Generative AI’s role in onboarding boosts efficiency and productivity. As Zavvy notes, AI-driven software speeds up onboarding, leading to quicker employee productivity and better retention and engagement. AI tools offer 24/7 access to resources, allowing new hires to consult information at their convenience, thus reducing information overload and the pressure of learning everything at once.

TechHQ highlights how AI simplifies tasks like document exchanges and account setups. Chatbots and AI tools answer new hires’ questions in real-time, easing their transition into the company. This approach leads to a smoother, more engaging onboarding experience.

At Doximity, we use Glean, an AI tool that integrates our internal data, providing instant GPT-powered answers for new engineers. This facilitates:

• Instant Knowledge Access: Engineers quickly access internal data, streamlining the learning process.
• Personalized Learning Pace: AI caters to each engineer’s learning style, allowing them to focus on unfamiliar areas at their own pace.
• Reduced Information Overload: AI delivers relevant, concise information, making onboarding less overwhelming.

Our recent revamp of the onboarding guide, prioritizing our GPT-powered knowledge base, has reduced the size of our onboarding guides by 30%. This shift aligns with the evolving tech-driven workplace, setting a new standard for integrating talent.

While AI is excellent for providing factual knowledge, it cannot replace human judgment and decision-making. This is where human mentors are crucial, guiding new hires through more nuanced, subjective aspects of onboarding. They focus on areas that align with the engineer’s strengths and the team’s needs, ensuring a seamless integration.

While not directly aimed at onboarding, platforms like Intro.co attempt to fill the gap where AI’s capabilities end. Intro.co connects individuals with human mentors, including founders, CEOs, and other leaders, for guidance that AI can’t yet provide. Some mentors on these platforms command fees as high as $5,000 per hour, catering to those seeking a competitive advantage.

This trend prompts an intriguing thought: At what point will AI’s aggregated knowledge eclipse the insights derived from a human’s lifetime of experience? As AI progresses, it increasingly challenges the boundary between computer-generated advice and human insight. This advancement hints at a future where AI might offer guidance that rivals or even surpasses human expertise in specific fields.

AI in mentorship complements rather than replaces human interaction. It takes on the factual, information-based learning, allowing human mentors to concentrate on the subjective aspects of onboarding. This combination results in a balanced, effective, and fulfilling onboarding experience for new engineers.

A 2023 large-scale survey done by GitHub revealed intriguing insights about developers using Copilot. The findings are remarkable: 60–75% of users reported increased job fulfillment and decreased frustration. They’re focusing on more satisfying work. Impressively, they noted 88% and 60% increases in productivity perception and fulfillment, respectively³.

However, GitClear’s analysis of 153 million lines of code authored between January 2020 and December 2023 tells a different story. It suggests a “Downward Pressure on Code Quality” and a notable rise in code churn rates⁴.

Nvidia’s CEO, Jensen Huang, thinks kids should no longer learn to code. He envisions replacing programming languages with human language prompts, enabling anyone to program⁵.

You probably recall over the course of the last 10 years, 15 years, almost everybody who sits on the stage like this would tell you it is vital that your children learn computer science. Everybody should learn how to program. And in fact, it’s almost exactly the opposite. It is our job to create computing technology such that nobody has to program. And that the programming language is human. Everybody in the world is now a programmer. This is the miracle. This is the miracle of artificial intelligence. The countries, the people that understand how to solve a domain problem in digital biology or in education of young people or in manufacturing or in farming, those people who understand domain expertise now can utilize technology that is readily available to you. You now have a computer that will do what you tell it to do.

Nvidia’s CEO, Jensen Huang – World Government Summit in Dubai 2023

Conversely, if you see programming as an art, Huang’s view falls short. Programming involves critical thinking akin to artistic creativity. Beyond hard skills like math, it’s about innovative problem-solving. Consider a calculator: it solves math problems, but humans need to understand the problem and interpret the tool’s output. That intersection of science and art is pivotal in programming.

