This article lays out a six-phase process for an AI agent to methodically mine, analyze, and reflect a user’s entire history of AI sessions. It details precise steps—from excavating archives to delivering actionable insights and tool reconfigurations—ensuring each phase has clear gates, evidence requirements, and user approvals.

This guide breaks down 12 steps to automate a quant desk inside one platform: from scheduled research and thesis writing to strategy backtesting, paper trading, and live execution. It highlights verifier gates—trade audits, paper runs, and alert-only tests—to ensure the loop refines itself and controls risk at every stage.

This newsletter highlights Microsoft’s new MAI-Image-2.5 model and Apple’s upgraded Image Playground, then breaks down Lovable’s self-reported growth metrics. It also links to design essays on embracing human flaws, writing decisions before mockups, and moving from rigid design systems to product context, plus a roundup of tools and case studies.

This article lists nine free or one-time-purchase Mac apps that tackle little annoyances in macOS—from using the notch as a file shelf and hiding menu-bar clutter to boosting file transfers, window management, screenshots, local AI, and cleanup. Each tool solves a specific pain point so the system feels smoother without ongoing subscriptions.

PPT Master is an open-source Python skill that runs inside AI IDEs (Claude Code, VS Code Copilot, Cursor) to turn PDFs, DOCX, URLs or Markdown into fully editable PowerPoint decks with real shapes, text boxes, and charts—not images. It runs locally, keeps your data off third-party servers, and costs only your AI model usage.

This article shows how solving complex problems benefits from a team of AI agents with roles like planner, doer, tool operator, critic, supervisor, and presenter. It breaks down each subagent’s function and gives tips on prompting, model choice, tuning, and context setup. The CDN-Folk case illustrates how a team of agents designed, validated, and deployed a content delivery network faster than traditional methods.

Thomas lists his go-to Chrome extensions, explaining how each speeds up tasks like video messaging, data extraction, image downloading and password management. He covers daily essentials like Loom, Dashlane and Table Capture, plus situational tools for full-page screenshots, color picking and batch link processing.

The author describes a pattern of prototyping workflows with AI agents then refactoring into code-driven processes, using agents only for tasks that require human-like judgment. A security vulnerability alert system illustrates how webhooks filter and route high-priority issues, delegating owner identification to an agent and formatting alerts via a second agent for reliable Slack notifications.

Ultraplan is a research-preview feature in Claude Code v2.1.91+ that drafts a plan for your codebase remotely. You launch it from the CLI, review and comment on the plan in a browser interface, then choose to have Claude implement it on the web or send it back to your local terminal for execution.

This article discusses the integration of Engram, a memory product built on Weaviate's vector search technology, into Claude Code. It explores the challenges and improvements in memory recall, particularly how Engram captures contextual details that MEMORY.md cannot, ultimately enhancing workflow efficiency.

Superpowers is a software development tool that enhances coding agents by guiding them through a structured workflow. It starts with clarifying project goals and progresses through design, implementation, and testing, all while ensuring code quality and adherence to best practices. The system automatically activates relevant skills for each task, streamlining the development process.

Mermaid is a tool that converts natural language or Markdown into diagrams like flowcharts and ER diagrams. It integrates with existing workflows, allowing real-time collaboration and customization. Ideal for teams needing to visualize ideas quickly and effectively.

The article discusses the author's experiences with Gas Town, an LLM orchestrator designed to manage multiple Claude Code instances. It highlights the potential challenges and benefits of adopting such a system, including workflow visibility, task management, and the need for better planning and coordination.

Boris Cherny shares his efficient setup for using Claude Code, highlighting the importance of customized workflows and verification processes. He details various strategies, such as running multiple sessions in parallel, using slash commands, and maintaining a shared repository for continuous improvement.

Andrei Kaparthy's insights on AI's role in work resonate with many, prompting a reflection on how to integrate these ideas into data engineering practices. The article emphasizes the importance of mastering fundamentals to effectively evaluate AI-generated work and encourages active participation in the evolving landscape of technology.