U.S. businesses lose an estimated $1.2 trillion every year due to poor communication, with ineffective workplace interactions costing companies an average of $12,506 per employee annually (Grammarly & Harris Poll, 2022).
Despite massive investments in soft skills training, teams forget 90% of what they learn without proper reinforcement (GP Strategies, 2024). Meanwhile, 46% of employees regularly receive confusing or unclear requests, spending around 40 minutes daily trying to decode directions (HR Magazine, 2024).
But the core issue isn’t that power skills are ineffective.
They work — communication, collaboration, adaptability, and emotional intelligence consistently predict performance.
The real issue is how organizations try to develop them.
Most training treats power skills as universal:
“Be clear.”
“Adapt to change.”
“Collaborate effectively.”
“Practice empathy.”
But in the real world, these skills only work when applied contextually — with the right approach, for the right person, in the right moment, based on team dynamics and stress levels.
Power Skills Don’t Break Down — Context Does
Power skills succeed when employees understand:
- who they’re communicating with,
- how each person receives information,
- what the relationship dynamic is,
- and when a situation requires a specific behavioral adjustment.
Traditional training cannot provide this level of moment-to-moment, relationship-aware guidance. It delivers content, not context. It teaches concepts, not situational application. It provides insights, but not timing.
This is the missing layer in power-skills development:
Contextual intelligence — the ability to read situations, relationships, and dynamics in real time.
And it’s the layer Cloverleaf’s AI coaching is specifically designed to unlock.
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What Makes Power Skills “Powerful” in the First Place?
Power skills are often described as the evolution of traditional soft skills — the human capabilities that enable good judgment, flexibility, creativity, and effective communication. They help people navigate complexity, work with others, and solve problems more effectively (isEazy, 2023).
But defining power skills as a list of competencies misses their core value.
Power skills are not static abilities. They are contextual abilities — the capacity to apply communication, collaboration, adaptability, and emotional intelligence differently depending on the person, team dynamic, and situation.
In other words: Power skills only create performance when applied contextually.
How Do Power Skills Show Up in Real-World Work Moments?
Real power skills are not abstract behaviors. They are situational responses rooted in relational intelligence:
- Contextual Communication — adjusting your message based on someone’s personality, stress level, and preferred style.
- Adaptive Collaboration — working across different motivations, working styles, and pressures.
- Situational Adaptability — shifting your approach based on the energy, tone, or dynamics in the room.
- Applied Emotional Intelligence — reading emotional cues in real time and responding appropriately.
These aren’t “nice-to-have” abilities. They’re direct performance drivers.
Do Power Skills Really Improve Performance? Here’s What the Research Says
The data is overwhelming:
- Emotional intelligence remains one of the 10 most in-demand skills globally through at least 2025 (Niagara Institute, 2024).
- 57% of people managers say their highest performers have strong emotional intelligence.
- 64% of business leaders say effective communication has increased their team’s productivity (Pumble, 2025).
- Employees who feel included in communication are nearly 5x more likely to report higher productivity.
Yet the gap between what organizations need and what their people can actually apply remains massive:
- Only 22% of 155,000 leaders demonstrate strong emotional intelligence (Niagara Institute, 2024).
- EQ is most critical during change, personal issues, and feedback conversations — precisely the moments where situational, relational insight matters most.
Soft-skills training clearly helps — a rigorous MIT study found that soft-skills development significantly improves productivity with substantial ROI (MIT, 2024).
But here’s the critical insight Cloverleaf brings:
According to Cloverleaf platform engagement data, 67% of all learning moments reported by users are about teammates—not individual development.
This means power skills are not individual competencies at all.
They are relational competencies — skills that depend on the people, personalities, and interactions involved.
This further confirms Cloverleaf’s foundational POV:
- Growth happens in relationships.
- Power skills are contextual — not universal.
- Contextual intelligence determines whether these skills translate into performance.
See Cloverleaf’s AI Coaching in Action
Power Skill Trainings Must Be Situational, In The Moment
Most training strategies often treats power skills as if they can be taught the same way every time, to every person, in every context. But power skills don’t work this way. They are situational behaviors shaped by the people involved, the team dynamics, and the environment. When organizations teach power skills as universal, they unintentionally remove the very ingredient that makes them effective: context.
This is why traditional learning formats—workshops, webinars, bootcamps, and compliance modules—struggle to produce lasting behavior change. They deliver content, not context, and cognitive science confirms that’s not enough.
What Does the Science Say About Why One and Done Workshops Struggle To Build Powerskills
Ebbinghaus’s classical research and modern replications show that without reinforcement, people lose most of what they learn—often within hours. Newer studies confirm steep early forgetting regardless of initial mastery (LinkedIn, 2024). Even emotionally engaging sessions fade quickly without ongoing application.
But forgetting is only the surface problem.
The deeper issue is that traditional training assumes power skills are static knowledge rather than situational abilities. Workshops can teach principles, but they cannot replicate the real interpersonal dynamics where these skills matter.
This aligns with research showing that standalone training events fail to create behavior change, largely because they are not reinforced through real work (Diversity Resources, 2024). Learners may understand a concept in the classroom, but they struggle to transfer it into workplace situations that demand nuance, adjustment, and interpersonal sensitivity (ResearchGate, 2024).
How Do You Actually Apply Power Skills to Different People and Situations?
Power skills aren’t abstract behaviors—they’re relational and situational.
For example:
- Communication isn’t “be clear.” It’s recognizing that a High-D colleague needs bottom-line details while a High-S colleague needs reassurance and shared context.
- Collaboration isn’t “work together.” It’s knowing that Enneagram 8s and 9s handle conflict, pressure, and decision-making in fundamentally different ways.
- Adaptability isn’t “go with the flow.” It’s reading team stress levels and adjusting your style to stabilize the environment.
- Emotional Intelligence isn’t “be empathetic.” It’s understanding when a colleague’s reaction is tied to personality triggers—not intent.
These distinctions cannot be taught as universal truths.
They only make sense in relationship to other people, at the moment they are needed.
What Does Teamwork Research Reveal About the Role of Context?
