tech-debt

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#tech-debt

my team shipped a working tech-debt agent in a day. the hard part wasn't the code, it was defining the problem well enough that an agent could carry it.

Reddit r/AI_Agents · 4d ago

A team built an AI agent to automatically fix tech debt by scanning the codebase and opening PRs, finding that the hardest part was precisely defining the problem. They discuss challenges of running multiple agents on the same codebase and the need for guardrails.

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#tech-debt

Pull Requests are Free Puppies

Lobsters Hottest · 4d ago Cached

Richard Hipp, creator of SQLite, uses the metaphor of a 'free puppy' for pull requests: they appear free on the surface, but actually commit to long-term maintenance. The article also reviews the origins of SQLite, early contracts, and the story of the founding of the consortium, exploring the hidden costs of open-source maintenance.

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#tech-debt

NetNewsWire Status

Lobsters Hottest · 6d ago Cached

Brent Simmons reports on the NetNewsWire RSS reader's progress over the past year, highlighting modernization, bug fixes, and performance improvements, with a focus on foundational work before adding new features.

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#tech-debt

Agent loops are great until they learn from your worst code

Reddit r/ArtificialInteligence · 2026-06-09

This article discusses how AI coding agent loops can inadvertently learn and propagate deprecated code patterns from existing codebases, leading to technical debt despite appearing successful.

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#tech-debt

are AI coding tools just becoming the new cloud bill problem?

Reddit r/artificial · 2026-06-07

The article compares the rising costs of AI coding tools to early cloud computing, highlighting hidden expenses like token usage, code review, and maintenance, and questions whether teams are tracking true cost per workflow.

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#tech-debt

Cognitive debt might be the most underrated problem AI is creating

Reddit r/artificial · 2026-06-01

The article argues that reliance on AI without foundational understanding creates 'cognitive debt', a hidden cost that may lead to professionals who cannot interrogate or evaluate AI outputs in high-stakes fields like law, medicine, and finance.

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