Believing programming is both an art and a science, however, means it will never be obsolete. We’ve had machines that flawlessly play back sheet music for decades, but musicians aren’t obsolete. There’s artistry in creating and performing music, much like in programming. Even familiar songs draw us to concerts, highlighting the enduring value of artistry—something AI can’t replicate in the foreseeable future.

When will we get to a world where computers materialize anything we imagine? In programming, this means no typos and potentially bug-free code. Yet, the nuanced understanding, critical thinking, and human experience required to develop code that truly addresses a problem remain irreplaceable. It’s about a certain je ne sais quoi, appealing to sentient beings who feel, touch, and make decisions in the real world.

So, is programming art, science, or a blend of both? The answer lies in how we view creativity and problem-solving in the evolving world of technology.

Listen to the text above:

1. GitHub CEO says Copilot will write 80% of code “sooner than later” ↩︎
2. Github CEO thinks AI will write majority of code in just five years ↩︎
3. Quantifying GitHub Copilot’s impact ↩︎
4. 2023 Data Suggests Downward Pressure on Code Quality ↩︎
5. Children Will No Longer Need To Learn To Code ↩︎

Mental models mentioned in the book you may want to look into further:

1. The Map is Not the Territory
2. Circle of Competence
3. Second-order Thinking
4. Probabilistic Thinking
5. Correlation Over Causation
6. Regression to the Mean
7. Inversion
8. Occam’s Razon
9. Hanlon’s Razor

In life and business, the person with the fewest blind spots wins. Removing blind spots means we see, interact with, and move closer to understanding reality. We think better. And thinking better is about finding simple processes that help us work through problems from multiple dimensions and perspectives, allowing us to better choose solutions that fit what matters to us. The skill for finding the right solutions for the right problems is one form of wisdom.

A mental model is simply a representation of how something works. We cannot keep all of the details of the world in our brains, so we use models to simplify the complex into understandable and organizable chunks.

When understanding is separated from reality, we lose our powers. Understanding must constantly be tested against reality and updated accordingly.

Our failures to update from interacting with reality spring primarily from three things : not having the right perspective or vantage point, ego – induced denial, and distance from the consequences of our decisions.

The second flaw is ego. Many of us tend to have too much invested in our opinions of ourselves to see the world’s feedback — the feedback we need to update our beliefs about reality. This creates a profound ignorance that keeps us banging our head against the wall over and over again. Our inability to learn from the world because of our ego happens for many reasons, but two are worth mentioning here.

The third flaw is distance. The further we are from the results of our decisions, the easier it is to keep our current views rather than update them.

It’s much easier to go on thinking what we’ve already been thinking than go through the pain of updating our existing, false beliefs.

We also tend to undervalue the elementary ideas and overvalue the complicated ones.

An engineer will often think in terms of systems by default. A psychologist will think in terms of incentives. A business person might think in terms of opportunity cost and risk – reward. Through their disciplines, each of these people sees part of the situation, the part of the world that makes sense to them. None of them, however, see the entire situation unless they are thinking in a multidisciplinary way.

Charlie Munger summed up this approach to practical wisdom : “ Well, the first rule is that you can’t really know anything if you just remember isolated facts and try and bang ‘ em back. If the facts don’t hang together on a latticework of theory, you don’t have them in a usable form.
The Map is not the Territory

What is common to many is taken least care of, for all men have greater regard for what is their own than for what they possess in common with others. – Aristotle

Remember that all models are wrong; the practical question is how wrong do they have to be to not be useful – George Box

There are three key practices needed in order to build and maintain a circle of competence : curiosity and a desire to learn, monitoring, and feedback.

Learning comes when experience meets reflection. You can learn from your own experiences. Or you can learn from the experience of others, through books, articles, and conversations.

It is extremely difficult to maintain a circle of competence without an outside perspective. We usually have too many biases to solely rely on our own observations. It takes courage to solicit external feedback, so if defensiveness starts to manifest, focus on the result you hope to achieve.
Supporting Idea: Falsifiability

The trend is not destiny. Even if we can derive and understand certain laws of human biological nature, the trends of history itself are dependent on conditions, and conditions change.