Decades of organizational psychology research shows that effective teamwork isn’t the result of a single skill—it’s the outcome of interdependent, relational processes.
Teams function well when members can coordinate, communicate, manage conflict, coach one another, and build shared understanding. These capabilities are not static traits but contextual behaviors that shift based on team dynamics, personalities, and the work environment (Oxford Research Encyclopedia, 2024).
In simple terms: The skills aren’t the problem. The absence of context is.
Traditional training can define cooperation or communication, but it cannot replicate:
- Real personalities
- Real stress
- Real disagreement
- Real interpersonal dynamics
- Real timing
…and that’s where power skills actually live.
Training explains the “what.”
Teams need support in the “how, with whom, and when.”
Which is why universal training consistently breaks down in real-world interactions.
Why Are Power Skills Really About Relational Intelligence?
Power skills don’t operate in isolation. They are relational intelligence—the ability to read a situation, understand the people involved, and adapt behavior accordingly.
Why Real-World Team Dynamics Require Contextual Intelligence
Different personality combinations change everything:
- A High-D and a High-S in DISC require different communication pacing, structure, and emotional reassurance.
- Enneagram 8s lead with intensity; Type 9s avoid conflict; Type 3s prioritize outcomes—identical feedback lands differently on each.
- Thinking types and Feeling types in 16 Types process feedback, decisions, and tension using entirely different cognitive filters.
These patterns aren’t theoretical—they show up daily in meetings, Slack threads, presentations, one-on-ones, and cross-functional work.
Validated assessments provide a behavioral foundation for understanding how different people communicate, make decisions, respond under stress, and collaborate productively. But memorizing personality types is not realistic.The goal is contextual intelligence—adapting your approach in the moment, based on the people right in front of you.
Context Drives Thriving, Not Content Alone
Research in applied psychology shows that team dynamics, supervisory relationships, and contextual factors strongly influence whether employees thrive—meaning whether they experience vitality, learning, and positive momentum at work (Applied Psychology, 2025).
People thrive when their environment supports:
- Clear relationships
- Healthy interactions
- Psychological safety
- Shared expectations
- Useful feedback
These are contextual conditions—not traits and not workshop outputs.
Traditional training treats power skills as individual capabilities.
But power skills are contextual capabilities—shaped by teams, relationships, and situations.
And that’s precisely why they fail without ongoing, situationally relevant support.
How Can AI Coaching Build Contextual Intelligence in Real Time?
Organizations have long known coaching works. Research shows that organizational coaching supported by AI enhances learning, wellbeing, and performance outcomes (Journal of Applied Behavioral Science, 2024). Meta-analyses confirm that coaching produces meaningful improvements in performance, goal attainment, and behavioral change (Emerald, 2024).
But coaching’s biggest limitation has always been scale. Human coaches cannot be present in every meeting, every project handoff, or every interpersonal moment where power skills are tested.
AI changes that—but only if the AI is contextual.
Most AI coaching tools provide generic guidance based on limited inputs. They offer well-intentioned tips but lack the behavioral science foundation necessary to interpret relationships, personalities, and situations.
What Science-Based AI Coaching Must Do (And What Cloverleaf Actually Does)
1. Start With Behavioral Science, Not Generic Advice
Cloverleaf’s AI Coach is built on validated behavioral assessments to understand working styles, motivations, stress responses, and collaboration tendencies.
This isn’t about labeling people. It’s about understanding the context required for skill application.
2. Read Team Dynamics, Not Just Individual Traits
Power skills only work when applied relationally. Cloverleaf’s AI Coach synthesizes:
- personality combinations across an entire team,
- preferred communication patterns,
- working style friction points,
- and upcoming moments where dynamics matter.
This enables anticipatory coaching—guidance surfaced before the moment, not after the mistake.
3. Deliver Insights in the Flow of Work
Power skills show up in real situations:
- A tense Slack thread where tone matters
- A cross-functional standup requiring different collaboration styles
- A 1:1 where a teammate’s stress level affects how feedback lands
- A decision-making meeting with mixed personality types
Ai coaching tools should integrate with Slack, Microsoft Teams, email, and calendars to deliver insights exactly when they’re needed, based on who you’re meeting with and how they prefer to work.
4. Reinforce Through Behavioral Nudges and Micro-Interventions
Research shows personalized behavioral nudging and micro-interventions outperform traditional learning for real behavior change (LinkedIn, 2024).
Cloverleaf uses this approach to build contextual awareness over time—not by teaching more content, but by reinforcing the right behavior at the right moment.
Power Skill Development Is Most Effective With True Contextual Intelligence
Power skills aren’t diminishing in relevance. They’re becoming more critical as work becomes more distributed, more interdependent, and more AI-enabled.
Leaders must realize that power skills are inherently contextual. They are not standalone abilities; they are situational judgments shaped by people, relationships, and dynamics.
But to create competitive advantage, these skills must evolve from generic training topics into real-time relational capabilities.
Organizations that do this will:
- Communicate with more precision
- Move faster with fewer friction points
- Make better decisions together
- Navigate ambiguity with resilience
- Strengthen cultures of trust and psychological safety
Contextual intelligence is no longer an HR initiative—it is a performance strategy for developing power skills at scale.
Ready to build your team’s contextual intelligence?
Discover how Cloverleaf’s AI coaching strengthens communication, alignment, and performance by delivering the situational awareness power skills truly require.
Artificial intelligence has lowered the cost of producing learning content to nearly zero. But while AI has made content easy to create, it has also created a much bigger risk for organizations: the illusion of progress without actual learning or real behavior change.
This problem is accelerating. The LinkedIn Workplace Learning Report 2024 shows that 77% of L&D professionals expect AI to dramatically shape content development. Yet in a striking contrast, the McKinsey 2025 AI in the Workplace report finds that only 1% of C-suite leaders believe their AI rollouts are mature.
That gap represents billions spent on AI tools that look innovative but fail to deliver what matters: performance improvement.
