Hacker News

Article URL: https://github.com/star-ga/mind-mem

Comments URL: https://news.ycombinator.com/item?id=47234761

Points: 1

# Comments: 1

Article URL: https://spectrum.ieee.org/military-drones-self-driving-cars

Comments URL: https://news.ycombinator.com/item?id=47234759

Points: 1

# Comments: 0

Article URL: https://srconstantin.wordpress.com/2019/06/28/book-review-why-are-the-prices-so-damn-high/

Comments URL: https://news.ycombinator.com/item?id=47234758

Points: 2

# Comments: 0

Article URL: https://cendyne.dev/posts/2026-02-27-from-fargo-to-zebra.html

Comments URL: https://news.ycombinator.com/item?id=47234756

Points: 1

# Comments: 0

Article URL: https://www.youtube.com/watch?v=r0QY2_Ej32Q

Comments URL: https://news.ycombinator.com/item?id=47234755

Points: 1

# Comments: 0

Article URL: https://macthemes.garden/

Comments URL: https://news.ycombinator.com/item?id=47234754

Points: 1

# Comments: 0

Article URL: https://cfp.cfgmgmtcamp.org/ghent2026/talk/LHWU8T/

Comments URL: https://news.ycombinator.com/item?id=47233925

Points: 1

# Comments: 0

In multi-step tasks, LLM outputs may replace structured intermediate forms with scalar results.

Example: (2 + 3) * 4 → 20

This removes structural decomposition and makes downstream reasoning dependent on a scalar result.

I built a minimal prototype that enforces admissibility before persistence using a write barrier. The write barrier separates model output from persistent state.

Core mechanisms: * Append-only lineage (no in-place mutation) * Explicit proposal → invariant check → commit cycle * Whitelisted structural transforms * Deterministic invariant checks before commit

If a transform attempts to collapse structure (e.g., replacing a decomposed expression with a scalar), the proposal is rejected and never enters the lineage.

Important distinction: Invalid states may still be representable as data, but they are uncommittable under the governed commit path.

This does not modify the model. It constrains persistence architecturally around model outputs.

Arithmetic is used purely as a stress-test domain to isolate one narrow claim: Certain structural collapses can be made impossible to persist.

Limitations: * Domain-specific invariants * Not a symbolic solver * Does not improve model accuracy * In-memory prototype storage

GitHub: https://github.com/PersistentVlad/persistent-reasoning-archi...

Comments URL: https://news.ycombinator.com/item?id=47233920

Points: 1

# Comments: 1

Hey HN,

Exodus tracks who's leaving the big AI companies, where they're going, and what they're building. 240+ moves, 80+ companies, every entry sourced.

I used AI to track these after noticing the same pattern every week: someone leaves OpenAI, someone leaves Anthropic, a new startup appears, they get funded week later. A few things stood out:

- Google/DeepMind lost 58 people and got 13 back - OpenAI alumni founded 18 startups worth $450B+ (TechCrunch calls them "The OpenAI Mafia") - Half of xAI's co-founding team walked out - Apple feeds Meta, Meta feeds OpenAI — there's a whole food chain

You can filter by company, role, seniority, or time period. There's a Sankey diagram and a brain drain chart.

The curation pipeline uses the same system I run for https://7min.ai. Every entry is checked against published sources.

Are we missing any patterns?

Comments URL: https://news.ycombinator.com/item?id=47233912

Points: 1

# Comments: 0

In many software applications, Search is the core feature. As Trey describes, the search bar is the universal interface for interacting with data!

So how should you think about designing user experiences around search so that your users are delighted to use your software?

What are the different types of search experiences you should be aware of as someone working in search engineering?

