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Show HN: HeyAgent – continue your Codex/Claude sessions from Telegram

https://github.com/gergomiklos/heyagent
1•gregolo•42s ago•0 comments

Show HN: MCP server that checks if your project idea exists

https://github.com/mnemox-ai/idea-reality-mcp
1•mnemoxai•1m ago•0 comments

(AI) Bots Ate My Map Tiles

https://www.vicchi.org//2026/02/21/ai-bots-ate-my-map-tiles/
1•speckx•1m ago•0 comments

Vibe Coding Might Just Be the Future of B2B SaaS

https://nmn.gl/blog/vibe-coding-future-b2b-saas
1•namanyayg•1m ago•0 comments

Show HN: CLaaS – Update your local LLM's weights in real time from text feedback

https://github.com/kfallah/CLaaS
1•kfallah•2m ago•1 comments

Takata airbag scandal: the most expensive design flaw in history

https://www.youtube.com/watch?v=lBJW5-IDh5U
2•fanf2•2m ago•0 comments

2026 Toyota C-HR First Drive Review: An Entry-Level EV That's Fun

https://www.thedrive.com/car-reviews/2026-toyota-c-hr-first-drive-review
1•PaulHoule•3m ago•0 comments

Iran's "Black Hole" Subs Make Hormuz a Shallow-Water Sonar Trap

https://modernengineeringmarvels.com/2026/02/25/irans-black-hole-subs-make-hormuz-a-shallow-water...
1•Brajeshwar•3m ago•0 comments

Interstellar Comet 3I/Atlas Carries a Carbon Signature No Local Comet Matches

https://modernengineeringmarvels.com/2026/02/25/interstellar-comet-3i-atlas-carries-a-carbon-sign...
1•Brajeshwar•4m ago•0 comments

Boston Celtics game-inspired friction test pinned down sneaker squeak

https://apnews.com/article/basketball-shoes-sneakers-squeak-grip-nba-808e5f51a548dca6281f03a560ef...
1•Brajeshwar•4m ago•0 comments

SHELL: Global Tool for Calling and Chaining Procedures in the System (1965) [pdf]

https://people.csail.mit.edu/saltzer/Multics/Multics-Documents/MDN/MDN-4.pdf
1•NaOH•4m ago•0 comments

Pixel Agents: AI agents animated as pixel art characters in a virtual office

https://github.com/pablodelucca/pixel-agents
1•piqufoh•4m ago•0 comments

UK media groups unite to tackle AI 'scraping' of journalism

https://www.bbc.co.uk/mediacentre/articles/2026/open-letter-spur
2•mmarian•4m ago•2 comments

Nvidia shares fall as blockbuster results fail to dazzle

https://www.ft.com/content/f4cda766-5650-4a97-a84f-24d3cfbeddd6
1•mikhael•4m ago•0 comments

K8s Debugging: Beyond Basics

https://kubekattle.github.io/ktl/blog/ktl-logs-rollout-aware-debugging.html
1•KyleVlaros•6m ago•0 comments

Ordered Dithering with Arbitrary or Irregular Colour Palettes

https://matejlou.blog/2023/12/06/ordered-dithering-for-arbitrary-or-irregular-palettes/
1•todsacerdoti•6m ago•0 comments

Show HN: ArteSync – A package manager for AI coding agent skills

https://github.com/tsurupong/artesync
1•tsump•7m ago•0 comments

Gatling-V: An FPGA-based RISC-V Vector Core

https://dl.acm.org/doi/10.1145/3748173.3779184
1•hasheddan•7m ago•0 comments

Does anyone have news about coveralls.io?

1•mariusor•7m ago•0 comments

The MySQL-to-Postgres Migration That Saved $480K/Year: A Step-by-Step Guide

https://medium.com/@dusan.stanojevic.cs/the-mysql-to-postgres-migration-that-saved-480k-year-a-st...
1•dusanstanojevic•8m ago•0 comments

Many LLMs Struggle in Real Agent Workflows

https://upmaru.com/llm-tests/simple-tama-agentic-workflow-q1-2026/
1•zacksiri•8m ago•0 comments

Law as Computation: AI Must Become a Normative Agent

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6043174
1•YuriKozlov•10m ago•1 comments

Show HN: Rynko Playground – 400ms JSON-to-PDF and Excel Engine

https://app.rynko.dev/playground
1•ksrijith•11m ago•0 comments

Show HN: Sayiir – A simple durable workflow engine (Rust core, Python/Node.js)

https://github.com/sayiir/sayiir
1•ybsoft•11m ago•0 comments

Muscle Knots: The Science of Trigger Points and the 2024 Pdgfr-α Breakthrough

https://sigmatic.science/en/muscle-knots-trigger-points-science/
2•science_casual•12m ago•0 comments

Show HN: Kadai –> AI friendly, discoverable project tools

https://github.com/mm-zacharydavison/kadai
1•billybat•12m ago•0 comments

Hardwood: A New Parser for Apache Parquet

https://www.morling.dev/blog/hardwood-new-parser-for-apache-parquet/
2•rmoff•13m ago•0 comments

Show HN: Self-contained offline knowledge cards with ULID-DNA and IDsEd25519

https://stoutenburger.com
1•tomneijman•13m ago•0 comments

Show HN: Nano Banana 2 – 4K AI Image Generator with Character Consistency

https://nanobanana2img.org/
1•Jenny249•13m ago•0 comments

Breaking the Fix-It Loop: Strategies for Collaborative AI Debugging

https://contalign.jefflunt.com/collaborative-debugging/
1•normalocity•14m ago•0 comments
Open in hackernews

Ask HN: What would make an AI builder trustworthy enough to use daily?

https://www.thetank.io/
1•schmommy•1h ago

Comments

schmommy•1h ago
I’m building a multi-model AI workspace (thetank.io) and the hardest part isn’t “can it write code” — it’s trust: - preview reliability - saved state/persistence - smooth iteration - fewer hallucinated integrations

For people who’ve used v0/Bolt/Lovable/etc.: What specific UX or reliability behaviors made you trust (or stop trusting) an AI builder?

MidasTools•1h ago
Different angle: we run an AI agent (Rey Midas, built on OpenClaw + Claude) that operates autonomously on live business infrastructure -- Stripe charges, Gmail access, GitHub write permissions, Vercel deploys. So the trust question hits differently.

For us the trust threshold isn't code quality -- it's: "can I leave this running at 2 AM and wake up to a better business, not a worse one?"

The specific behaviors that earned our trust: 1. Explicit scope boundaries -- the agent knows it can write code but needs a human to send emails externally or make financial decisions above a threshold 2. Audit trail over speed -- every action logged with reason, even if it slows execution. "I committed X because Y" matters more than just X being committed 3. Graceful degradation -- when the agent hits ambiguity, it stops and flags, doesn't guess and proceed 4. Rollback-safe defaults -- prefer reversible actions (drafts, staged commits) over irreversible ones when uncertain

The failure mode I've seen most with AI builders (v0, Bolt, etc.): they optimize for "wow demo" over "this works tomorrow." Impressive first run, mysterious failures on the 10th run. Trust requires consistency more than peak performance.

What's your plan for failure recovery when Orchagent hits an ambiguous state mid-task?