The core issue? Most AI in learning is built to produce more content faster, not help people apply what they learn or behave differently in real work. And when organizations deploy generic AI tools that produce generic learning, the outcome is predictable:
- low adoption
- low trust
- low impact
- high frustration
The stakes are not theoretical. Research from the Center for Engaged Learning shows how AI hallucinations can result in “hazardous outcomes” in educational settings. Even outside corporate learning, researchers are raising the alarm. Boston University’s EVAL Collaborative found that fewer than 10% of AI learning tools—across the entire education sector—have undergone independent validation. The problem is systemic: AI is being adopted faster than it is being proven effective.
If organizations accept low-quality AI, they accept low-quality learning—and ultimately, low-quality performance.
This article outlines a clearer path: leaders must demand AI learning that is personalized, contextual, interactive, and grounded in behavioral science. And they must stop settling for AI that only scales content when what they need is AI that actually scales capability.
Get the free guide to close your leadership development gap and build the trust, collaboration, and skills your leaders need to thrive.
The Current AI Landscape: A Flood of Tools, A Drought of Impact
Why every learning vendor suddenly claims “AI-powered”
AI’s accessibility has led to an explosion of vendors offering automated learning solutions. The problem isn’t that these tools exist—it’s that leaders often struggle to distinguish between AI that looks impressive and AI that drives measurable change.
Most AI learning tools fall into five common categories:
1. Content Generators
They rapidly produce courses, scripts, or microlearning modules. Useful for speed—but often shallow.
- Generic “starter” content
- Often requires human rewriting
- Lacks learner- or team-specific context
No surprise: companies report up to 60% of AI-generated learning content still requires substantial revision.
2. Recommendation Engines
These tools suggest courses based on role, skill tags, or past activity. On the surface, this feels personalized. In reality, it rarely is.
Research on personalized and adaptive learning shows that effective personalization requires cognitive, behavioral, and contextual adaptation—not merely matching people to generic content.
3. Auto-Curation Systems
They pull content from libraries or the open web. This increases volume—not relevance. Without quality controls, curation leads to:
- bloated libraries
- inconsistent quality
- decision fatigue
4. AI Quiz Builders & Assessments
These generate questions or quick checks for understanding. The issue? They often fail to align with real work demands. The ETS Responsible AI Framework underscores how most AI assessments fall short of required validity standards.
5. Chat Tutors / On-Demand Assistants
These tools answer learner questions or summarize concepts. But as Faculty Focus research highlights, AI hallucinations and generic responses still undermine trust.
See Cloverleaf’s AI Coaching in Action
Why Most AI Learning Fails: Content ≠ Capability
A pivotal finding from the World Journal of Advanced Research and Reviews makes this clear:
Most AI in learning optimizes for content production—not behavior change.
The result is a widening “quality divide”:
Content-Focused AI
- Speeds up creation
- Produces learning assets
- Measures completions
- Encourages passive consumption
- Results: low retention, low adoption, low impact
Research shows learners retain only 20% of information from passive formats.
Behavior-Focused AI
- Helps people apply new skills
- Connects learning to real work
- Reinforces habits over time
- Measures behavioral outcomes
- Results: improved performance, stronger relationships, better teams
The difference is dramatic. PNAS research demonstrates that AI can directly shape behavior—but only when it engages with people meaningfully.
The Three Non-Negotiables of Effective AI Learning
Leaders who want more than check-the-box training must insist on AI that meets three criteria:
1. Personalization: Grounded in Behavioral Science, Not Job Titles
Most “personalized” AI learning is anything but. True personalization requires understanding how individual people think, communicate, and make decisions.
Validated behavioral assessment like DISC, Enneagram, or 16 Types—reveal cognitive patterns and work-style tendencies generic AI cannot infer.
A study in ScienceDirect (2025) shows AI personalization yields significant performance gains (effect size 0.924) when it adjusts for cognitive abilities and prior knowledge.
Effective personalization must:
- reflect real behavioral data
- explain why a recommendation matters
- adapt as a person grows
- support team-specific dynamics
Ineffective personalization:
- “Because you’re a manager…”
- “Because you viewed 3 videos on feedback…”
- Same content for everyone in a job family
When AI understands behavior—not just role—personalization becomes transformative.
2. Context: The Missing Ingredient in Almost All AI Learning
The number one reason learning doesn’t transfer?
It happens out of context.
The Learning Guild notes that learning fails when it’s separated from the moments where it’s applied. A 2025 systematic review reinforces that workplace e-learning rarely succeeds without contextual alignment.
Contextual AI considers:
- the meeting you’re heading into
- the personalities in the room
- your team’s communication patterns
- current priorities and tensions
- the timing of performance cycles
This is what makes learning usable—not theoretical.
Context examples:
- Before a 1:1: “This teammate values structure; clarify expectations early.”
- Ahead of a presentation: “Your audience prefers details; lead with data, not story.”
- During team conflict: “Your communication style may feel intense to high-S colleagues; slow your pace.”
This is what mediocre AI learning and development tools and coaches cannot do. It doesn’t know or understand the context.
3. Interactivity: What Actually Drives Behavior Change
A mountain of research—including active learning analysis and Transfr efficacy studies—shows that learning only sticks when people interact with it.
Passive AI = quick forgetting
Interactive AI = habit building
Reactive chatbots succeed only 15–25% of the time.
Proactive coaching systems succeed 75%+ of the time.
Because interaction drives:
- reflection
- intention
- timing
- reinforcement
And those four elements drive behavior change.
The Costly Sacrifice of Mediocre AI
Organizations assume mediocre AI is “good enough.” It isn’t. It’s expensive.
1. The Mediocrity Tax
- wasted licenses
- low adoption
- inconsistent quality
- rework and rewriting
- user skepticism
- stalled digital transformation
HBR’s Stop Tinkering with AI warns that small, tentative AI deployments “never reach the step that adds economic value.”
2. The Trust Erosion Problem
Once people encounter hallucinations or generic advice, they stop engaging. Research from ResearchGate shows trust recovery takes up to two years.
3. The Competitive Gap
Organizations using high-quality AI learning systems report:
- 30–50% faster skill acquisition
- 20–40% better team collaboration
- higher retention
Mediocre AI leads nowhere. Quality AI compounds results.
