Hacker News
This isn't a PPT. Repo speaks
• EvolutionEngine— L1-L6 autonomous evolution loop • MemorySystem— declarative/episodic/procedural, weighted • NightlyReview— metacognition proto • CodeSandbox— self-modifying code • TokenBudget / LiveStatus / KnowledgeFusion Hunyuan API + Ollama. Runs. Growing.
Comments URL: https://news.ycombinator.com/item?id=48680473
Points: 1
# Comments: 0
Show HN: Pw-whip, a bridge between PipeWire and WHIP
WHIP (RFC 9725) is a standardised media ingress protocol: it serves to stream audio and video to a network server, and is supported by a number of media distribution systems. PipeWire is the currently fashionable multimedia framework for Linux, and almost all Linux applications are able to send audio to PipeWire, either natively or through PipeWire's emulation of the ALSA and PulseAudio APIs.
Pw-whip is a bridge between PipeWire and WHIP: it enables every application that can speak to PipeWire to stream its audio to any compliant WHIP server.
Comments URL: https://news.ycombinator.com/item?id=48680445
Points: 1
# Comments: 0
Poll
Deep Dive into IBM's new NanoStack 0.7nm Process Node for Chips – 666 MTr/mm2
Article URL: https://morethanmoore.substack.com/p/ibms-announces-07nm-process-node
Comments URL: https://news.ycombinator.com/item?id=48680424
Points: 2
# Comments: 0
Hollywood-backed nonprofit launches machine-readable AI consent registry
Article URL: https://rslmedia.org/
Comments URL: https://news.ycombinator.com/item?id=48680410
Points: 1
# Comments: 0
The Garbage Collection Handbook: The Art of Automatic Memory Management (2nd Ed)
Article URL: https://gchandbook.org/
Comments URL: https://news.ycombinator.com/item?id=48680370
Points: 2
# Comments: 1
AI doesn't take jobs. It takes tasks
Article URL: https://www.nextgig.rocks/dash/how-ai-changes-jobs
Comments URL: https://news.ycombinator.com/item?id=48680358
Points: 2
# Comments: 0
How do you tackle a backlog of deferred maintenance you didn't create?
I don't mean migration in the sense of switching databases or rewriting in another language. I mean that a codebase rots if nobody maintains it. Deprecations, warnings, upstream changes — each is cheap to handle the moment it appears, often a 10-minute fix (let's say 'in average'). But plenty of teams never catch them. No real CI/CD, no culture of reading changelogs or acting on warnings. So it piles up silently, and then at some point — usually when an infra or security team shows up with tickets — the whole accumulated pile lands on one person at once. Often a new hire or a junior who's never seen the code, with no record of why any of it is the way it is beyond git blame, a stale changelog, and a few dead chat threads. What I think gets underestimated is that clearing it all at once costs far more than the sum of the small fixes would have. The problems tangle into each other, and the context that would let you separate them is already gone. So I'm trying to learn from people who've been dropped into this. What did you actually reach for, and what worked — tests, diffing output before/after, shadowing prod traffic, or just running it and hoping? Did anyone try LLM agents, and where did they genuinely help versus confidently make things worse? (I know of an Angular case where the agent kept patching a function it assumed was the problem, and after a couple of failed runs invented its own workaround — when the correct approach was in the docs the whole time). Just time spending. If you can ballpark it: how much worse was all-at-once versus incremental — 3x, 10x? And one thing I keep wondering: when you were reconstructing a system like this, what were you missing more — a description of what the code does, or of what someone meant it to do? Those feel like two different problems.
