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Listen to Mixtapes from Before

https://intertapes.net/
1•poniko•1m ago•0 comments

My First Impressions of MeshCore Off-Grid Messaging

https://mtlynch.io/first-impressions-of-meshcore/
1•mtlynch•2m ago•0 comments

I built a tool to restore old family photos without ruining them with AI

https://forevi.ai
1•poznerd•2m ago•1 comments

Designing Electronics That Works

https://nostarch.com/designingelectronics
1•0x54MUR41•3m ago•0 comments

Most LLM cost isn't compute – it's identity drift (110-cycle GPT-4o benchmark)

https://github.com/sigmastratum/documentation/blob/main/sigma-runtime/SR-EI-03/benchmark_report_S...
1•teugent•3m ago•1 comments

Show HN: PlanEat AI, an AI iOS app for weekly meal plans and smart grocery lists

1•franklinm1715•4m ago•0 comments

A Post-Incident Control Test for External AI Representation

https://zenodo.org/records/17921051
1•businessmate•4m ago•1 comments

اdifference gbps overview find answers

1•shahrtjany•5m ago•0 comments

Measuring Impact of Early-2025 AI on Experienced Open-Source Dev Productivity

https://arxiv.org/abs/2507.09089
1•vismit2000•7m ago•0 comments

Show HN: Lazy Demos

http://demoscope.app/lazy
1•admtal•8m ago•0 comments

AI-Driven Facial Recognition Leads to Innocent Man's Arrest (Bodycam Footage) [video]

https://www.youtube.com/watch?v=B9M4F_U1eEw
1•niczem•8m ago•1 comments

Annual Production of 1/72 (22mm) scale plastic soldiers, 1958-2025

https://plasticsoldierreview.com/ShowFeature.aspx?id=27
1•YeGoblynQueenne•9m ago•0 comments

Error-Handling and Locality

https://www.natemeyvis.com/error-handling-and-locality/
1•Theaetetus•11m ago•0 comments

Petition for David Sacks to Self-Deport

https://form.jotform.com/253464131055147
1•resters•11m ago•0 comments

Get found where people search today

https://kleonotus.com/
1•makenotesfast•13m ago•1 comments

Show HN: An early-warning system for SaaS churn (not another dashboard)

https://firstdistro.com
1•Jide_Lambo•14m ago•1 comments

Tell HN: Musk has never *tweeted* a guess for real identity of Satoshi Nakamoto

1•tokenmemory•14m ago•2 comments

A Practical Approach to Verifying Code at Scale

https://alignment.openai.com/scaling-code-verification/
1•gmays•16m ago•0 comments

Show HN: macOS tool to restore window layouts

https://github.com/zembutsu/tsubame
1•zembutsu•19m ago•0 comments

30 Years of <Br> Tags

https://www.artmann.co/articles/30-years-of-br-tags
2•FragrantRiver•26m ago•0 comments

Kyoto

https://github.com/stevepeak/kyoto
2•handfuloflight•26m ago•0 comments

Decision Support System for Wind Farm Maintenance Using Robotic Agents

https://www.mdpi.com/2571-5577/8/6/190
1•PaulHoule•27m ago•0 comments

Show HN: X-AnyLabeling – An open-source multimodal annotation ecosystem for CV

https://github.com/CVHub520/X-AnyLabeling
1•CVHub520•30m ago•0 comments

Penpot Docker Extension

https://www.ajeetraina.com/introducing-the-penpot-docker-extension-one-click-deployment-for-self-...
1•rainasajeet•30m ago•0 comments

Company Thinks It Can Power AI Data Centers with Supersonic Jet Engines

https://www.extremetech.com/science/this-company-thinks-it-can-power-ai-data-centers-with-superso...
1•vanburen•33m ago•0 comments

If AIs can feel pain, what is our responsibility towards them?

https://aeon.co/essays/if-ais-can-feel-pain-what-is-our-responsibility-towards-them
3•rwmj•37m ago•5 comments

Elon Musk's xAI Sues Apple and OpenAI over App Store Drama

https://mashable.com/article/elon-musk-xai-lawsuit-apple-openai
1•paulatreides•40m ago•1 comments

Ask HN: Build it yourself SWE blogs?

1•bawis•40m ago•1 comments

Original Apollo 11 Guidance Computer source code

https://github.com/chrislgarry/Apollo-11
3•Fiveplus•46m ago•0 comments

How Did the CIA Lose Nuclear Device?

https://www.nytimes.com/interactive/2025/12/13/world/asia/cia-nuclear-device-himalayas-nanda-devi...
1•Wonnk13•47m ago•1 comments
Open in hackernews

Ask HN: AI for maintenance of open source abandonware?

3•acheong08•7mo ago
I've been thinking about this over the past few days - If AI is as capable as people here claim - enough to replace junior or intermediate developers - could it be used to maintain semi-abandoned open-source projects?

There is a fair number of abandoned OSS with 1 or 2 major issues that prevent them from continuing to work and isn't too difficult to fix - just requires time. If users pooled context (issues, code, docs) and tokens, I'm inclined to believe an AI agent could resolve them.

Here's an example: hydroxide [0] is a ProtonMail to IMAP/SMTP bridge that no longer works due to upstream API changes [1]. Working implementations are available, just in a different language [2]. All an AI would have to do is reference the current implementation and the alternative implementation, then migrate over to the new API format. Perhaps use an mitmproxy MCP to verify that the requests made are identical. Overall, not a very difficult problem and I can probably do it myself given a few days.

Human engineering hours are quite expensive though and for such a low value task, I would assume an AI agent would be more cost effective.

Is anyone working on a similar problem/premise?

[0] https://github.com/emersion/hydroxide [1] https://github.com/emersion/hydroxide/issues/304 [2] https://github.com/opulentfox-29/protonmail-api-client/blob/master/src/protonmail/client.py

Comments

rvz•7mo ago
> I've been thinking about this over the past few days - If AI is as capable as people here claim - enough to replace junior or intermediate developers - could it be used to maintain semi-abandoned open-source projects?

I don't think AI agents can generalize reliably to maintain complex open-source software, better than the authors. Those who say that are out to sell you an AI product or something.

The benchmark I would consider is the maintenance of the Linux kernel and AI is far from approaching to the level that it can maintain correct critical code that is trustworthy enough to being merged into mainline. But we'll see.

> Overall, not a very difficult problem and I can probably do it myself given a few days. Human engineering hours are quite expensive though and for such a low value task, I would assume an AI agent would be more cost effective.

Software maintenance is indeed expensive for a reason, however we still can't assume that an AI agent can help deal with autonomous maintenance on OSS projects; large or small or even in [0] and [2].

Technical debt is also a cost and many of these abandoned OSS projects don't even have any tests in the first place, including both 'hydroxide' and the protonmail client in [2].

So how do you know you if either project really works or not? Even if you use AI, what if it introduces a new bug in its implementation? How would you know beyond 'it works for me'?

In fact, autonomous AI agents just risk introducing more technical debt in OSS projects and increases that cost rather than reducing it.