As agent harnesses become more standardized, we’re going to see a lot more “managed agent services”
AUTOMATION
-
Perplexity Computer now helps prepare federal tax returns
By
–
https://t.co/b774dXzDJ7 https://t.co/NeC9DfB4rI
— Aravind Srinivas (@AravSrinivas) 28 mai 2026Perplexity Computer can now help prepare your federal tax return. Select “Navigate my taxes” on Computer to give it a shot.
-
Surgical Humanoid Robot Achieves FDA Clearance for Spine Surgery
By
–
World’s First Surgical Humanoid #Robot Achieves FDA-Cleared Precision in Spine Surgery
— Ronald van Loon (@Ronald_vanLoon) 28 mai 2026
by @StarSnap_1#MedTech #Healthcare #HealthTech #Tech #TechForGood pic.twitter.com/iP2mo94AI8World’s First Surgical Humanoid #Robot Achieves FDA-Cleared Precision in Spine Surgery
by @StarSnap_1 #MedTech #Healthcare #HealthTech #Tech #TechForGood -
Integrating MagicPath AI Agent Skill with Cursor for Code Automation
By
–
For Cursor to communicate with MagicPath, it needs our agent skill. Just paste this inside the Cursor chat. "Install this skill npx skills add https://
github.com/magicpathai/ag
ent-skills
… –skill magicpath" The agent will walk you through the installation, logging into our app and the CLI. If you -
AI Agents Need to Learn from Executions for Meaningful Functionality
By
–
I've been waiting for something like this for a while. Agents that don't learn from their executions make no sense.
-
Self Improving AI beats Karpathy’s autoresearcher by improving itself
By
–
Self Improving AI (SIA) beats Karpathy's autoresearcher agent by improving itself!
— Sumanth (@Sumanth_077) 28 mai 2026
SIA is a Self Improving AI framework to autonomously improve the performance of any AI system (Model / Agent) on a benchmark task.
Most agent frameworks are static. Fixed harness, fixed model… https://t.co/bk4BaLqsCE pic.twitter.com/kiByM7J0KvSelf Improving AI (SIA) beats Karpathy's autoresearcher agent by improving itself! SIA is a Self Improving AI framework to autonomously improve the performance of any AI system (Model / Agent) on a benchmark task. Most agent frameworks are static. Fixed harness, fixed model
-
AutoScientists: Decentralized AI Agents for Scientific Research
By
–
Banger paper from Harvard. AutoScientists drops the central planner entirely. Agents interpret shared experimental data, self-organize around promising directions, evaluate proposals before resource allocation, and document successes AND failures. Decentralized AI co-scientists
-
Systematic failures in long agent runs: repetition, forgetting, high API bill
By
–
You have probably seen this with Claude Code or any long agent run: – it repeats work
– it forgets a decision
– it argues with stale instructions
– it misses the exact file you mentioned earlier
– the API bill keeps climbing That is not random. -
General-Purpose AI Agent Surpasses Karpathy’s Auto-Researcher by Self-Improvement
By
–
A GENERAL-PURPOSE AGENT SURPASSED KARPATHY'S AUTORESEARCHER It wasn't designed for research. It simply improved itself until it achieved it The framework behind it is called SIA by Hexo Labs and it's open source → The agent updates its own logic
→ Modifies its own weights -
Developers Using AI Agents for Large Pull Requests
By
–
Developers are using agents to write more "mega PRs."