First Principles Thinking: Applying the filter of falsifiability helps us sort through which theories are more robust. If they can’t ever be proven false because we have no way of testing them, then the best we can do is try to determine their probability of being true.

Socratic questioning generally follows this process: Clarifying your thinking and explaining the origins of your ideas.

1. Why do I think this? What exactly do I think?
2. Challenging assumptions: How do I know this is true? What if I thought the opposite?
3. Looking for evidence. How can I back this up? What are the sources?
4. Considering alternative perspectives. What might others think? How do I know I am correct?
5. Examining consequences and implications. What if I am wrong? What are the consequences if I am?
6. Questioning the original questions. Why did I think that? Was I correct?
7. What conclusions can I draw from the reasoning process?

Many people mistakenly believe that creativity is something that only some of us are born with, and either we have it or we don’t. Fortunately, there seems to be ample evidence that this isn’t true. We’re all born rather creative, but during our formative years, it can be beaten out of us by busy parents and teachers. As adults, we rely on convention and what we’re told because that’s easier than breaking things down into first principles and thinking for yourself. Thinking through first principles is a way of taking off the blinders. Most things suddenly seem more possible.

The truth is, the events that have happened in history are but one realization of the historical process — one possible outcome among a large variety of possible outcomes. They’re like a deck of cards that has been dealt out only one time. All the things that didn’t happen, but could have if some little thing went another way, are invisible to us.

Thought experiments tell you about the limits of what you know and the limits of what you should attempt. In order to improve our decision – making and increase our chances of success, we must be willing to probe all of the possibilities we can think of. Thought experiments are not daydreams. They require both rigor and work. But the more you use them, the more you understand actual cause and effect, and the more knowledge you have of what can really be accomplished.

In mathematics they call these sets. The set of conditions necessary to become successful is a part of the set that is sufficient to become successful. But the sufficient set itself is far larger than the necessary set. Without that distinction, it’s too easy for us to be misled by the wrong stories.
Second-Order Thinking

Probabilistic Thinking: Almost everyone can anticipate the immediate results of their actions. This type of first – order thinking is easy and safe but it’s also a way to ensure you get the same results that everyone else gets. Second – order thinking is thinking farther ahead and thinking holistically.

The theory of probability is the only mathematical tool available to help map the unknown and the uncontrollable. It is fortunate that this tool, while tricky, is extraordinarily powerful and convenient. Benoit Mandelbrot

Occam’s Razor: Think about not only what you could do to solve a problem, but what you could do to make it worse — and then avoid doing that, or eliminate the conditions that perpetuate it. Simpler explanations are more likely to be true than complicated ones. This is the essence of Occam’s Razor.

Why are more complicated explanations less likely to be true ? Let’s work it out mathematically. Take two competing explanations, each of which seem to equally explain a given phenomenon. If one of them requires the interaction of three variables and the other the interaction of thirty variables, all of which must have occurred to arrive at the stated conclusion, which of these is more likely to be in error ? If each variable has a 99 % chance of being correct, the first explanation is only 3 % likely to be wrong. The second, more complex explanation, is about nine times as likely to be wrong, or 26 %. The simpler explanation is more robust in the face of uncertainty.

Hanlon’s Razor: “extraordinary claims require extraordinary proof. ”

I need to listen well so that I hear what is not said. Thuli Madonsela

Hanlon’s Razor states that we should not attribute to malice that which is more easily explained by stupidity.

The explanation most likely to be right is the one that contains the least amount of intent.

Kahneman and Tversky exposed a sort of tic in our mental machinery : we’re deeply affected by vivid, available evidence, to such a degree that we’re willing to make judgments that violate simple logic. We over – conclude based on the available information. We have no trouble packaging in unrelated factors if they happen to occur in proximity to what we already believe.

