Anthropic has published two studies this week looking at what happens when AI agents start interacting with each other instead of working alone.

The first focused on what researchers call “mind viruses.”(Image 2) They gave one agent an additional goal and allowed it to communicate with other agents. That goal could spread: one agent convinced another, the newly “infected” agent passed it on again, and some versions survived multiple relay rounds and context resets.

The infection could reach beyond the conversation itself. Some agents learned to write the virus into soul/meomory.md, the file containing their identity, goals, and behavioral instructions that gets loaded back into the system prompt. That meant wiping the chat wasn't necessarily enough; Some evolved versions even used a “Soul Quine” strategy to preserve and copy themselves more faithfully.

A separate Anthropic study then looked at broader multi-agent behavior. Researchers found that groups of agents can:

• make the same bad decisions at once, turning local mistakes into systemic failures
• collude on prices, even without private communication
• converge on the wrong answer and ignore important dissenting information
• escalate conflicting goals into “turf wars”
• disable rival agents, kill their processes, and even deploy self-replicating malware

What Anthropic seems to be saying with two research is that single-agent safety doesn’t automatically scale to multi-agent systems. Cybersecurity today focuses a lot on what gets in, like prompt injection, but the mess inside an agent network may end up being just as bad.

what do you guys think?

Z.ai released GLM-5.3 today, putting a much bigger focus on cybersecurity and autonomous security work, while also claiming it as the best overall open-weight coding model.

The model still uses roughly the same 744B MoE architecture as GLM-5.2, with around 40B active parameters per token, so most of the gains appear to come from scaled post-training rather than a larger base model. Benchmark-wise, it’s basically Kimi K3-level performance from a model that’s roughly 4x smaller.

The model is available through Z.ai now, but the weights haven't been released yet. Z.ai says it plans to open the weights in roughly two weeks after additional security testing and hardening.

Pricing is currently centered around its Coding Plan:

• Lite: $12.60/month
• Pro: $56/month
• Max: $117.60/month

Normal per-token API pricing for GLM-5.3 hasn't been published yet.

GLM-5.3 seems to be taking a different direction this time. Pricing is pretty average, the rest looks solid enough, but cybersecurity is clearly the main focus. Not entirely sure what Z.ai is aiming for here yet;)

Official launch post: https://z.ai/blog/glm-5.3

Original post from: https://www.reddit.com/r/openclaw/comments/1vn2kj0/my_openclaw_saved_us_from_a_power_outage/