I am fully aligned with your observations (focus on How vs Why) and recommendations (importance of teaching concepts). You speak about neglecting performance metrics, practical value, applicability, best practices.... I've frequently heard technical experts dismiss these elements as "just marketing". If it's not directly tied to code, infrastructure, or specific tools, they perceive it as fluffy, abstract content that skirts around "real" technical topics. There's often a suspicion that this kind of content is used to mask a lack of technical depth.
The truth is the value of any training or presentation depends entirely on the audience and their goals. What resonates with one group might be irrelevant—or even off-putting—to another. Each audience comes with its own definition of value and unique expectations.
Tool Expert -> Technical mastery: How the tool works, feature depth, performance specs, and troubleshooting
Enterprise Architect -> System coherence: Architectural integrity, scalability, interoperability, and minimizing technical debt
CIO Business alignment: How technology investments support business strategy, reduce risk, and drive efficiency
Chief Digital Officer (CDO) -> Digital transformation: Leveraging technology to enhance customer experience, business model innovation, and cultural change
Business Process Owner -> Operational impact: Improving process efficiency, business KPIs, and readiness for organizational change
Board/Executives -> Strategic outcomes: Long-term value creation, competitive differentiation, innovation, and risk management
When it comes to the topic of "what's next after the training", "closing the loop", .. your observations are valid for all trainings I feel: it is recurring problem with learning and development.
To learn more about my views on that, and how AI can help solve it, check out my last article:
Concepts might be simpler to talk about but it can sometimes be pretty hard to integrate to businesses. Some businesses have certain concepts ingrained within their processes (Maybe due to past projects) and injecting a new concept would involve convincing various parties in the company to take it up.
Maybe it'll be easier if higher ups attended such trainings - but even so, the higher ups might sometimes need to take time out to explain the concept to people under their charge - and to make them understand why such concepts make sense...
Maybe ml/ai concepts are a bit more universal and well agreed upon... but Imo, computer science concepts might be sth can be debated about...
I am fully aligned with your observations (focus on How vs Why) and recommendations (importance of teaching concepts). You speak about neglecting performance metrics, practical value, applicability, best practices.... I've frequently heard technical experts dismiss these elements as "just marketing". If it's not directly tied to code, infrastructure, or specific tools, they perceive it as fluffy, abstract content that skirts around "real" technical topics. There's often a suspicion that this kind of content is used to mask a lack of technical depth.
The truth is the value of any training or presentation depends entirely on the audience and their goals. What resonates with one group might be irrelevant—or even off-putting—to another. Each audience comes with its own definition of value and unique expectations.
Tool Expert -> Technical mastery: How the tool works, feature depth, performance specs, and troubleshooting
Project Manager -> Project delivery: Cost, timeline, resource allocation, and minimizing project risks
Enterprise Architect -> System coherence: Architectural integrity, scalability, interoperability, and minimizing technical debt
CIO Business alignment: How technology investments support business strategy, reduce risk, and drive efficiency
Chief Digital Officer (CDO) -> Digital transformation: Leveraging technology to enhance customer experience, business model innovation, and cultural change
Business Process Owner -> Operational impact: Improving process efficiency, business KPIs, and readiness for organizational change
Board/Executives -> Strategic outcomes: Long-term value creation, competitive differentiation, innovation, and risk management
When it comes to the topic of "what's next after the training", "closing the loop", .. your observations are valid for all trainings I feel: it is recurring problem with learning and development.
To learn more about my views on that, and how AI can help solve it, check out my last article:
https://www.linkedin.com/feed/update/urn:li:ugcPost:7282008401847402496/
Concepts might be simpler to talk about but it can sometimes be pretty hard to integrate to businesses. Some businesses have certain concepts ingrained within their processes (Maybe due to past projects) and injecting a new concept would involve convincing various parties in the company to take it up.
Maybe it'll be easier if higher ups attended such trainings - but even so, the higher ups might sometimes need to take time out to explain the concept to people under their charge - and to make them understand why such concepts make sense...
Maybe ml/ai concepts are a bit more universal and well agreed upon... but Imo, computer science concepts might be sth can be debated about...
Koocept