Buy yourself a copy of the book.

Thanks for reading 🤗

Be prepared to say anything complex a few times, in different ways. If you feel that you don’t understand something your mentee has asked you, repeat the question in a different way. Let him correct you. Use those whiteboards scattered around your office, if necessary, to draw diagrams. Spend the time that you need to spend to feel understood, and like you understand the mentee. And remember that you’re in a position of huge power in your mentee’s eyes. He’s probably nervous about screwing this opportunity up, trying his best to please you, and trying hard not to look stupid. He may not ask questions even when he doesn’t understand things. Make your life easier and get those questions out of him. The odds of you spending all of your time answering questions are slim compared to the odds that your intern will go off in the absolute wrong direction because he didn’t ask enough questions.

When you are a mentor Tell your mentee what you expect from him. If you want him to come prepared for your meetings with questions he has sent you in advance, ask for that. Be explicit about your time commitment. And then be honest with him when he asks questions. There’s no point in being a mentor to a relative stranger if you can’t at least use that professional distance to offer him the kind of candid advice that he may not get from his manager or coworkers.

If you’re ever in the position to promote people to management, be very, very on the team. Highly technical hands-on managers can be good for small teams of careful in giving your alpha geeks team management positions, and keep a close eye on the impact they have in that role. The alpha geek culture can be very harmful to collaboration and can deeply undermine those who feel unable to fight back. Alpha geeks who believe that their value comes from knowing more than others can also hide information in order to maintain their edge, which makes everyone on the team less effective.

What you measure, you improve. As a manager you help your team succeed by creating clear, focused, measurable goals. So often, we fail to apply this basic wisdom to the process of assigning mentors, but it applies here as much as anywhere else. When you need to assign a mentor for your new hire or intern, figure out what you’re hoping to achieve by creating the relationship. Then, find the person who can help meet those goals.

Senior engineers can develop bad habits, and one of the worst is the tendency to lecture and debate with anyone who does not understand them or who disagrees with what they are saying. To work successfully with a newcomer or a more junior teammate, you must be able to listen and communicate in a way that person can understand, even if you have to try several times to get it right. Software development is a team sport in most companies, and teams have to communicate effectively to get anything done.

The tech lead is learning how to be a strong techniC project manBger, and as such, they are scaling themselves by delegpting work effec tively without micromanaging They focus on the whole team’s productivity and strive to increase the impact of the team’s work produuct They are empowered to make independent decisions for the team and are learning how to handle difficult management and leadership situations They are also learning how to partner effectively with product, analytics, and other areas of the business.,

Asa new tech lead, be carefual of relying on process to solve problems tha are a result of communication or leadership gaps on your team.

Another approach that many experienced managers use is to help their new reports create a 30/60/90-day plan.

When you feel like you want to micromanage, ask the team how they’re measuring their success and ask them to make that visible to you on an ongoing basis.

Why bother writing any code if all you’re doing is small stuff? The answer is that you need to stay enough in the code to see where the bottlenecks and process problems are. You might be able to see this by observing metrics, but it’s far easier to feel these problems when you’re actively engaged in writing code yourself.

If the build is really slow or deploying code takes too long or on-call is a nightmare, you’ll feel it in the difficulties you, an experienced engineer,

Sometimes, teams aren’t shipping because the tools and processes they’ve been using make it hard to get work done quickly. A common example is that your team only tries to release changes to production once a week or less. Infrequent releases can hide pain points such as poor tooling around releases, heavily manual testing, features that are too big, or developers who don’t kmow how to break their work down. Now that you’re managing the team, start to push for the eam, removal of hese bottlenecks.

Be careful that vocally negative people don’t stay in that mindset on your team for long. The kind of toxic drama that is created by these energy vampires is hard for even the best manager to combat. The best defense is a good offense in this case, and quick action is essential,

It might be cultivating the list of things that are important but you haven’t thought about in a while, so you know what to focus on. If you don’t set aside some time to focus on these issues, they’ll sneak up on

The purpose of this skip-level process, beyond maintaining trust and engoge Ment, is to help you detect places ìn which you’re being “managed up” well o the detriment of the team under that manager.