What Quality AI Learning Looks Like (And Why Cloverleaf Meets the Standard)
Most AI learning tools cannot meet the three standards above for a simple reason: they lack foundational data about how people behave and work together.
Cloverleaf takes a fundamentally different approach.
1. Assessment-Backed Personalization (the science foundation)
Cloverleaf’s AI Coach is built on validated assessments giving it behavioral insight generic AI cannot mimic.
This enables:
- tailored guidance for each personality
- team-specific coaching
- insights that explain why an approach works
- adaptive updates as behavior changes
2. Contextual Intelligence Across the Workday
Cloverleaf connects with:
- calendar systems
- HRIS data
- communication platforms (Slack, Teams, email)
- team structures
It delivers coaching:
- at the moment of real work
- for the specific people involved
- based on real team dynamics
- in normal workflows
3. Proactive, Not Reactive Engagement
Cloverleaf does not wait for users to ask questions.
Rather it can:
- anticipate coaching needs
- deliver micro-insights before meetings
- reinforce strengths over time
- adapt based on user response patterns
This is what drives sustained adoption (75%+) and measurable results:
- 86% improvement in team effectiveness
- 33% improvement in teamwork
- 31% better communication
The problem with mediocre AI is that it produces content—endlessly, cheaply, and often generically. Cloverleaf does something different: it builds capability by coaching people in the moments where their behavior, decisions, and relationships actually change.
How Leaders Can Evaluate Their AI Learning Investments
A simple, fast audit using the “Quality Standards Matrix” can reveal whether your current AI tools will create capability—or waste.
1. Personalization
Does the AI understand behavior, not just role?
2. Context
Does it integrate with real work and real teams?
3. Interactivity
Does it drive reflection, timing, reinforcement?
4. Proactivity
Does it anticipate needs instead of waiting for prompts?
5. Measurement
If the system can’t show measurable improvement in how people communicate, collaborate, and make decisions, then it’s not building capability. It’s simply generating content.
The Choice Ahead: Mediocrity or Meaningful Change
AI is shaping the next decade of workplace learning, but whether it accelerates performance or amplifies mediocrity depends entirely on the standards leaders demand.
Mediocre AI makes learning cheaper.
Quality AI makes teams better.
The difference is enormous.
Leaders have a rare opportunity to build implement tools that truly transform how people work, collaborate, and grow. But only if they refuse to settle for AI mediocrity and choose to invest in solutions that meet the science-backed standards of personalization, context, and interactivity.
Why Most High-Potential Programs Don’t Work
Organizations spend billions on leadership development each year, yet 70% of high-potential (HiPo) programs fail to produce effective future leaders.
The core problem isn’t budget, engagement, or training design.
It’s that Traditional HiPo identification relies on subjective judgment instead of validated behavioral evidence.
Managers nominate people who look ready, sound confident, or mirror existing leaders. AI tools built without contextualized data often replicate these same patterns. As a result:
- Capable talent is overlooked
- The wrong individuals are accelerated
- Leadership pipelines become increasingly homogeneous
- Early identification mistakes are amplified through development investments
This is why most HiPo programs fail. It is not because organizations lack high-potential talent, but because the systems used to identify that talent are fundamentally misaligned with how leadership potential actually works.
Fixing the HiPo pipeline requires shifting from subjective nomination to validated behavioral science, paired with continuous, context-aware AI coaching that develops people based on their real patterns, not perceptions, assumptions, or stereotypes.
Get the free guide to close your leadership development gap and build the trust, collaboration, and skills your leaders need to thrive.
The Costly Flaws in Traditional HiPo Identification
Even well-intentioned HiPo programs break down at the identification stage. Three systemic failures drive the problem.
1. Bias (Human and Algorithmic) Distorts Who Is Seen as “High Potential”
A landmark 2025 INFORMS Organization Science study found that men are 20%–30% more likely than women to be labeled “high potential”, even when passion and performance are identical. Women showing enthusiasm were marked as “emotional”; men exhibiting the same behavior were praised for commitment.
A University of Washington study of 3 million LLM hiring comparisons showed similar patterns:
- White male–associated names were preferred 85% of the time
- Female-associated names: 11%
- Black male–associated names: 0% preference at equivalent qualifications
A VoxDev randomized experiment found the same: identical résumés produced materially different advancement scores across gender and race.
When perception shapes selection, leadership pipelines reflect accumulated inequity, not actual potential.
2. High Performance Is Mistaken for High Potential
Gallup research shows organizations select the wrong manager 82% of the time because performance is used as a proxy for potential.
But the two measures are fundamentally different:
- Performance: effectiveness in known tasks
- Potential: ability to learn, adapt, influence, and lead in new situations
Traditional tools (like the 9-box grid) blend these factors and produce wildly inconsistent outcomes. A 365Talents analysis shows how this leads to misalignment: top individual contributors may struggle in people leadership, while steady performers may possess exceptional adaptability or change leadership capacity.
3. Lack of Transparency Erodes Trust
Research on ResearchGate documents how traditional HiPo selection triggers:
- Perceptions of unfairness
- Reduced engagement
- Misalignment between values and opportunity
- “Organizational malfunctions” such as low trust and uneven development access
Employees conclude that advancement is political, opaque, or based on personality rather than capability.
This isn’t a talent problem: it’s a system design problem.
See Cloverleaf’s AI Coaching in Action
Why Behavioral Science Is a More Accurate and Equitable Foundation
Replacing intuition with evidence begins with validated behavioral assessments. Unlike performance reviews, behavioral assessments reveal how people operate in the situations where leadership emerges: ambiguity, tension, influence, communication, and change.
Research on workplace personality assessments shows scientifically grounded tools like DISC, Enneagram, 16 Types, and CliftonStrengths® reveal:
- Decision-making tendencies
- Stress and resilience patterns
- Communication style
- Motivational drivers
- Collaboration and influence approach
These patterns are stable, consistent across contexts, and strongly correlated with leadership effectiveness.
