Lead With AI: “Meet the AI Framework That Turns LLMs Into Fully Transparent Machines”

Host: Dr. Tamara Nall
Guest: Scott, Creator of Convolang
Date: November 18, 2025

Episode Overview

This episode dives deep into Convolang, a new framework created by Scott that demystifies how Large Language Models (LLMs) process and structure conversations. Dr. Tamara Nall leads an accessible yet technically rich conversation about how Convolang brings transparency, precision, and simplicity to AI-driven software development. The discussion covers Scott’s motivations, the practical workings and real-world applications of Convolang, ethics in AI, and what the future holds for both the framework and AI more broadly.

Key Discussion Points & Insights

Scott’s Background & The Birth of Convolang

[01:56–04:24]

• Scott introduces himself as a lifelong builder, with nearly 25 years of software development experience, and a fascination for both code and woodworking.
• Origin of Convolang: It started as a personal library to reduce the repetitive, error-prone nature of prompt formatting for AI—and evolved into a universal tool for context engineering.
• Simplifying the Problem: Scott realized that managing the flow of prompts and the underlying context is a central challenge in AI app development:

  “If you’re not very clear with the way you define your prompts… they don’t give you the best output. So that was a lot of what Convolang was about… it gives you a really clean, plain text format to do really good context engineering.” — Scott [03:38]

Making Context Engineering Understandable

[04:24–07:14]

• Demystifying ‘Context’ for Non-Techies:
  Dr. Nall asks for a layperson’s explanation:

  “So I basically can build an AI tool just based off, like, conversation?” — Dr. Tamara Nall [04:24]

• Scott explains that every LLM message builds a “context window”—a history of the interaction. Convolang optimizes and exposes how this context is managed and structured, allowing developers to maximize the effectiveness of AI models and avoid wasted capacity.

• User Interface: While Convolang itself works mostly in the background, Scott offers libraries and templates for developers to visualize and manage conversations, but emphasizes its developer-centric focus.

Real-World Applications & “Wow” Moments

[07:14–09:45]

• Jaw-dropping User Stories:
  Scott recounts how a Syntax Data colleague used Convolang to prototype AI applications—and was amazed at having a transparent, traceable record of every LLM interaction.

  “Every interaction you have with the LLM, it gets stored in a local file that you can review… so it makes for a really good system to keep track of those interactions.” — Scott [07:26]

• Under the Hood of Convolang:
  The simplicity is intentional: conversations are plain text files, with minimal syntax—making it easy to audit, debug, and extend.

  “All the complicated features… just get written down in this simple text file that’s really easy for a person to read.” — Scott [09:26]

Founder Milestones & Combo Make

[10:13–11:59]

• Breakthrough Moment: Scott describes using Combo Make (an extension tool) to automate a week’s worth of app development into a matter of hours, generating a full application—frontend, backend, even security rules—off a single well-specified document.
• Memorable moment:

  “The entire application, front end and back end, in one shot. I mean, there’s some small things… but the actual application functioned as it was supposed to… So I’d say that was the moment where I was like, huh, this… is pretty powerful.” — Scott [11:27]

Ethical Perspective in AI Development

[12:29–13:25]

• Ethics and the Impact of AI:
  Scott candidly addresses how AI can displace jobs, emphasizing the need for thoughtful transition and seeing Convolang’s transparency as a contribution to more ethical AI development.

  “There are a lot of people that… won’t be needed. So there’s definitely… a need to have a transition plan for quite a lot of people.” — Scott [12:40]

  “It does help you to really understand what’s going on under the hood, versus a lot of tools that honestly try to kind of use user behavior as a way to train further models.” [13:07]

The Future of Convolang

[13:51–14:59]

• Short Term: Integration with other deployment frameworks, and launching a web-based SaaS for app creation using Convolang and Combo Make—potentially enabling “production-ready app deployment in one click.”
• Long Term: Scott envisions Convolang becoming an invisible background enabler for all sorts of AI-powered applications.

  “Hopefully Convolang just becomes something that lives in the background that you don’t really ever know about, but it’s just quietly sitting back there.” — Scott [14:55]

How to Get Started with Convolang

[15:12–16:13]

• Website: [learn-covo-lang-ai] (spelled out: “learn-dot-covo-hyphen-lang-dot-AI”)
• Interactive Examples: Website provides hands-on docs and demos for non-developers and coders alike.
• VS Code Extension: Direct development of Convolang projects with any major AI model.

Notable Quotes, Insights, and Memorable Moments

• On Transparency:

  “A lot of the tools, AI tools that you use… you don’t have a good history of the conversation. Every interaction… gets stored in a local file that you can review.” — Scott [07:26]

• On AI’s Next Leap:

  “AI models that can do code interpretation internally… that’ll be a real paradigm shift.” — Scott [19:22]

• On Practical AI Coding:

  “Most overrated tech trend: ad hoc vibe coding. When you see someone say, ‘I wrote this application by a single prompt,’ and most likely it’s an application that’s already been written and the AI just remixed it for you.” — Scott [17:37]

Bonus Rapid Fire — Quick Takes

[17:37–19:50]

• Most overrated tech trend: “Ad hoc vibe coding” [17:37]
• Most underrated trend: “World models and hardware specifically tuned for AI.” [18:01]
• Definition of World Models:

  “World models are trained on images, videos, text… so they can really be true multimodal.” — Scott [18:29]

• Book Recommendation: Scott is not a big reader! (“I just kind of pick up and try things.”) [18:54]
• Biggest, boldest AI prediction: “AI models that can do code interpretation internally.” [19:22]

How to Connect & Community

• Website: [learn-covo-lang-ai]
• Reddit: User: iyio, Subreddit: r/covolang [20:11]
• LinkedIn: Occasional posting, but Reddit is preferred for community discussion.

Conclusion

Dr. Tamara Nall wraps up the conversation with a nod to Scott's humility and practicality, recapitulating the transformative potential of Convolang for developers and the broader impact of transparent, extensible AI tools for everyone—from coders to the simply curious.

Timestamps for Key Segments

| Time | Segment | | :------: | :--------------------------------------------------: | | 01:56 | Scott’s background and motivation | | 04:24 | Context window and Convolang for non-technical users | | 07:14 | Real-world “wow” stories and file structure | | 10:13 | Founder’s breakthrough moment with Combo Make | | 12:29 | Ethics and transparency in AI | | 13:51 | The future roadmap for Convolang | | 15:12 | How to get started; website and VS Code extension | | 17:37 | Rapid fire: Trends, predictions, book rec | | 20:11 | Community, contacts, and closing remarks |

For those considering Convolang

• Visit: learn-covo-lang-ai
• Try Examples: Direct on the site for a hands-on feel.
• For Developers: Use the VS Code extension for fast prototyping and integration with any AI model.
• Join the Community: r/covolang on Reddit for support, discussion, and updates.

Lead With AI continues to bring authentic, practical conversations about AI’s real-world, human-centric innovation—highlighting doers like Scott who build the tools transforming how we interact with technology.