One of the best ways to do this is by asking the people who would report to the new manager to interview her by asking her to help with problems they have right now, or have had in the recent past. Similar to a senior engineer being asked how he might approach debugging an issue that you just resolved, a good manager-even without a full understanding of the people or projects involvedshould have good instincts for questions to ask and suggested next steps that might improve matters. You can take it a step further and actually role-play other types of difficult situations, like dealing with an employee who is underperforming, or delivering a negative performance review.

Importantly, a manager must also be able to debug teams. Ask the manager to describe a time when she ran a project that was behind schedule, and what she did in that scenario. Or ask her to role-play with an employee who is thinking about quitting. Ask the manager to describe how she’s coached employees who were struggling, and helped great employees grow to new levels.

Design and architecture questions based on the types of systems she’s built or managed are a good approach. Make sure she can discuss the tradeoffs that were made and why. You might also have her mediate a technical debate between engineers who disagree on the solution to a problem.

Managing teams is a series of complex black boxes interacting with other complex black boxes. These black boxes have inputs and outputs that can be observed,

Dedicate 20% of your team’s schedule to “sustaining engineering,” This means allowing time for refactoring, fixing outstanding bugs, improving engineering processes, doing minor cleanup, and providing ongoing support. Take this into account in every planning session. Unfortunately, 20% is not enough to do big projects, so additional planning will be needed to get major technical rewrites or other big technical improvements. But without that 20% time, there will be negative consequences with missed delivery goals and unplanned and unpleasant cleanup work.

As you can see from this tale, good technology strategy here meant several things. It meant technology architecture, yes. It also meant team structure. It meant understanding the underpinnings of the business and the directions in which it was headed. I like to describe technology strategy for product-focused companies as something that “enables the many potential futures of the business.” It’s not just a reactive document that tries to account for current problems, but it anticipates and enables future growth. If you’re in a product-focused business, this is the heart of your technology strategy. It’s not about actually deciding the product’s direction, but about enabling the larger roadmap to play our successfully.

One of the best analogies I’ve heard for startup leadership comes from a friend, On Freud, who’s been in engineering management at several different startups. On describes the earliest startup as like driving a race car. You’re close to the ground, and you feel every move you make. You have control, you can turn quickly, you feel like things are moving fast. Of course, you’re also at risk of crashing at any moment, but you only take yourself down if you do. As you grow, you graduate to a commercial flight. You’re farther from the ground, and more people’s lives depend on you, so you need to consider your movements more carefully, but you still feel in control and can turn the plane relatively quickly.

Finally, you graduate to a spaceship, where you can’t make quick moves and the course is set long in advance, but you’re capable of going very far and taking tons of people along for the ride.

Buy yourself a copy of the book.

Thanks for reading 🤗

I recently took his three-hour course on The Three Pillars of Effective Leadership and would like to share my notes with you. I highly recommend this course to anyone interested in kind and effective organizational leadership. I hope you find the following notes useful.

1. Awareness

The best leaders are most self-aware; they are aware of how the message is being received and can course correct.

1. Be a spectator to your own thoughts
   1. Recognize we are wired for certain behavior. Fight human nature: Egocentrism, triggers (past exp.), bias (particularly unconscious) [1]. When you can become a spectator to these processes, triggered by someone else’s agenda, that’s when you can be interviewed, difficult because of natural tendencies.
   2. How to: Develop a mindfulness practice.
2. Manage compassionately
   1. Compassion = Empathy + Action
   2. Compassion is not conditional; the people you don’t like need it the most. Don’t simply surround ourselves with people like us.
   3. When an interaction goes sour, be compassionate to recognize (be a spectator), be kind and truthful (establish trust).
   4. Trust = consistency over time.
   5. Value of managing compassionately. Ultimately, a company’s value is about the speed and quality of the decisions made within that company.
3. Know what you ultimately want to accomplish
   1. Optimize for Passion and Skill.
   2. Understand strengths and weaknesses.
   3. Ways to generate self-awareness: mindfulness practice, 360-reviews, mentorship – Ray Chambers [2], Fred Kofman [3].