Cloverleaf’s Advantage in Consolidating Behavioral Data
Most organizations suffer assessment sprawl: multiple tools across multiple systems. Cloverleaf unifies behavioral insight from:
- DISC
- Enneagram
- 16 Types
- CliftonStrengths®
- VIA
- Insights Discovery
- Strengthscope®
- Culture Pulse
- Energy Rhythm
into one integrated platform.
Organizations report 32% savings and gain, for the first time, a unified understanding of how individuals show up across teams and relationships. This creates an evidence-based foundation for equitable identification.
What Science-Backed Assessments Can Reveal About Leadership Potential
Validated behavioral data surfaces the capabilities traditional reviews can’t reliably see.
1. Decision-Making Under Ambiguity
Whether someone:
- moves quickly with limited data
- seeks broad input
- adapts fluidly
- requires stability before acting
These tendencies determine leadership fit across different environments.
2. Navigating Conflict
Assessments reveal whether an individual:
- avoids
- addresses directly
- seeks collaboration
- influences indirectly
Conflict approach predicts how leaders guide teams through tension.
3. Communication Adaptability
Leaders must adapt communication across audiences. Behavioral tools reveal:
- clarity preferences
- pacing and intensity
- directness
- facilitation tendencies
- contextual flexibility
4. Change Leadership and Resilience
Data shows whether someone:
- embraces change
- seeks stability
- supports others through transitions
- maintains composure
5. Influence Without Authority
Crucial in matrixed environments: revealing trust-building, persuasion, and collaboration patterns.
Together, these insights form the clearest, most equitable predictor of leadership potential available today.
How AI Coaching Helps Develop High-Potential Talent More Effectively
Identifying potential is only step one. Developing it requires continuous, contextual, and personalized support: something traditional quarterly workshops and programs simply cannot deliver.
Leadership can struggle to develop HiPo talent because they:
- Occur outside the flow of work
- Don’t match individual behavioral patterns
- Rely on managers for reinforcement
- Lose impact quickly without repetition
McKinsey’s 2025 Learning Trends confirms that traditional learning rarely transfers to the real world.
As a result, the people labeled as “high potential” often receive learning experiences that are not matched to their learning style, not timed to their moments of need, and not reinforced consistently enough to drive behavior change.
Where AI Coaching Can Support Leadership Development Programs
Leadership capability develops through repetition, reflection, and application of learning.
AI coaching tools can provide:
- Daily micro-coaching inside tools like Slack, Teams, calendars, and email
- Insights grounded in behavioral assessments
- Guidance aligned based on team relationships and work schedules
- Nudges tied to upcoming meetings and decisions
- Feedback loops for reflection and behavior change
A 2025 Arist meta-analysis shows microlearning improves real-world behavior by up to 50%, because it is:
- contextual
- bite-sized
- repeatable
- immediately applicable
The Five Strategies HR Should Use to Identify and Develop High-Potential Talent
Strategy 1: Use Validated Behavioral Assessments to Establish an Objective Foundation
HR must shift identification from perceived potential to behavioral evidence.
This means implementing validated tools that measure:
- communication tendencies
- collaboration patterns
- conflict responses
- decision-making approaches
- motivational drivers
- resilience and change style
This creates a standardized, research-backed understanding of how individuals lead across situations. This is the most reliable predictor of future leadership effectiveness.
Strategy 2: Integrate Multiple Assessments Into a Unified Behavioral Profile
A single assessment is not enough to understand leadership potential.
Teams achieve more accurate identification when they:
- combine complementary assessments
- analyze cross-assessment patterns
- centralize all results in one platform
- contextualize behavioral tendencies across relationships and teams
This eliminates the fragmentation and guesswork that undermine most HiPo processes.
Strategy 3: Incorporate Team Dynamics, Relationship Data, and Work Context
Leadership does not happen in isolation. It emerges within teams, collaboration patterns, and stakeholder relationships.
HR leaders are increasingly layering contextual data into HiPo evaluation, including:
- peer collaboration patterns
- cross-functional communication
- feedback trends
- manager-direct report dynamics
- meeting behaviors
- stress and workload signals
This contextual layer allows organizations to identify HiPo talent based on performance in real environments, not in abstract reviews.
Strategy 4: Develop HiPos Through Continuous, In-the-Flow-of-Work Coaching
Use daily, contextual coaching (AI-powered) to reinforce behaviors, increase adaptability, and ensure leaders experiment with new approaches in real situations.
Evidence shows that:
- microlearning increases behavior change
- daily coaching outperforms workshops
- in-context guidance supports retention and application
- AI-augmented coaching scales development equitably
These practices help ensure that HiPo development is a daily practice embedded in how people work.
Strategy 5: Build a Connected Talent System Linking Assessment, Development, and Succession
Leadership pipelines strengthen when all talent signals, including behavioral data, performance patterns, coaching interactions, and manager feedback, flow into one integrated system.
The most effective HR teams think in systems, not programs.
They integrate:
- behavioral insight
- team dynamics
- performance signals
- coaching interactions
- manager feedback
- development goals
- succession planning inputs
When these components connect, HR gains a continuously updated understanding of who is ready for future leadership. It also shows what support they need next.
The Future of High-Potential Development Is Evidence-Based and Continuous
Organizations face a clear choice in how they approach high-potential identification and development. Those that continue relying on biased, point-in-time assessment methods will fall behind competitors using evidence-based, continuous development approaches.
The evidence-based alternative offers measurable advantages: objective, science-backed identification that reduces bias; continuous development that drives actual behavior change; diverse, capable leadership pipelines; and demonstrable ROI on talent investment.
Those that adopt behavioral science + integrated assessments + AI coaching will build leadership pipelines that are:
- more accurate
- more equitable
- more scalable
- more predictive
- more effective
The research is clear. The technology is proven.
Ready to transform your high-potential identification and development approach? Discover how Cloverleaf’s evidence-based platform can eliminate bias, drive behavior change, and create measurable leadership development results for your organization.
When a single comment in a team meeting erodes the trust you’ve spent months building, generic leadership advice isn’t enough. Here’s how behavioral assessment-powered AI coaching provides the personalized strategies leaders need to rebuild trust—one personality type at a time.
