The Lost art of conversation

Recently I came across this videocast about the “Lost art of conversation”. The anchor and the guest discuss how the society rapidly changing with people becoming more absorbed in-themselves. I highly recommend to watch the video.

If you are time-poor, here are some nuggets I gathered

Why We Lost the Art

The speakers identify several cultural and technological shifts that have eroded our ability to connect:

• Technology and Physical Isolation: Technology has shifted us from communal experiences (like watching TV together in a neighborhood) to individual ones on personal devices. This reduces the need for physical connection and shared reflection.

• The Culture of Efficiency: We live in a society that prioritizes being "busy" and productive. Activities like sitting still or having a "water cooler" conversation are often viewed as unproductive or a waste of time.

• The Impact of COVID-19: The pandemic encouraged people to isolate and become highly self-reliant and individualistic, making the return to coexisting in workplaces difficult.

• Motive-Driven Interactions: Many people only initiate contact when they have a specific agenda or motive, such as a business deal or a safety check, which makes genuine, motive-less connection feel suspicious or "not real" to others.

What is Needed to Reclaim It

To restore the art of conversation, the speakers suggest several shifts in mindset:

• Suspending the Agenda: This involves approaching a conversation with an open mind and letting go of what you want to "get" from the interaction. It means listening to understand the other person's world rather than just waiting for a moment to drop in your own needs.

• Stillness and Presence: Connection requires being in the "here and now". The brain needs stillness—not constant productivity—to process information, connect with others, and spark creative "aha" moments.

• Shifting from "Vivad" to "Samvad": The talk contrasts Vivad (argument where one truth wins) with Samvad (a conversation where two truths meet to create a bigger truth and widen perspectives).

• Acknowledging the Other: Reclaiming connection starts with simple acknowledgments, like a greeting, to ensure others feel seen, heard, and understood.

The Impact of This Loss

The erosion of conversation and connection has significant consequences:

• Pervasive Indifference: People have become so indifferent that they may look right through others in common areas or feel "stunned" when a stranger offers a kind word.

• Mental Health and Stress: A society obsessed with efficiency over-schedules everyone, including children, leading to mental health struggles and a lost ability to simply "be".

• Stifled Innovation: Because the workplace rewards "busyness" and lacks stillness, employees struggle to find the mental space necessary for creativity and innovation.

• Fractured Community: Without deep connection, we lose our sense of social resilience and solidarity, which research suggests is a primary human need.
  

Evolution of Jidoka in Manufacturing

Each newsletter will carry a part of the book that Harish Jose and I co-authored. Today’s topic is to introduce the evolution of Jidoka.

“The roots of Jidoka can be traced back to two key approaches introduced by Sakichi Toyoda. The first was to separate the operator’s work from the machine’s work, enabling one operator to manage multiple machines rather than being tied to a single one. Traditionally, operators watched a machine as it worked, creating no value during that time. Sakichi’s vision freed operators from this limitation. The second approach was to design machines that could detect anomalies and stop on their own, preventing the production of defective goods and forcing immediate problem-solving. Both ideas were fully implemented in the Toyoda Automatic Loom Works, where a single operator could manage as many as 25 automatic looms at once.

After World War II, Kiichiro Toyoda set an ambitious goal: Toyota must catch up with American productivity within three years. To achieve this, Ohno adopted Sakichi’s principle of one operator managing multiple machines, which significantly increased productivity. However, this introduced new challenges. Machines that completed their cycle did not stop; they kept producing parts unnecessarily. If a machine malfunctioned, it continued making defective parts. Productivity improved, but process flow and quality suffered.

To address these issues, Ohno redesigned machine layouts and introduced limit switches so that machines would stop automatically when the required quantity was produced. For quality concerns, he relied on the second principle of Jidoka: machines should stop when an abnormality occurs. This prevented defective parts from moving downstream. Over time, this concept extended beyond machines to people. Operators were not only allowed but expected to stop the line when they identified a problem. The andon cord system provided a visual and audible alert for assistance. If the issue could not be resolved within a set time, the entire line would stop until it was fixed.”

We cover more interesting stories and the history behind the birth of TPS. You can purchase the book using the links below

eBook purchase link: https://leanpub.com/connecting-the-dots
Physical copy (paper back): Link
Hard bound copy : Link

Other topics covered in this book ?