Wisdom without compassion is ruthlessness, and compassion without wisdom is folly.

Fred Kofman

• Inspiration: What are the most important qualities of a leader? The ability to inspire others to achieve shared objectives
• Managers tell people what to do. Leaders inspire people to do it.
• Synthesis: Effective leaders can separate signal from noise, connecting dots.

Team and Company Awareness

1. Building Your Team
   1. The winning teams are comprised of people that complement one another: skills + life experiences + perspectives.
   2. The team performs better when there are people like them in the team: diversity and inclusion.
   3. Zero tolerance for people who are not willing to uphold values and cultures. Rogue/toxic people.
   4. Three qualities of teams I want to work with:
      1. Dream big
      2. Get stuff done
      3. know how to have fun (share values)
   5. Be grateful to your team.
2. Reading the Room
   1. Listen with the intent to understand, not just with the intent to reply.
   2. Speak with the intent to be understood, not just to prove your point. Model behavior to foster options, compassion.
   3. Just because you said, it doesn’t make it so.
      1. Must share goals, objectives, roadmaps, visions, best practices, socialized, cascaded the direction.
   4. Repeat, repeat, repeat. Once you get sick of yourself saying, only then will BEGIN to internalize what you are saying.
3. Meeting Dynamics
   1. Identify what problem you are trying to solve. This meeting will be a success if (no higher than 3)
   2. Balance: presentation & discussion, pressure & patience.
      1. Read the agenda/docs before or first thing in the meeting.
      2. Tension: there should be a minimum productive tension; if everyone is quiet, it is a problem.
      3. Patience vs. impatience balance.
      4. Be careful w/ unintended consequences of casual feedback. They’ll treat as mandates. The more responsibility you have, the more influence you have, the more people will weigh your words and actions. The more senior you become, the more aware you need to about how your behavior is being interpreted.
      5. Three tiers of feedback:
         1. OPO (one person’s opinion)
         2. Strong suggestion – if mistakes, OK.
         3. Mandate
4. Company Awareness
   1. Daily and weekly data: dashboards, email updates
   2. Weekly meetings: 1-on-1s, staff meetings
   3. Longer-term picture meetings: Corp Dev meetings, Corp Biz Reviews, OKRs

2. Synthesis

Separate signal from the noise, focus on what matters most, connect the dots. Create a sense of mission, and roadmap, use your awareness to course correct.

1. Vision to values
   1. Vision: dream, true north, designed to inspire.
   2. Mission: Overarching objective, measurable and realizable.
   3. Value prop: Benefit or advantage creating for customer.
   4. Target audience: Who needs prioritizing.
   5. Strategy: How to make mission become a reality (understand competition)
   6. Priorities: Ranked list of tactics designed to realize objectives
   7. Objectives: Measurable goals aligned with the realization of mission and strategy. Unintended consequences of a measurable goal.
   8. Culture: Collective personality of the corporation, who we are, and who we inspire to be.
   9. Values: First-principles to make day-to-day decisions.
2. FoCuS
   1. Fewer Things Done Better
      1. Everybody is trying to do too much.
      2. Start with the value proposition at the top, draw a bulls-eye at and concentric circles. The center is your primary opportunity.
      3. Don’t draw out resources from an inner layer to an outer layer too early. Competitors are chomping at the bit to steal that from you.
   2. Communicate: The right info to the right people, at the right time.
      1. Avoid surprises, over-communicating, bring it up quickly, don’t overdue, address prioritize.
      2. Who is in the to: and cc: is really important.
      3. Be clear when you expect to hear back,
   3. Speed
      1. Role of RAPID (recommend, agree, perform, input, decide) — understand who contributes to each category of rapid. Ask “what’s the RAPID?” for this decision.
      2. Alignment within 5 days (alignment, not necessarily decision, some decisions take a lot longer). Misalignment that goes longer for 5 days is counter-productive, time to escalate to the D.
3. Tools
   1. Flying at the right altitude, there are two times continuous.
      1. Tactical <—> Strategic: Become more strategic as the org grows.
      2. Problem-solving <—> Coaching: As you become more responsible for people, coach to scale, don’t simply solve their problems. Coach your teams to coach their teams; that’s how to scale.
   2. Time management
      1. Scheduling every minute of your day leaves you no time to think.
      2. Make time to think mindfully.
      3. The constant pressure of falling behind will undermine your ability to think, make good decisions and your morale. Establish proper buffers.
      4. Walk the walk. Someone’s schedule sets your priorities.
   3. Forums
      1. Create forums (meetings/people) to help you synthesize. Regular staff meetings, strategy reviews, team offsite, product reviews.