Why are so many leaders struggling to rebuild trust on their teams?
Sarah thought she was being direct and efficient when she cut off her team member mid-presentation with, “Let’s just get to the point—this is taking too long.” What she didn’t realize was that her high-S (Steadiness) team member, who values harmony and process, experienced this as a personal attack on their competence and worth.
Within days, Sarah noticed the change. Her team member stopped contributing in meetings, avoided eye contact, and began responding to her messages with terse, formal replies. The trust that had taken months to build crumbled in a single moment.
Sarah’s experience reflects a broader crisis in leadership trust. According to PwC’s 2024 Trust Survey, while 86% of executives believe employees highly trust them, only 60% of employees actually do. This 26-point trust gap isn’t just a perception problem—it’s costing organizations productivity, innovation, and talent retention.
But here’s what most leaders don’t realize: the path to rebuilding trust isn’t one-size-fits-all. The same apology that resonates with a high-D (Dominance) personality might feel hollow to a high-C (Conscientiousness) team member. The transparency that builds trust with an Enneagram Type 8 might overwhelm a Type 9.
This is where the intersection of AI coaching and behavioral assessments creates unprecedented opportunities for leaders to rebuild trust with precision, not guesswork.
Why personality differences influence the way trust is rebuilt
Most leadership advice treats trust rebuilding like a universal formula: apologize sincerely, be transparent, follow through on commitments, and give it time.
While these elements matter, they overlook an important reality of human behavior: people experience and rebuild trust in different ways, shaped in part by their personality and communication style.
Research in organizational psychology and behavioral science shows that personality traits and communication preferences strongly influence how individuals perceive and repair trust after a breakdown.
People don’t just respond to broken trust with logic — they respond through emotion, values, and preferred ways of communicating. A behavior that feels like accountability to one person might feel like criticism to another.
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Consider these personality dynamics and how they can impact trust:
Imagine a leader’s dilemma who is a high-D on DISC:
“I made a quick decision without consulting my team, and now they don’t trust my judgment. I’ve explained my reasoning multiple times, but they’re still resistant.”
For this leader, the issue isn’t lack of explanation—it’s mismatch. Their direct, results-focused style clashes with teammates who value collaboration and reflection. A high-S (Steadiness) personality, for instance, needs reassurance that their input will be considered next time, not another logic-driven justification.
The Enneagram helps articulate personality complexity and differences too:
A Type 1 (Perfectionist) who makes a mistake rebuilds trust through clear structure and prevention plans. A Type 7 (Enthusiast) interprets that same structure as criticism and instead needs optimism and relational reassurance. The same “I’m sorry” lands in two completely different ways.
Behavioral economics helps explain this. When trust breaks, the brain’s threat system activates; people become hyper-alert to signs of future harm. The stimuli that trigger this alertness—and the signals that calm it—depend on individual traits.
Leaders need situational empathy—an understanding of how each person’s behavioral style shapes what trust repair actually looks like to them.
This is precisely where AI coaching grounded in validated assessments becomes powerful. By combining behavioral data from tools such as DISC, Enneagram, and 16 Types with real-time context, AI coaches can translate psychological theory into practical, everyday language and coaching: what to say, how to say it, and when it will resonate most.
How can AI use personality data to help leaders rebuild trust
Rebuilding trust after a leadership misstep takes more than a good apology—it requires understanding how each person experiences that rupture.
Cloverleaf Coach brings that understanding to life by combining **validated behavioral assessments** (DISC, Enneagram, 16 Types, CliftonStrengths®, and others) with AI coaching to provide personalized trust rebuilding strategies.
Here’s how it works: the AI interprets a leader’s team personality data, identifies potential blind spots in communication or decision-making, and provides real-time guidance on how to repair and strengthen trust.
Instead of offering generic advice, Cloverleaf transforms personality insights into specific, situation-aware actions that help leaders rebuild relationships with precision and empathy.
See Cloverleaf’s AI Coaching in Action
AI coaches can interpret personality insight to recommend useful next steps for rebuilding trust
Cloverleaf Coach transforms behavioral assessment data into actionable trust recovery strategies through several key capabilities:
1. Searchable, Situational Guidance
Cloverleaf allows leaders to type in specific scenarios: “How do I rebuild trust with Avery after giving them inaccurate project requirements?” The AI provides coaching tailored to both the situation and the personality involved.
2. Real-Time Micro-Moment Coaching
Trust isn’t rebuilt in one grand gesture—it’s restored through consistent, everyday interactions. Cloverleaf’s AI delivers **bite-sized nudges** through Slack, Teams, and email based on each person’s behavioral tendencies and timing within the workday.
👉 Morning nudge: “Jordan values consistency. Consider starting today’s 1:1 by acknowledging their reliable contributions before discussing new changes.”
👉 Pre-meeting prompt: “Remember: Riley processes decisions through security concerns. Frame your proposal in terms of risk mitigation, not just opportunities.”
3. Team Dynamics Intelligence
Cloverleaf is team intelligent because it understands how different personality combinations interact. It can predict potential friction points and suggest preventive strategies:
💡 “Your high-D communication style may feel overwhelming to Kai. Consider slowing your pace and asking for their input before moving to solutions.”
💡 “The tension between your Type 8 and Type 9 team members likely stems from different conflict styles. Here’s how to facilitate their next interaction…”
How AI coaching can turn trust building into a cultural practice
Most trust breakdowns don’t happen because leaders don’t care — they happen because leaders don’t recognize how their behavior lands differently with each person. Knowing that is one thing; remembering to adjust in the moment is another.
That’s where AI coaching becomes useful. It doesn’t “fix” trust or prescribe scripts. Instead, it helps leaders stay aware of how their actions affect others, and it reinforces those adjustments over time — so repairing trust becomes something people practice, not just talk about.
Rather than following or attempting to remember a rigid framework, AI coaching helps reinforce habits of of building or repairing trust:
1. Understanding What Broke Trust
When relationships feel strained, it can be hard for a leader to see the situation clearly. AI coaching helps by combining behavioral data with everyday context — who’s involved, what the interaction looked like, and what personality factors might be shaping the reaction.