• Just-in-Time: Creating flow, reducing waste, and building responsiveness into the system.

• Jidoka: Stopping to fix problems and embedding quality into the process.

• Respect for People: Moving beyond slogans to understand what this principle demands in practice.

• Continuous Improvement (Kaizen): Why improvement must be ongoing and how it shapes learning.

• Genchi Genbutsu: Going to the source and seeing reality for yourself.

• Thinking about the Thinking Production System: A deeper reflection on TPS as a way of framing problems.

• Cultural Foundations: How Japanese history and philosophy influenced TPS principles. Leadership and Ethics: Learning from Toyota without becoming Toyota, and addressing the challenges of AI and efficiency-driven thinking.

Can AI replace the need for adopting LeSS principles ?

I was questioning myself a few weeks ago about how AI could impact adoption of LeSS principles in organisation. We have principles like Systems Thinking, Lean Thinking, Queuing Theory, etc. Are they still relevant in the AI era ? How do they impact these principles.

Here are my thoughts…

Here’s a concise analysis of how AI (especially generative AI and agentic systems) impacts each of the 10 Large-Scale Scrum (LeSS) principles you shared. Each bullet reflects a tension or synergy between AI and the principle.

1. Large-Scale Scrum is Scrum
   
   AI doesn’t change the core need for empirical process control (inspect & adapt). However, AI can generate fake “certainty” (e.g., perfect-looking plans, tests, code) that undermines transparency. Teams must remain skeptical of AI outputs and still inspect real working software.

2. Queueing Theory
   
   AI accelerates individual tasks (coding, analysis, testing), which can reduce queue lengths. But queues still form at coordination points (e.g., merging AI-generated code, reviewing LLM outputs). Worse, faster input can hide bottlenecks elsewhere. Queueing discipline becomes even more critical.

3. Empirical Process Control
   
   AI can augment inspection (e.g., anomaly detection in logs, test results) but cannot replace the human act of adaptation based on shared understanding. If teams blindly follow AI recommendations, they revert to pseudo-predictive control the opposite of empiricism.

4. Systems Thinking
   
   AI cannot replace systems thinking. LLMs lack awareness of organizational dynamics, power structures, tacit knowledge, and feedback delays. Heavy AI use often optimises local sub-systems (e.g., individual productivity) while damaging the whole (e.g., coordination debt, fragmented ownership). Systems thinking becomes more necessary, not less.

5. Continuous Improvement Towards Perfection
   
   AI can surface improvement opportunities (e.g., cycle time patterns, test flakiness). Danger: teams may delegate improvement ideas to AI and stop reflecting themselves. Perfection remains human-driven; AI is a tool for detecting waste, not defining value.

6. More with Less
   
   AI can reduce certain waste (handoffs, documentation, boilerplate code). But “more with less” in LeSS means simplification of structure, roles, and coordination. AI often adds complexity (new tools, agents, prompts, governance). The principle acts as a guardrail against AI bloat.

7. Whole Product Focus
   
   AI excels at narrow tasks but struggles with holistic customer value. If each team uses AI to optimise its slice, the whole product can degrade (e.g., inconsistent UX, conflicting business rules). Whole product focus requires cross-team alignment that AI cannot own.

8. Customer Centric
   
   AI can personalise, summarise feedback, or simulate customers. However, customer centricity in LeSS means direct user contact and shared responsibility. AI intermediaries (chatbots, automated analysis) risk diluting empathy and creating proxy-driven development. Use AI to amplify voice of customer, not replace it.

9. Lean Thinking
   
   AI can identify waste (e.g., duplicate work, long feedback loops) but can also introduce new waste: prompt engineering, AI output validation, model latency, and energy costs. Lean thinking demands ruthless elimination of waste including AI-generated waste.

10. Continuous Improvement Without Queues
    
    Ironically, AI can create hidden queues (e.g., waiting for GPU time, model API rate limits, human review of AI output). Even if development tasks are fast, decision queues (e.g., which AI suggestion to accept) may form. The principle still holds: reduce batch size and limit work-in-process, with or without AI.

Bottom line: AI does not invalidate LeSS principles. It exposes them. Systems thinking, queues, and empiricism become more critical when AI is introduced—not less.

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