Open Collective
@opencollect
Platform to run your community like an open source project. Manage your income and expenses in a transparent way.
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Latest posts 5
In case you are wondering how much funding the PHP Foundation is receiving to maintain this central piece of infrastructure.
Ask your company and government to fund the road and bridges of our digital space. The cost of not doing so is far greater.
opencollective.com/phpfoundation
Ask your company and government to fund the road and bridges of our digital space. The cost of not doing so is far greater.
opencollective.com/phpfoundation
In Berlin? See you at the Neo Cypherpunk Summit today s26ber.web3privacy.info
s26ber.web3privacy.info Neocypherpunk Summit #1 14 Jun 2026 - 2025 was an exceptional year: 10000 people, 130 speakers from Eva Galperin (EFF) to Roger Dingledine (Tor) speaking. We decided to make a sequel and strengthen Cypherpunk activism,... And at 4pm, join us for a conversation on “Stewarding Resilient, Free & Open Digital Infrastructures” with @TBSocialist @fsf @mpg_dd and myself.View quoted post on X
talx.dod.ngo/neocypherpunk-…
#web3privacy #Cypherpunk
Fund an independent and decentralized citizen wireless network.
Je viens de faire un don à Meshtastic. Toi aussi, soutiens-les ! opencollective.com/meshtastic via @opencollectView quoted post on X
TLDR: we need maintainers more than ever.
Support the maintainers.
Support the maintainers.
🤯BREAKING: Alibaba just proved that AI Coding isn't taking your job, it's just writing the legacy code that will keep you employed fixing it for the next decade. 🤣
Passing a coding test once is easy. Maintaining that code for 8 months without it exploding? Apparently, it’s nearly impossible for AI.
Alibaba tested 18 AI agents on 100 real codebases over 233-day cycles. They didn't just look for "quick fixes"—they looked for long-term survival.
The results were a bloodbath:
75% of models broke previously working code during maintenance.
Only Claude Opus 4.5/4.6 maintained a >50% zero-regression rate.
Every other model accumulated technical debt that compounded until the codebase collapsed.
We’ve been using "snapshot" benchmarks like HumanEval that only ask "Does it work right now?"
The new SWE-CI benchmark asks: "Does it still work after 8 months of evolution?"
Most AI agents are "Quick-Fix Artists." They write brittle code that passes tests today but becomes a maintenance nightmare tomorrow. They aren't building software; they're building a house of cards.
The narrative just got honest: Most models can write code. Almost none can maintain it.View quoted post on X
