLMs can already accomplish (as well as, to be honest, plenty of very disappointing cases where it struggles significantly on tasks that I expected would have been trivial). It's a learning experience, seeing things like how to avoid hallucinations; developing an intuition for how much to break down large tasks into smaller ones; or knowing when to abort a conversation and restart it with an improved prompt (vs continue to steer it in the right direction). I think investing up-front in setting up a good context (e.g., good validation logic, useful constant contexts, a good set of "review evaluators" that can push-back against sloppy code) can go a long way to increase the odds of success. It has changed my perception on the applicability of AI for developing software. While I've reviewed all the outputs (and often rewrite parts of them manually), I'm already incorporating it into (some parts) of my development life-cycle. I have many ideas for improvements, but figured I'd share this early and ask for feedback. Hopefully others find it interesting; would love to hear your thoughts.
8 points · Open discussion

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