In a recent LinkedIn post, Ruben Hassid offers a comprehensive guide to maximizing the capabilities of Claude AI, moving beyond basic chatbot interactions to unlock advanced features. Hassid, a proponent of sophisticated AI utilization, outlines 26 distinct strategies aimed at users who have already moved past introductory prompts and are seeking deeper integration and efficiency with the AI model.
Hassid emphasizes the distinction between the Claude desktop application and its web-based counterpart, advocating for the former as the primary interface for advanced workflows. He introduces the concept of ‘Cowork’ within the app, suggesting that using a traditional chat interface is akin to using a tool from a previous era.
“Use Cowork, not the chatbot. If you’re typing into a chat box, you’re using it like it’s 2025.”
The post details a fundamental shift in managing AI interactions, advocating for ‘Skills and Projects’ as the core organizational system, rather than traditional file structures. Hassid argues that folders can inadvertently introduce outdated information into an AI’s context, complicating its responses.
Rethinking AI Interaction and Context Management
Ruben Hassid’s strategy centers on teaching Claude specific capabilities once as ‘skills’ and using ‘projects’ as dedicated workspaces for ongoing tasks. This approach aims to streamline interaction and ensure that relevant information is consistently accessible without manual re-entry.
The Role of Skills and Projects
Hassid explains his system, stating:
“A skill is a capability you teach once. A project is a place you go back to.”
He further advises users to delete their ‘about-me’ files and rebuild them as skills, ensuring this personal context is available across all conversations. For those unsure how to implement this, Hassid provides a free guide via his welcome email upon subscribing to how-to-ai.guide, which includes a downloadable library of Claude skills.
Optimizing Claude’s Performance and Cost-Effectiveness
A significant portion of Hassid’s advice focuses on optimizing Claude’s performance and managing the associated costs, which are directly tied to token usage. He highlights a critical limitation of the AI:
“The longer your chat, the dumber it gets. Anthropic’s own engineers said it out loud.”
To counter this, Hassid recommends restarting conversations from earlier points rather than attempting to correct a degraded context. He also points out the financial implications of prolonged interactions, noting that each word exchanged costs money. Hassid suggests using more advanced models like Opus 5 High for general tasks and a more focused approach for complex problems, emphasizing efficiency by limiting conversational turns and switching models strategically.
Prompting and Output Verification
Hassid’s guidance extends to how users should interact with Claude. He advocates for providing the AI with a clear goal rather than a step-by-step process, allowing it to operate more effectively. He also issues a stern warning about sensitive information:
“Don’t paste logins, passwords, or keys. Ever.”
Furthermore, Hassid stresses the importance of critically evaluating Claude’s output. He advises users to prompt Claude to audit its own answers before trusting them, as the AI can present incorrect information with high confidence. He also recommends asking for multiple distinct versions of an output to leverage the user’s own taste and judgment in the final selection. The overarching principle, as articulated by Hassid, is to:
“outsource the thinking, never the understanding.”
This principle underscores the need for users to retain critical comprehension and decision-making while delegating the more intensive cognitive load to the AI.
📝 About This Content
This article is based on insights shared by Ruben Hassid on LinkedIn.
📅 Originally posted on July 27, 2026 | View original post on LinkedIn →