My guest today is Ian Hogg, the Chairman of SolvedBy.ai, an applied AI company helping SaaS vendors embed enterprise-grade forecasting, demand and decision intelligence directly into their platforms. In this conversation,

• Ian shares his background, from the Royal Navy and Xerox to building early web businesses, a SaaS platform, and an AI-focused company.
• He describes how his SaaS business began by solving his own operational problem and then expanded when others in the industry recognized the same need.
• He shares how, In enterprise AI, one needs to distinguish decision-support and forecasting systems from generative AI
• Ian highlights that AI adoption in organizations depends heavily on leadership behavior
• The conversation also covers mindset barriers, the empowerment of non-technical users, and the need to build confidence through hands-on experimentation rather than waiting for formal permission or perfect readiness.
• On branding and customer acceptance, Ian explains that people may resist AI if it feels like replacement, but respond more positively when it is framed as assistive and human-in-the-loop.
• He shares career advice for both newcomers and mid-career professionals
• In closing, he shares aspects that help him stay grounded

Ian Hogg is Chairman of SolvedBy.ai, an applied AI company helping SaaS vendors embed enterprise-grade forecasting, demand and decision intelligence directly into their platforms.

He has spent his career building, scaling and investing in software businesses, with a particular focus on workforce management, SaaS partnerships and AI-driven operational optimisation.

Ian is a strong voice on the “SaaS apocalypse” — the idea that AI will expose weak, seat-based SaaS models while creating huge opportunities for vendors that own deep workflow, data and distribution.

At SolvedBy.ai, he is focused on helping SaaS companies add the AI layer their customers now expect, without needing to build specialist AI engines from scratch.

Ian may be reached at:

https://x.com/ianhogg88

https://www.linkedin.com/in/ianhoggworktechgroup/

https://solvedby.ai/

My guest today is a good friend and colleague - and not to forget with whom I was a co-author for a book, Paramu Kurumathur.

In this episode, Paramu discusses how his recent development work evolved from small Google Apps Script utilities copied and adapted from online examples to building AI-connected applications via APIs to tools like Gemini and ChatGPT, including enabling Q&A over his book content.

He describes surprises from “conversing” with his books—especially that LLMs retain details he has forgotten—while noting key risks such as hallucinations and the need for precise prompts. He explains learning Cursor with guidance from our colleague, Raja, discovering that it can generate code, and rapidly producing a proof of concept that maps citizens to the Government welfare schemes using PDFs, Chroma DB, sentence transformers, and queues—work that took about a week instead of months.

The conversation contrasts older development eras with today’s dependency-heavy environments, argues many SDLC intermediate steps are compressed, and highlights transferable mid-career skills in requirements and problem translation, alongside concerns about limited debugging and testing depth.

The timestamps are approximate and do not include the time for the intro. Add about 90 seconds to locate the section

00:00 Welcome and Setup

01:16 Rediscovering Coding via Apps Script

02:02 Connecting Scripts to LLM APIs

03:21 Talking to Your Own Book

05:32 Hallucinations and Prompt Control

06:50 Learning Cursor and Building a POC

09:09 Old School Dev vs Modern Tooling

12:00 AI Changes the SDLC

13:36 Testing and Trusting AI Output

15:10 Debugging Gaps and Assumptions

16:34 Setting AI Standards

17:20 Mid Career Transfer Skills

18:48 Prompting Without Hallucinations

20:21 Courses vs Learning by Doing

23:25 Overcoming First Step Fear

25:24 LLM Limits in Astronomy

28:24 Cursor for Reliable Code

29:37 Anybody Can Code Now

31:13 Next Projects and Wrap Up