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Article URL: https://kirit.com/Blog:/2026/02-27-AI%20Assisted%20coding

Comments URL: https://news.ycombinator.com/item?id=47178195

Points: 1

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Article URL: https://sixcolors.com/post/2026/02/apple-announces-f1-details-and-a-surprising-netflix-partnership/

Comments URL: https://news.ycombinator.com/item?id=47178194

Points: 1

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Article URL: https://github.com/apache/logging-log4j2/discussions/4052

Comments URL: https://news.ycombinator.com/item?id=47178187

Points: 1

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Article URL: https://techxplore.com/news/2026-01-generation-disinformation-ai-swarms-threaten.html

Comments URL: https://news.ycombinator.com/item?id=47178158

Points: 1

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Article URL: https://openclaw.ai/blog/virustotal-partnership

Comments URL: https://news.ycombinator.com/item?id=47177861

Points: 1

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Article URL: https://github.com/ryan-allen/scarnon

Comments URL: https://news.ycombinator.com/item?id=47177858

Points: 1

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Article URL: https://www.xda-developers.com/sudo-rs-password-asterisk-entry/

Comments URL: https://news.ycombinator.com/item?id=47177851

Points: 1

# Comments: 0

Article URL: https://takeinterest.ai/guardclaw

Comments URL: https://news.ycombinator.com/item?id=47177832

Points: 1

# Comments: 1

I kept running into the same problem: trying to find something new to watch, opening multiple streaming apps, and Googling titles one by one because the apps don't tell you if something is actually worth watching.

So I built What to Watch, which aggregates content across major streaming services and reduces discovery to a simple Watch or Skip decision using IMDb and community ratings.

I hadn’t written code since high school — this was built over ~400 iterations using Claude and Replit.

Still very early and mostly trying to learn how people actually decide what to watch and how broad this use case is. Would love feedback from the HN community.

Comments URL: https://news.ycombinator.com/item?id=47177814

Points: 1

# Comments: 1

Article URL: https://atoship.com/docs/integrations/openclaw

Comments URL: https://news.ycombinator.com/item?id=47177794

Points: 1

# Comments: 0

Article URL: https://pudding.cool/2026/02/happy-map/

Comments URL: https://news.ycombinator.com/item?id=47177788

Points: 1

# Comments: 0

Article URL: https://www.cnn.com/2026/02/26/business/block-layoffs-ai-jack-dorsey

Comments URL: https://news.ycombinator.com/item?id=47177785

Points: 1

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Article URL: https://mailvaultapp.com/

Comments URL: https://news.ycombinator.com/item?id=47177782

Points: 2

# Comments: 1

Hi all,

We’ve been thinking about a core limitation in current mobile AI assistants:

Most systems (e.g., Apple Intelligence, Google Assistant–style integrations) rely on predefined schemas and coordinated APIs. Apps must explicitly implement the assistant’s specification. This limits extensibility and makes the ecosystem tightly controlled.

On the other hand, GUI-based agents (e.g., AppAgent, AutoDroid, droidrun) rely on screenshots + accessibility, which gives broad power but weak capability boundaries.

So we built Mobile-MCP, an Android-native realization of the Model Context Protocol (MCP) using the Intent framework.

The key idea:

- Apps declare MCP-style capabilities (with natural-language descriptions) in their manifest.

- An LLM-based assistant can autonomously discover all exposed capabilities on-device via the PackageManager.

- The LLM selects which API to call and generates parameters based on natural language description.

- Invocation happens through standard Android service binding / Intents.

Unlike Apple/Android-style coordinated integrations:

- No predefined action domains.

- No centralized schema per assistant.

- No per-assistant custom integration required.

- Tools can be dynamically added and evolve independently.

The assistant doesn’t need prior knowledge of specific apps — it discovers and reasons over capabilities at runtime.

We’ve built a working prototype + released the spec and demo:

GitHub: https://github.com/system-pclub/mobile-mcp

Spec: https://github.com/system-pclub/mobile-mcp/blob/main/spec/mobile-mcp_spec_v1.md

Demo: https://www.youtube.com/watch?v=Bc2LG3sR1NY&feature=youtu.be

Paper: https://github.com/system-pclub/mobile-mcp/blob/main/paper/mobile_mcp.pdf

Curious what people think:

Is OS-native capability broadcasting + LLM reasoning a more scalable path than fixed assistant schemas or GUI automation?

Would love feedback from folks working on mobile agents, security, MCP tooling, or Android system design.

Comments URL: https://news.ycombinator.com/item?id=47177770

Points: 1

# Comments: 0

Article URL: https://www.reuters.com/business/blocks-fourth-quarter-profit-rises-announces-over-4000-job-cuts-2026-02-26/

Comments URL: https://news.ycombinator.com/item?id=47177733

Points: 1

# Comments: 0

Article URL: https://finditsales.substack.com/p/why-the-storytellers-will-win-the

Comments URL: https://news.ycombinator.com/item?id=47177732

Points: 1

# Comments: 0

Article URL: https://github.com/openoctp/spec

Comments URL: https://news.ycombinator.com/item?id=47177702

Points: 1

# Comments: 1

Article URL: https://evanhahn.com/introducing-gzpeek/

Comments URL: https://news.ycombinator.com/item?id=47177700

Points: 1

# Comments: 0

CISA has released an advisory to warn about four vulnerabilities discovered by a researcher in Gardyn Home and Gardyn Studio.

The post Critical Flaws Exposed Gardyn Smart Gardens to Remote Hacking appeared first on SecurityWeek.