The Human Touch: Why Industry experts elevate the Learning experience far beyond AI

In an age where artificial intelligence (AI) and automation are becoming increasingly prevalent in our daily lives, the value of human-led training courses cannot be overstated. While AI-driven training from Large Language Models (LLMs) offers scalability and consistency, it lacks the nuanced understanding and depth of experience that industry experts bring to the table. Here’s why training delivered by seasoned professionals is often superior to AI-based learning.

Depth of Knowledge Industry experts possess a deep knowledge of their subject matter, honed through years of hands-on experience. They’ve navigated the complexities of their field, encountered a myriad of scenarios, and learned from both successes and failures. This depth cannot be replicated by AI, which, despite its vast data, cannot contextualize information with the wisdom gained from real-world experience.

Adaptability and Personalisation Experts can adapt their teaching methods to the unique needs of their audience, providing personalised feedback and guidance. They can read the room, adjust their pace, and delve deeper into topics of interest or relevance. AI, on the other hand, follows a predetermined path and lacks the ability to tailor its approach to individual learning styles.

Networking and Mentorship Learning from industry experts opens doors to networking opportunities and mentorship. Attendees can form valuable connections that may lead to future collaborations or career advancements. AI-based training offers no such networking potential, as it lacks the human element that fosters relationship building.

Real-World Problem-Solving Experts can draw upon their extensive experience to present real-world problems and case studies, offering practical solutions that they’ve applied in their careers. This hands-on problem-solving approach is more engaging and informative for attendees, providing them with tools and strategies they can apply in their own work.

Enhanced Learning Outcomes and Active Engagement Studies in educational settings demonstrate that expert-led courses significantly boost learners’ self-efficacy and lead to superior educational outcomes. When instructors with deep industry knowledge guide the learning process, they not only impart knowledge but also instill confidence in their students. This personal investment catalyses a more profound engagement with the material, fostering an environment where active participation is encouraged. Such dynamic interaction, facilitated by the instructor’s expertise, is crucial for deep learning and retention, which AI-driven methods can not fully replicate.

Continual Learning Industry experts are often at the forefront of their field, continuously updating their knowledge to stay current with the latest trends and technologies. They can impart this cutting-edge information to attendees, ensuring that the training remains relevant and up-to-date. AI, while it can be updated, typically operates on a set database of information that may quickly become outdated.

Emotional Intelligence Finally, industry experts bring emotional intelligence to their training sessions. They can empathize with learners, offer encouragement, and provide motivation—qualities that AI simply cannot emulate. The human connection fosters a more engaging and supportive learning environment.

In closing, I do believe that AI-based training has its place, particularly for base-foundational knowledge, however the irreplaceable insights and personal touch offered by industry experts makes their training courses an essential resource for learners seeking a comprehensive and enriching educational experience.

Where am I...

So right now I'm working out how to pull my different posts and blogs together into one place. Mostly I write on LinkedIn these days, but maybe I should bring this back to life again, rather than move it : )

Still here, still Agile.

Transformation troubles and non-technical debt

Technical debt if not managed can end up becoming a critical factor dramatically slowing down future development and in some instances has lead to whole-scale system re-writes just to keep products maintainable. The flip side is that by taking that "loan" occasionally, often a quick win can be leveraged to enable a new product to be born, a market opportunity to be captured or a deal to be won.

The sad thing is that for the last several decades most corporations have been choosing those "easy solutions" in their operational space. Individual departments have bought their own software to solve their own problems whilst not really worrying about integration with other areas. Others have home grown their own processes without considering the "customer" journey (try a value stream mapping exercise in a finance department!). And many have created products and KPIs that predominantly meet internal company goals rather than external customers and market requirements.

As this has been going on, these companies have become larger. What once was a "point fix" is now scaled up to become an integral part of the organisations processes. What once was seen as "a little bit of extra admin we can live with" is now a part of an oppressive organisational culture. What once was "for now we think we know what the market needs" is now the hand on the rudder of the organisations product roadmap. Scaling anything is an effective way in seeing where all the inefficiencies lie and where the limiting factors are - just try driving 70mph on the motorway when it is full of other traffic on a Friday night.

So our organisations processes and culture are actually just like our technical code-bases, after-all a code-base is just a written version of a load of processes and behaviours. Well-maintained code is easy to understand and easy to enhance or change; and the term "well-maintained" normally means re-paying any technical debt "loans" on a regular basis.

We all live in an imperfect world though and the point that organisations come to decide they need a "Transformation" is normally because the non-technical debt (or cultural / organisational debt if you prefer) has become such that product delivery is slowed/stuck, innovation is lacking, processes are overbearing, staff are unhappy and often shareholder value is slipping as a result.

Barry O'Reilly wrote a piece about Explore vs Exploit organisations, and the above situation could also describe the "Exploit" organisations who have got towards the end of wringing their current market dry but are not able to explore new markets due to their internal culture and constraints.

So where does this take us?

Large consultancies are often brought in to help manage large Transformations and amongst them (and elsewhere) are people who will give projected financial improvements as a result of their prescribed transformation. "You will develop product this much faster/gain this many new customers, so it's worth £X million." however the 'cost' is often not really quantified. Nik Silver wrote an interesting article on the cost vs value of paying back technical debt and I think the same broad principals can be applied with organisational debt too.

Nik neatly suggests that you can model the payback point of stopping product development to fix technical debt. This is based on the velocity of product development beforehand and the "boosted" velocity afterwards as a result of the debt being paid (vs just continuing without the fix).

It's worth noting that the break even point is well after the period of activity of "solving the problem", so if we apply a similar mindset to Transformation we should not expect a net gained benefit until some time after we are done Transforming.

Of course whilst that makes perfect sense from a benefit delivery perspective in a product development domain, in the organisational domain it could be shaped a little different as the benefit over time is probably already diminishing rather than being steady (hence the need to "fix things") so it could look like this:

Also you won't find any Transformation agents telling you that you wont get any benefit during the transformation process (or you wouldn't sign up to it would you) but recognise that the overhead of "change" is going to make productivity/output/profit dip in the first instance. You can't add extra work into a system without the system responding to the work.

So in the above diagram at the point when you exit your "Transformation" you are actually potentially net benefit worse off than if you hadn't done it at all. You've borne the cost of buying in consultants, you've lost staff, you've gained new staff, you've bought new software, you've built new processes and retired old processes, you've re-furbished the office space, and you've scared the jam out of most people along the way, but the believers are still on board.

So was it worth it?

Well that is difficult to quantify as what you have actually done is payed back the "non-technical debt" in your organisation all in one go and "boosted" your future velocity as a result. You're still in business and now better prepared to take on the future, in fairness you've potentially saved the company from a steady decline and uncertain fate. Things are certainly different, that's for sure.

But was this the only option? What you have done is a full system re-write of the organisations' "code-base". Perhaps was it better to fix the "non-technical debt" little and often just like we encourage our developers to do?