It might highlight that a direct message came across as dismissive to someone who prefers more collaborative discussion, or that a lack of follow-up made a detail-oriented team member question reliability.
This isn’t about blame. It’s about perspective — helping the leader see the situation through the other person’s lens so their repair efforts start from understanding, not assumption.
2. Finding the Right Next Step
Once leaders understand what went wrong, the next challenge is knowing how to re-engage. Cloverleaf’s AI uses personality and communication data to suggest phrasing, timing, or approaches that fit both the relationship and the moment.
That might sound like:
“Before tomorrow’s meeting, take a minute to acknowledge how this change may have felt sudden to Jordan. Reinforcing stability first will help them hear what’s next.”
The goal isn’t to automate empathy — it’s to make it easier to express. By surfacing reminders and suggestions in tools like Slack or Teams, leaders can show up with intention instead of reacting on autopilot.
3. Rebuilding Trust Through Small, Consistent Signals
Trust repair doesn’t happen all at once; it happens through steady, reliable behavior. Cloverleaf’s AI nudges help leaders stay consistent — to follow up, recognize effort, and check in when it matters most. Over time, these micro-interactions start to reshape how people experience the relationship.
It might mean remembering to circle back after feedback, or taking a moment to name progress in a project recap. These are small actions, but they signal care and accountability — the foundation of trust.
4. Recognizing When Trust Has Started to Recover
One of the hardest parts of leadership is knowing whether your efforts are making a difference. Because Cloverleaf tracks behavioral patterns and feedback moments, it can surface early signs of recovery: participation returning in meetings, warmer tone in responses, or greater collaboration across the team.
These subtle changes often go unnoticed, but when leaders see them reflected back, it reinforces that consistency pays off. That reinforcement makes trust repair not just possible, but sustainable.
In essence: AI coaching doesn’t replace emotional intelligence; it helps leaders *apply* it more consistently. It keeps the science of behavior change close to the moments that matter — the quiet, everyday interactions where trust is either rebuilt or lost.
The Future of Developing Trust-Aware Leadership
The integration of AI coaching with behavioral assessments represents just the beginning of trust-aware leadership. Emerging capabilities include:
Predictive Trust Analytics
Cloverleaf’s AI is developing the ability to predict trust issues before they occur by analyzing communication patterns, personality combinations, and team dynamics. Leaders receive early warnings: “Your upcoming decision may create trust concerns for your high-S team members. Here’s how to frame it…”
Cultural Trust Intelligence
As organizations become more global and diverse, Cloverleaf is expanding beyond personality assessments to include cultural intelligence, helping leaders navigate trust building across different cultural contexts while maintaining personality awareness.
Organizational Trust Mapping
Future capabilities will provide organizational-level trust mapping, showing trust networks, identifying trust influencers, and suggesting systemic interventions to build high-trust cultures at scale.
Rebuilding Trust Always Starts With Understanding
The most sophisticated AI coaching in the world can’t replace authentic human connection, but it can help leaders ensure that their efforts to rebuild trust land in ways that resonate with each team member’s unique personality.
Sarah, the leader from our opening story, discovered this firsthand. When she used Cloverleaf Coach to better understand her high-S teammate, the suggestion was simple but powerful:
“I realize my comment made you feel like I don’t value your thorough approach. Your attention to detail is exactly what this project needs, and I want to make sure you feel supported in bringing that strength forward.”
That one shift — from explanation to empathy — changed the tone immediately. Within days, their collaboration returned to normal.
Trust doesn’t have to be rebuilt through trial and error. When you understand how different personalities experience trust breaches and recovery, you can rebuild relationships with precision, authenticity, and lasting impact.
Even the smartest AI can’t repair trust for you — but it can help you understand where to begin.
Ready to accelerate how you build trust with your team? Cloverleaf Coach combines validated behavioral assessments with AI-powered coaching to provide the personalized strategies you need. Because trust isn’t one-size-fits-all—and neither should your approach to rebuilding it.
86% of users say their teams become more effective with Cloverleaf Coach. Discover how behavioral assessment-powered AI coaching can help you rebuild trust and strengthen your leadership impact.
When we first began imagining an AI coach more than a decade ago, we were told it was impossible. When we launched our first commercial product in 2018, “AI coach” was a frightening phrase in the market. We softened it to “Automated Coaching.”
We led the market with academic research. We showed that technology does not replace human coaching—it amplifies it, extending support into places human coaches cannot go. And we proved it works. Coaching from technology was not only effective, but trusted. Even beloved.
Still, the market was skeptical. And honestly, the technology could only deliver a fraction of our vision.
Today, everything has changed.
Three Disruptions Reshaping the Future of Work
We stand at the intersection of three seismic shifts:
1. Consolidation of the HR tech stack.
Organizations demand tools that work together seamlessly, not another silo.
2. The accelerating half-life of skills.
Technical skills expire in months. Human skills—collaboration, leadership, creativity—are now the enduring differentiator.
3. AI. Need we say more?
These disruptions are not threats. They are opportunities. And the question is not whether HR will evolve, but how boldly. Today, like never before, Talent and Learning leaders can finally equip every individual with the help they need, the moment they need it.
It is time to take a strategic seat at the table. Let us lead our people into their best futures.
What’s Possible in Talent Development with AI Today
We are thrilled to announce a new suite of Cloverleaf products, built to meet this moment.
At the center is Cloverleaf Connect, the most progressive and comprehensive integration of learning and talent management ever imagined.
Why should managers navigate difficult conversations without a coach that understands their team’s engagement scores and each employee’s skills, performance, goals, and behavioral profile?
Organizations have so much data about their people scattered in disparate systems. It’s time this data not just be about the people, but united and put to use for the people.
Gone are the days when “personalization” meant role-generalized content. No more one-size-fits-many.
With Cloverleaf Connect, every person receives coaching tailored to them individually, to be deeply empowered and developed continuously. And talent leaders, for the first time, can measure their impact with clarity and confidence.
