Observed Signal · Jul 20, 2026 · Thought Leadership · Source: UX Collective · Impact: 1/5 · Sentiment: Neutral
Using Claude Code to Make Research a Living Artifact
The article describes how the author uses Claude Code as a 'thinking partner' and an 'artifact maker' to improve the research process. It notes that Claude Code can search the web, compare products, synthesize documents, and organize results into templates. The author emphasizes two moments where the tool changes their work: while research is still open (to challenge assumptions) and when research results are handed to product teams (to create reusable artifacts). The page metadata shows the article was published on 2026-07-20.
Practical UX research workflow using an LLM; relevant to general research and product teams but not a major industry event for AdTech/MarTech.
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Key Takeaways & Evidence Grounding
- Claude Code can search the web, compare products, synthesize documents, and organize results into a template.
- The author uses Claude Code in two roles: as a 'thinking partner' during open research and as an 'artifact maker' when research enters a product team.
- The article is titled "Research shouldn’t end in a deck" and was published with metadata timestamp 2026-07-20T22:02:19Z.
Connected Companies & Entities
1 Entity mapped“Image and author profile link referencing https://miro.medium.com/... and https://medium.com/@sunless77 in the article header....”
Ontology Mapping & Concepts
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Writer-Researcher's Guide to Claude Code
Mario Gabriele describes building a full-stack, agent-driven knowledge-management system using Claude models and local tooling. His system (nicknamed Delphi) indexes more than 45,000 searchable chunks drawn from The Generalist archive, podcasts, Obsidian notes, Readwise highlights, Google Drive and desktop files. Search combines Voyage-3 embeddings, SQLite FTS5 keyword search and a locally trained cross-encoder reranker distilled from Cohere and fine-tuned on ~40K MS MARCO query–passage pairs. A suite of background agents (using tools such as Jina, Firecrawl and headless browsers) scrapes articles, transcripts and paywalled content the author can access, automates research tasks, and prepares consolidated reports. The piece is a hands-on guide and case study demonstrating how recent Claude model upgrades and agentic workflows can accelerate research and personal productivity.
When Claude Saves Your Workflow
A developer's guide to using Claude in production workflows, describing where the model excels (complex reasoning, code refactoring, documentation, prototyping) and where it wastes time (debugging weird errors, domain-specific business logic, simple formulaic tasks). The author shares practical strategies—use Claude as a thinking partner, limit multi-turn conversations, and verify outputs—and reports project metrics (e.g., 3x faster code reviews, 40% faster Vue migration). The piece highlights operational gotchas such as token costs, multi-turn context degradation after ~20 exchanges, and confident hallucinations that require verification. It concludes that Claude is valuable for reasoning and transformation tasks but not a substitute for domain expertise or debugging unknown failures.
Using Claude AI for Equity Investing
This guest post (published 2026-05-21) by Michael Fritzell explains practical workflows for using Anthropic's Claude large language model to support equity research and portfolio analysis. The article outlines four use cases (Research, Projects, Skills, Cowork) and describes hands-on techniques such as instructing Claude Code to scrape 10‑K/SEC filings and using Anthropic's Model Context Protocol (MCP) to connect Claude to live financial databases and brokerages. The piece also catalogs recent Anthropic product launches—including Claude Cowork (released late January 2026), Claude Design, Claude Marketplace, and Claude integrations for Excel/PowerPoint/Word/Chrome—and positions Claude as an increasingly important tool for investors and analysts.
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