Also, whereas LLMs have typically responded to us with a wall of text, they can now respond with applications created from stacks such as HTML/CSS/JavaScript. How will this shape search experience design?

https://www.youtube.com/watch?v=zenU1lsjRL0

Comments URL: https://news.ycombinator.com/item?id=47233900

Points: 1

# Comments: 0

Article URL: https://www.even.li/posts/2026-03-03-deploy-github-actions-without-storing-secrets-using-oidc/

Comments URL: https://news.ycombinator.com/item?id=47233882

Points: 1

# Comments: 0

Article URL: https://www.pinchofintelligence.com/two-months-as-a-vibe-coder/

Comments URL: https://news.ycombinator.com/item?id=47233881

Points: 1

# Comments: 0

Article URL: https://www.phenomenalworld.org/analysis/finance-in-the-dark/

Comments URL: https://news.ycombinator.com/item?id=47233877

Points: 1

# Comments: 0

Article URL: https://www.getesimpal.com/en-US/agents

Comments URL: https://news.ycombinator.com/item?id=47233854

Points: 1

# Comments: 1

Article URL: https://www.distillabs.ai/blog/the-10x-inference-tax-you-dont-have-to-pay

Comments URL: https://news.ycombinator.com/item?id=47233844

Points: 1

# Comments: 0

I built aside this weekend because I was tired of pasting meeting transcripts into Claude Code myself to get notes that actually connected to my Obsidian vault. Every tool I tried either required an account, sent my audio to a server, or produced summaries disconnected from where I actually think.

aside is a ~5MB Rust binary that records meetings and feeds them into an AI-native transcription-to-vault workflow:

1. Record — captures mic + system audio simultaneously (stereo WAV, left=you, right=them) with a timestamped TUI editor for real-time notes 2. Transcribe — local transcription via whisper.cpp, with a 7-stage cleanup pipeline that strips hallucinations, deduplicates backchannels, and merges fragments 3. Align — interleaves your memo lines with the transcript on a shared timeline, so you can see what was said around each thing you noted 4. Distill — a Claude Code skill searches your Obsidian vault for related notes, then writes a structured note back into it with [[wikilinks]] to your existing thinking

The distillation step is the part I'm most interested in feedback on. The entire pipeline is a 240-line markdown file (a Claude Code "skill") that the LLM follows as instructions. It treats your memo lines as attention signals — what you wrote down mid-call gets priority over what you didn't. Lines you edited mid-meeting get weighted even higher. It searches your vault semantically and by structure (tags, people, wikilinks), then weaves connections into the output note.

The output doesn't read like a meeting summary with action items. It reads like what you would have written up yourself if you had the time — highlighting what mattered to you, connected to what you've already been thinking about.

The skill is plain text. You can read it in the repo, fork it, change how it prioritizes topics or formats notes. There's no black box between the transcript and the vault note — just markdown instructions an LLM follows.

This matters because the workflow is vault-native end to end: sessions live inside the vault, distilled notes land where your thinking already lives, and the AI step uses your vault's own language and structure as context. The meeting note isn't a standalone summary — it's a node in your existing knowledge graph.

Technical details: 3.1k lines total. Rust binary handles recording + TUI (cpal for audio, ratatui for the editor, lock-free ring buffers for real-time capture). Python script handles transcription cleanup. Claude Code skill handles distillation. Everything runs locally except the optional LLM call.

Dual audio capture solves hybrid meetings — conference room mic + remote participants on speaker both get transcribed on separate channels.

No accounts, no telemetry, Apache 2.0. Install via `brew install jshph/aside/aside`

Comments URL: https://news.ycombinator.com/item?id=47233839

Points: 1

# Comments: 0

Article URL: https://nesbitt.io/2026/03/03/package-management-is-naming-all-the-way-down.html

Comments URL: https://news.ycombinator.com/item?id=47233822

Points: 1

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Article URL: https://plasma-bigscreen.org

Comments URL: https://news.ycombinator.com/item?id=47233821

Points: 1

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Article URL: https://medium.com/@big.sebastian.ionut/darwinian-post-design-when-ease-of-use-becomes-the-only-honest-metric-ecbdc16dc515

Comments URL: https://news.ycombinator.com/item?id=47233809

Points: 1

# Comments: 1

Article URL: https://www.bloomberg.com/news/articles/2026-03-02/european-gas-rallies-more-than-30-as-qatar-halts-lng-production

Comments URL: https://news.ycombinator.com/item?id=47233793

Points: 2

# Comments: 0