Comments URL: https://news.ycombinator.com/item?id=48680354
Points: 1
# Comments: 0
Elasto Mania Ported to WebAssembly
Article URL: https://joshumax.github.io/elma-web/
Comments URL: https://news.ycombinator.com/item?id=48680330
Points: 1
# Comments: 0
Show HN: HoprLabs – a Python lab for prototyping AI math ideas
Article URL: https://github.com/TangibleResearch/HoprLabs
Comments URL: https://news.ycombinator.com/item?id=48680309
Points: 2
# Comments: 0
Oracle workforce shrinks by about 21,000 employees amid AI adoption
Article URL: https://finance.yahoo.com/technology/ai/articles/oracle-workforce-shrinks-13-204431510.html
Comments URL: https://news.ycombinator.com/item?id=48680283
Points: 1
# Comments: 0
Ford could bring F1-inspired 'skunkworks' EVs to Europe
Article URL: https://www.autocar.co.uk/car-news/electric-cars/ford-could-bring-f1-inspired-skunkworks-evs-europe
Comments URL: https://news.ycombinator.com/item?id=48680278
Points: 2
# Comments: 0
Show HN: DeepSeek Flash inverted the economics of agent products
There is an adversarial relationship between developers and big model labs.
Model labs charged developers higher API prices to subsidize their own agent harness offerings. Think Anthropic charging 5x higher Claude API prices to subsidize consumer subscriptions. So Cursor in a way was subsidizing their own direct competitor.
DeepSeek V4 Flash totally inverted this relationship. Now you have a model that beats even Sonnet in some benchmarks and is totally opensourced. Now inference providers are racing to the bottom to optimize and give cheaper hosting. Every player with a non-SOTA is now racing to swap over to stop paying the big model lab tax, even Microsoft is switching Copilot to use DeepSeek.
On switching over to Deepseek: - we noticed over a 100x cost decrease while similar or better performance then Gemini 3 Flash - insane saving from the cached input tokens: $0.002/1 Million tokens - both DeepSeek Flash and GLM 5.2 are text-only models, so clearly multimodal training is not worth the additional cost. Language is just a much more efficient sparse representation of the world/reasoning than vision - we had a early bet on a text-only web agent harness, and now with DeepSeek this results in a unique cost advantages. - we rewrote our harness as a callable DSL library that a model can generate code to execute on. DeepSeek has proven phenomenal on code generation to drive an agent harness. - I would highly recommend everyone to rewrite their harness to be text-only and callable via executable code
Comments URL: https://news.ycombinator.com/item?id=48680260
Points: 3
# Comments: 0
Om Malik
Article URL: https://en.wikipedia.org/wiki/Om_Malik
Comments URL: https://news.ycombinator.com/item?id=48680251
Points: 1
# Comments: 0
California AI Unemployment Tracker
Article URL: https://capolicylab.org/california-ai-unemployment-tracker/
Comments URL: https://news.ycombinator.com/item?id=48680242
Points: 1
# Comments: 0
Liveness Proofs in Veil, Part I: The First Step
Article URL: https://proofsandintuitions.net/2026/06/24/liveness-proofs-in-veil-part-1/
Comments URL: https://news.ycombinator.com/item?id=48680234
Points: 1
# Comments: 0
New macOS malware embeds fake errors to confuse AI analysis tools
Article URL: https://www.bleepingcomputer.com/news/security/new-macos-malware-embeds-fake-errors-to-confuse-ai-analysis-tools/
Comments URL: https://news.ycombinator.com/item?id=48680232
Points: 1
# Comments: 0
Data Science Weekly – Issue 657
Article URL: https://datascienceweekly.substack.com/p/data-science-weekly-issue-657
Comments URL: https://news.ycombinator.com/item?id=48680231
Points: 1
# Comments: 0
The Sunscreen Result No One Wants to Talk About
Article URL: https://charlottekupewasserphd.substack.com/p/the-sunscreen-result-no-one-wants
Comments URL: https://news.ycombinator.com/item?id=48680226
Points: 3
# Comments: 1
Powercode
Article URL: https://codeberg.org/slaubenberger/Powercode
Comments URL: https://news.ycombinator.com/item?id=48680212
Points: 3
# Comments: 0
