Creator · youtube

@Thomas Landgraf

SPECLAN is a free VS Code extension for spec-driven development in the AI age. Short, concrete walkthroughs of how specs survive agentic coding. Product Owners own intent. Dev teams (human and AI) implement against governed requirements. Six statuses — draft → review → approved → in-development → under-test → released — act as ownership handoffs between roles. Specs are Markdown + YAML frontmatter, committed to Git alongside the code. AI agents read them through MCP tools, not copy-pasted prompts. Works with Claude Code, Cursor, and GitHub Copilot. For POs, dev teams adopting AI coding, QA engineers, solo devs, and eng leads bringing discipline to vibe-coded codebases. Full disclosure: I'm the creator. SPECLAN is a side project — free, open source, try it yourself. Install: https://marketplace.visualstudio.com/items?itemName=DigitalDividend.speclan-vscode-extension Docs: https://speclan.net GitHub: https://github.com/thlandgraf/speclan-essentials

496followers136median recent views · n=60 posts246 · 1.8×best post · Excalidraw · vs own median1apps in the library · 0 with a standing program1posts audited
2025-11audited posts / month2026-10
Who they post for1 apps · public relationship evidence

0 standing programs, 0 ambassador-level feeds and 0 disclosed paid relationships in this sample. Repeated posting describes dedication; it does not prove a fee.

ExcalidrawCoding & app building · 1 posts audited
Unknownunverified relationship
Recent feed1 of 60 posts mention it
2462026-05-31
“Diagrams Your AI Coding Agent Can Actually Read — Excalidraw in VS Code” — https://www.youtube.com/watch?v=QQ81eCAjElk; public page reviewed, but no Excalidraw-specific commercial disclosure or tracked Excalidraw link was found. The post that identifies it →
The script they keep usingcounted from 1 audited posts
How they open1 of 1 audited posts run Capture context, then hand off the work. The lines below are the openings of their most-viewed posts.
Audited posts1 in sample · ranked by views · hover a frame to scrub

Followers, medians and views as captured in the research release. A multiple compares the post to the creator’s own recent median. Relationship labels describe the public evidence, never the amount paid. Definitions in the methodology.