Since the release of OpenAI’s GPT-3 in November 2022 generative AI has taken off and has widely become acknowledged as the fastest developing tech in human history. I have spent the past few months going from vague interest in AI developments to completing my thesis in industry investigating the potential application paths for AI within engineering.

Through this process I have tried to gain as much insight on general AI trends and news, seeking to understand the ways in which AI is going to change industry. I have engaged with seminars, domain academics and subscribed to a variety of AI centered newsletters.

Through this process I have been challenged with trying to keep up to date with developments and to grasp the full magnitude of what is happening. I have particularly struggled to find sources that provide insights into these developments for professionals in engineering and industry, both globally and within Australia.

As such I had the awesome idea of trying my own hand at making a newsletter that fits this niche, with the even more awesome name of Enginuity (don’t laugh). This is by no means polished and to start out is focused around my own learning and development. Over the next few months I am seeking to build up to 3 updates a week regurgitating my ideas, thoughts, general AI news and the articles and content I am enjoying in the space.

In this initial phase I am really seeking to iron out the form this newsletter will take, cleaning up the Enginuity website (Which is an absolute mess), and getting as much feedback from readers on content, style, aesthetics and anything else that readers wish to see.

So, let’s get started!

Here’s what will be covered in today’s newsletter:

All the latest news and updates that have amazed me

OpenAI and Perplexity, among others, released their Deep Research tools in 2025, agentic research systems that chain together multiple reasoning steps to deliver richer, more structured insights. When it comes down to practicality there aren’t many tools that are better or simpler than this.

Instead of simple searching or responding based purely off its training data, the deep research model “thinks” over minutes to plan, search, analyse and synthesis information across sources. This tool has immense applications into market research, project scouting (E.g. Searching all existing FEL3/4 project within Australia for the mining sector).

For more insight onto deep research and its applicability check this out → OpenAI Deep Research in 4 mins

Workout

For every newsletter this section will aim to introduce a potential application of AI into engineering fields. I will aim to spread these applications across sectors and across disciplines. Applications will cover on site uses to in office automation strategies. Some may already be happening, some may be in development and some may just be ideas off the top of my head. Who knows!

For those who know me this one will be a familiar project considering it is what I am completing my thesis on

Human Centric LLMs for Operational Readiness

One exciting application of AI in engineering consultancy is using LLM-powered systems to supercharge Operational Readiness (OR) planning. Traditionally, crafting deliverable lists for OR projects involves combing through piles of past project data, frameworks, standards, and engineering documents—a slow, manual, and often inconsistent process. By combining Retrieval-Augmented Generation (RAG) with human expertise, consultancies could quickly generate these lists for clients that are often facing significant resource or time pressures.

The real takeaway from an application like this is the human-AI symbiosis. Instead of replacing engineers, the system would engage specialists through targeted questions and to integrate their domain expertise directly into the model’s outputs on top of the existing data. This keeps humans in the loop for critical decision-making while letting AI handle the heavy data lifting.

The potential result? Faster delivery, more consistent outputs, and improved quality—without losing the nuance and judgement that only experienced engineers can bring.

This human-AI focus potentially represents the future of consultancies, particularly in domains where scenarios are so variable, and where the data is not sufficient for automation.

For more insight into human-AI concepts check out this video (Link)

This newsletter seeks to engage and challenge the way engineers see AI and its potential for application in Industry. Any thoughts, questions or arguments are welcome!