Agents are quite good honestly. I played around with prompts to try to post engagement bait, study my past tweets that got high engagement, and optimize for replies and likes. I think letting agents run reliably with full autonomy and recursive feedback loops is around the
PROMPT ENGINEERING
-

CPGD: Stabilizing Rule-Based Reinforcement Learning for Language Models
By
–
CPGD: Toward Stable Rule-based Reinforcement Learning for Language Models CPGD introduces a novel reinforcement learning algorithm designed to stabilize policy updates for language models trained with rule-based rewards, addressing instability and training collapse issues found
-

II-Researcher: Advanced Research Assistant with LangChain Integration
By
–
II-Researcher A research assistant that combines search providers and web scraping with LangChain's text processing functionality to tackle complex questions. Features flexible LLM support and comprehensive data gathering capabilities. Explore on GitHub!
-
5 AI Prompts Transform Your Writing Forever
By
–
5 AI Prompts That Will Transform Your Writing Forever Want sharper content, faster? These five smart AI writing prompts could revolutionise how you write — whether it’s emails, blogs, or reports. Read more https://
bernardmarr.com/5-ai-prompts-t
hat-will-transform-your-writing-forever/
… #AIWriting #Productivity #ContentCreation -

Guardrails in AI Agents: Six Key Components for Success
By
–
And that is how we specify Guardrails in AI Agents!
— Akshay 🚀 (@akshay_pachaar) 24 mai 2025
Guardrails are powerful, which is why they are considered among the 6 things that make Agents great:
– Role
– Tools
– Focus
– Memory
– Guardrails
– Cooperation pic.twitter.com/eUTtST1HukAnd that is how we specify Guardrails in AI Agents! Guardrails are powerful, which is why they are considered among the 6 things that make Agents great:
– Role
– Tools
– Focus
– Memory
– Guardrails
– Cooperation -

Agent Error Handling and Guardrail Method Retry Mechanism
By
–
This time, we get the output shown in the image. The lines in yellow indicate the error message received from the guardrail method. The Agent retries a few times to fix it before it exits the program.
-

Understanding Failure in Guardrail Methods and Crew Execution
By
–
But now let's understand what happens upon failure. Let's intentionally ask it to generate a 200-word summary instead, keep the guardrail method the same, and kick off the Crew. Here's the code
-

Guardrails for Agent Output Validation and Word Limit Enforcement
By
–
Consider an Agent to summarize research topics. The summary must be under 150 words—a Guardrail. A Guardrail accepts the task's output and returns two values: • Success (True) or Failure (False).
• The validated output (success) or an error message (failure). Check this -

Implementing Guardrails for Reliable AI Agent Outputs
By
–
AI agents are powerful, but without safeguards, they can hallucinate, enter infinite loops, or give unreliable outputs.
— Akshay 🚀 (@akshay_pachaar) 24 mai 2025
Guardrails solve this. We can use them to:
• Limit tool usage
• Set validation checkpoints
• Specify fallback mechanisms
Below, let's implement them! pic.twitter.com/QuWzV5z5O4AI agents are powerful, but without safeguards, they can hallucinate, enter infinite loops, or give unreliable outputs. Guardrails solve this. We can use them to:
• Limit tool usage
• Set validation checkpoints
• Specify fallback mechanisms Below, let's implement them! -
Adding Guardrails to AI Agents for Safety Control
By
–
Stop your AI from going rogue! Let's learn how to add Guardrails to your AI Agents: