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In this episode of The Context Window, Brandon Mathis and Jonathan Fontanez explore a provocative question emerging in AI-assisted development: could Markdown become the next programming language? Using examples from agentic workflows, Claude Code skills, MCP integrations, and evolving AI harnesses, they unpack how structured Markdown files are increasingly being used to orchestrate repeatable workflows, prototype systems, and guide AI agents with surprisingly programmatic behavior.
The conversation digs into the tradeoffs of treating Markdown like executable infrastructure, including maintainability, entropy, security risks, token costs, hallucinations, and the challenges of testing non-deterministic workflows. Brandon and Jonathan debate where Markdown-based “programming” fits compared to traditional software engineering, especially for short-lived automations, prototyping, internal tooling, and rapidly evolving startup environments. Along the way, they discuss concepts like skill.md files, harness maturity, vibe coding, structured prompting, evals, repeatable workflows, and how AI agents are reshaping the boundary between natural language and software development itself.
In This Episode, You’ll Learn:
- How AI agents are turning Markdown into a lightweight way to define repeatable development workflows
- Why short-lived automations and fast-moving projects may benefit from “programming” with Markdown instead of traditional code
- The risks involved with agentic workflows, including hallucinations, security concerns, token costs, and workflow entropy
- How skills, MCPs, and AI harnesses work together to connect agents to external systems and automate real engineering tasks
- A practical framework for deciding when to use prompts, Markdown workflows, or full software systems in AI-assisted development
Brandon Mathis on Linkedin: https://www.linkedin.com/in/mathisbrandon/
Jonathan Fontanez on Linkedin: https://www.linkedin.com/in/jonathan-fontanez-27715428/
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