Take a sneak peak at the next phase of OmniMem a #Semantic #Memory layer for your #AI #agents .

We have a brand new dashboard in the works letting you manage memories even easier and drill down into the statistics.

Also coming are self building and evolving skills compiled from your experiences, preferences and knowledge.

100% #opensource

👉 https://omnimem.org

GitLost Attack Exploits GitHub Agentic Workflows Preview

🔗 https://cybersecurefox.com/en/gitlost-github-agentic-workflows-data-leak

#gitlost #github #agentic #workflows #ai #agents #prompt #injection #private #repositories

How Malicious AI Coding Skills Evade Static Scanners

🔗 https://cybersecurefox.com/en/malicious-ai-skills-bypass-static-scanners

#ai #agents #malicious #skills #static #scanners #skillcloak #skilldetonate

Google DeepMind is worried about what happens when millions of agents start to interact | MIT Technology Review https://www.technologyreview.com/2026/06/11/1138794/google-deepmind-is-worried-about-what-happens-when-millions-of-agents-start-to-interact/ #AI #Agents #interactions #RiskManagement

Want to get started using #Copilot Studio? Microsoft Learn has some free training available online. #AI #Agents

Mastering Copilot Studio https://learn.microsoft.com/en-us/shows/mastering-copilot-studio/

Did you know that `opencode` has a dynamic context pruning plugin?

It helps to ensure better quality through an optimized context window.

Here: with DeepSeek v4 Pro which (imho) is very close to Sonnet or GPT 5.4. And the differences matter less with DCP and a good setup.

https://github.com/Opencode-DCP/opencode-dynamic-context-pruning

#opencode #context #agents #vibecoding

claude-mem also allows you to add Skills for self-improving agents. For example after each run you can analyze the friction points and commit the learnings to the project memory.

Over time the agents then inherit the new status.

The question for me always is, how can I ensure that the agents read the Claude.md ?
These are not suggestions, but guardrails.

#claude-mem #self-improving #agents #memory

The Race Is on to Keep #AI #Agents From Running Wild With Your #CreditCards

#AIagents may soon be buying your stuff for you. The #FIDO Alliance has teamed up with #Google and #Mastercard to try to ensure that #shopping in the near future isn't a complete disaster.
#security

https://www.wired.com/story/the-race-is-on-to-keep-ai-agents-from-running-wild-with-your-credit-cards/

NEW BIML Bibliography entry

https://arxiv.org/pdf/2603.28052

Meta-Harness: End-to-End Optimization of Model Harnesses

Lee, Yoonho, Roshen Nair, Qizheng Zhang, Kangwook Lee, Omar Khattab, and Chelsea Finn

Harnesses for Agentic AI include perception and memory devices that allow an LLM to externalize and preserve state. This work describes iterating over a set of harnesses and finding better ones. Results are impressive.

#TOPPAPER #Agents #Engineering #LLM

https://berryvilleiml.com/bibliography/

Alt...

BIML cow

BLUG, Bergen 2026-05-28: Social anarchic, mad, and misbehaving agents collaboratively solving tasks v/Bjarte Johansen

https://blug.linux.no/events/2026-05-agents/

Bergen (BSD and) Linux User Group er tilbake!

#bergen #linux #agents #development #programming

What I thought then is still true today: to make something like a software agent legitimately useful for a lot of people would require a large amount of low-level grunt work and non-technical work (2) of the sort that the typical Silicon Valley company is unwilling to do. (3) The technology is the absolute easiest part of this task. Throwing a Bigger Computer at the problem leaves all those other pieces of work undone. It's like putting a bigger engine in a car with no wheels, hoping that'll make the car go.

By the way #AI companies and VCs, I'm available for contract work and have done due diligence research before if you ever want to stop wasting everyone's time and money!

#AI #GenAI #GenerativeAI #LLM #agents #hype #SiliconValley #VentureCapital #dev #tech

(1) Which we've been told repeatedly is essentially infinite time in the tech world.
(2) Establishing semantic data standards and convincing a large enough number of people to implement them being an important component. LLMs do not magically develop protocols and solve all the ETL-style problems of translating among different ones. The Semantic Web didn't really stick for a lot of reasons, but one reason is that it's hard!
(3) Back when I was still in the startup world I was asked several times by VCs to tell them what I thought about some new startup that claimed to be able to magically clean and fuse data. I think they're still very keen on investing in this style of magic, because it requires an intense amount of human labor, but I think where companies landed was invisibilizing low-paid workers in other countries and pretending a computer did the work they did. Which has also been happening for well over a quarter of a century.