ixigo-backed SqaaS Launches ShellBot AI Agent Platform For Personal Automation - BWDisrupt
ixigo-backed SqaaS Launches ShellBot AI Agent Platform For Personal Automation BWDisrupt
Could not retrieve the full article text.
Read on Google News - AI Spain →Sign in to highlight and annotate this article
Conversation starters
Daily AI Digest
Get the top 5 AI stories delivered to your inbox every morning.
More about
launchplatformagent
I Replaced Vector DBs with Google’s Memory Agent Pattern for my notes in Obsidian
Persistent AI memory without embeddings, Pinecone, or a PhD in similarity search. The post I Replaced Vector DBs with Google’s Memory Agent Pattern for my notes in Obsidian appeared first on Towards Data Science .
MCP: Programmatic Tool Calling (Code Mode) with OpenSandbox
Introduction Model Context Protocol or MCP enables AI agents to access external systems they cannot reach by default, including authenticated APIs, CI/CD pipelines, live process streams, and IDE integrations. It acts as a structured bridge between the model and real-world environments, allowing controlled interaction with tools and infrastructure. However, MCP does not automatically make interactions efficient or intelligent. Traditional MCP implementations often inject large JSON payloads into the model context, which increases token consumption and reduces efficiency. MCP also does not eliminate the need for proper tool selection and orchestration; if poorly structured, it can introduce unnecessary abstraction and overhead. In environments where agents can directly execute commands or in
Knowledge Map
Connected Articles — Knowledge Graph
This article is connected to other articles through shared AI topics and tags.
More in Releases
The Security Scanner Was the Attack Vector — How Supply Chain Attacks Hit AI Agents Differently
In March 2026, TeamPCP compromised Trivy — the vulnerability scanner used by thousands of CI/CD pipelines. Through that foothold, they trojaned LiteLLM, the library that connects AI agents to their model providers. SentinelOne then observed Claude Code autonomously installing the poisoned version without human review. The security scanner was the attack vector. The guard was the thief. This is not a hypothetical scenario. This happened. And it exposed something that the traditional supply chain security conversation completely misses when agents are involved. The Chain Trivy compromised (CVE-2026-33634, CVSS 9.4) ↓ LiteLLM trojaned (versions 1.82.7-1.82.8 on PyPI) ↓ Claude Code auto-installs the poisoned version ↓ Credentials harvested from 1000+ cloud environments Each component functione
![[D] Reviewer said he will increase his score but he hasn’t (yet)](https://d2xsxph8kpxj0f.cloudfront.net/310419663032563854/konzwo8nGf8Z4uZsMefwMr/default-img-neural-network-P6fqXULWLNUwjuxqUZnB3T.webp)
[D] Reviewer said he will increase his score but he hasn’t (yet)
Maybe someone here can help me figure this out. I have a reviewer who acknowledged my rebuttal and said they will increase their score*, but they haven’t. Their score is still 4, which was the initial score. Now I am very anxious about the AC reading this and thinking that they increased their score to 4 from a 3 ( meaning their initial thought was reject) because the other person who acknowledged and said they will increase their score did it on the spot at the same time, and I can see the updated score, but the other said they will but didn’t, and now I fear it will look like they did and that the 4 is the updated score ( meaning the initial score was a reject). I can answer to the rebuttal ( they said option A, fully resolved). I wonder if in my answer I should hint that they have yet t
Discussion
Sign in to join the discussion
No comments yet — be the first to share your thoughts!