3. Inspiration: Effective Communication

Leadership: The ability to inspire others to achieve shared objectives.

Managers tell people what to do. Leaders inspire them to do it. Ideally, all managers can be leaders.

Jeff Weiner

If you want to inspire others, start with what inspires you. It May sound obvious, it’s not. In order to inspire you to have to believe completely in what you are trying to convey. This is why name-dropping is not effective.

1. Clarity of your vision
   1. Requires you to have a defined personal vision and reconcile that with your goals.
2. The courage of your convictions
   1. Beliefs: Belief in your vision with everything you got; you can’t just be rationalized. Lead from the place of deeply held belief.
   2. Values: If we pursue to what at the exclusion of the how, it’ll lead to potential unintended consequences. What are your leadership values?
   3. Alignment
      1. Define your personal values
      2. Define your leadership values
      3. Think about how they align with the company values
3. Effective Communication
   1. Authenticity – absolutely essential
      1. Ensure Belief, feel, do, say are in sync. That’s when you will show up as a leader.
      2. It’s human to feel that you are expected to be different from who you actually are at some level. Being true to yourself is key to effective communication.
      3. Vulnerability: Strike the right balance, too much you seem dishonest, too little, you can seem weak.
   2. Transparency
      1. The vicious cycle of obfuscation: Leadership holds info → info leaks, people lose trust → more measures to prevent leaks → repeat.
      2. The virtuous cycle of transparency: Leadership shares info → people feel like the info is theirs → they’ll protect their info → learn and build on best practices → helps solve problems → repeat.
   3. Repetition
      1. Repeat a message often. That’s when people begin to hear you.
      2. This is necessary because people see the world through their own lenses.
      3. History teaches that almost nothing a leader says is heard if spoken only once — David Gergen

History teaches that almost nothing a leader says is heard if spoken only once.

David Gergen

Inspiration: Effective Public Speaking

1. Know Your Audience
   1. Don’t start with what you want to say. Find the union of what you want to say and what your audience wants to hear. Understand your audience. Who, why?
2. Know Your Material
   1. Recognize and avoid the doom loop: Memorize → Forget a line → panic → people disconnect/discomfort → panic.
3. Know Your Passion
   1. Your Energy > Your Words. Best speakers make you feel inspired, connected, passionate.
   2. When you are passionate about what you’re talking about, it’s going to shine through.

Jeff ends with a recommendation to a superb keynote delivered by Bryan Stevenson at Ted.

Notes

1. Egocentrism: in theory, by leveraging experiences, we think we can make better decisions. Triggers: unwind neuro connections by putting yourself in a safer situation, deeply embedded.
2. Ray Chambers:
   1. Importance of being in the moment
   2. Spectator to your own thoughts
   3. It’s better to be kind than to be right.
   4. Be grateful for at least one thing daily.
   5. Help others every chance you get
3. Fred Kofman: Wisdom without compassion is ruthlessness, and compassion with wisdom is folly.

Thanks for reading 🤗