This is not just what’s possible—it is what is best. HR should accept nothing less from all of their vendors today.
Cloverleaf Solutions for Every Organization: Assess, Coach & Connect
We recognize the world is changing rapidly in different directions. That’s why we’re also launching:
Cloverleaf Assess: a smarter, more affordable way to manage all behavioral assessments.
Cloverleaf Coach: the industry’s first ever AI coach grounded in personality science.
Wherever your company is—whether AI is tightly restricted or becoming fully integrated with your people data—Cloverleaf has a solution that empowers your people to grow in the uniquely human skills that all the research is showing our future demands: complex problem-solving, feedback conversations, leadership, cross-functional collaboration, creativity, innovation, etc, etc.
Why HR and Learning Leaders Must Act Now
When we began this journey ten years ago, we believed everyone should have their own coach in their corner, and that technology would make it possible. We knew the scattered data inside organizations held the key to deeply personalized growth. And we knew that people deserved more than static systems and disconnected tools.
Now, technology has caught up to vision. The disruption is here. HR has the chance to lead like never before.
This is the moment to demand more from your vendors. To settle for nothing less than solutions that empower every individual to thrive.
The world is changing fast. But for the first time, we can say: this is the future we’ve been waiting for. Let’s own this moment to make the next future the one we hope it to be: more human, more wise, more connected.
See What’s Possible with Cloverleaf: Try Our Interactive Demo
Cloverleaf’s New Brand Identity: The Future of Talent & Learning
As we launch this new suite of products, we’re also proud to introduce a refreshed Cloverleaf brand that reflects this next chapter.
Just as our products are designed to connect people and unlock growth, our new logo and visual identity sharpen that same promise: clear, approachable, and built to scale. It’s still us, just more confident, more connected, and more human.
Facing Change: Why Curiosity Beats Fear Every Time
Recently, I came across an idea from Chip Conley that captured perfectly what it feels like to navigate big life shifts. Chip described midlife as a subtle but profound transition—from focusing on your external identity (“ego”) to exploring the internal truths (“soul”) that really define you. It’s about shifting from what you’ve built on the outside to discovering what’s been quietly growing on the inside.
This resonated deeply with me because right now, many of us are facing another big shift, driven not by age, but by technology. AI is changing things rapidly, sparking curiosity for some—but fear for many others. It’s tempting to look at AI and wonder what might be lost rather than what could be gained.
But the truth is, whether it’s midlife transitions or technological revolutions, change always forces a decision: Do we retreat into what’s comfortable and known, or do we lean into curiosity and growth—even when that feels uncomfortable or risky?
For me, the answer has always been clear. And it starts by consciously choosing curiosity over fear.
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Midlife: Perfect Time to Start Over (Yes, Even if It’s Scary)” 🫣
When I was in my early 40s, I did something that felt completely counterintuitive at the time—I left a stable corporate career in Audit to start a tech company. It wasn’t just a career pivot; it was a total mindset shift.
I went from a predictable role where my experience and credentials largely shielded me from rejection, to an environment where I faced multiple rejections from investors and potential customers nearly every day. It was humbling, frustrating, and sometimes painful. But more than anything, it was an education in vulnerability.
Chip Conley talks about something called “The Striver’s Dilemma”—the irony that midlife success can become its own kind of trap.
By the time you reach your 40s or 50s, you’ve often built an identity around external markers: your job title, your expertise, your reputation. These become the uniforms you wear—comfortable, reassuring, but also limiting.
You start to believe the idea that to be successful means to avoid failure at all costs. Unfortunately though, your life gets smaller, your world less interesting, and your growth stalled.
I felt this dilemma deeply when I made the decision to become a beginner again. Stripping away the professional identities I’d accumulated over two decades wasn’t easy, but the alternative—settling into comfortable stagnation—was far scarier.
Midlife, I realized, wasn’t a time to cling tighter to what I already knew. It was the perfect moment to learn something new, even if it meant occasionally feeling foolish or uncertain. Especially if it meant those things.
Why Embracing Beginnerhood Makes AI Less Intimidating
There’s something Chip said that really stuck with me: “The key to a great second half of life is putting yourself in situations where you’re a beginner—where you’re learning again.”
When we’re young, being a beginner is just part of everyday life. Kids don’t worry about looking silly or being bad at something—they just dive in. But as adults, especially successful adults, we avoid beginnerhood because we’re afraid of embarrassment, failure, or appearing incompetent.
Yet here’s the truth I’ve discovered firsthand: actively choosing to be a beginner again is incredibly powerful. It frees you from the pressure of needing to have all the answers. Instead, you get to ask questions, experiment, and explore new ideas without needing to immediately be the best at them.
Right now, as AI rapidly reshapes our world, we have another clear choice. We can shrink back into fear, worrying about what this technology might disrupt or take away—or we can embrace beginnerhood again, leaning into the excitement of discovery.
Personally, I’m fascinated by what AI might unlock, rather than what it might replace. I’m diving into prompt engineering, learning how AI can amplify creativity, improve decision-making, and transform leadership development and team dynamics—the areas that matter most to me professionally. It’s humbling. Sometimes it’s challenging. But above all, it’s energizing and meaningful.
In other words, I’m choosing learning over fear—again.
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What the Early Days of the Internet Taught Me About AI
I remember vividly being an undergrad in the late 90s, fascinated by the rise of the internet. Everything felt exciting, uncertain, and full of possibility.
There were browser wars between Netscape and Microsoft Explorer, debates about how the internet would be searchable (Yahoo versus Google), and wildly different bets on e-commerce, from niche retailers like Pets.com to Amazon’s ambitious “one marketplace for everything.”
Back then, I desperately wanted to graduate quickly and jump into that arena because I could sense how pivotal that moment was. It felt like history was unfolding right in front of us, and I wanted to be part of shaping it.
Today, we’re standing at another inflection point—this time driven by AI—and I feel the same familiar excitement. There are plenty of unknowns and, yes, reasons to feel nervous. But I see even greater potential. AI isn’t just another tool; it’s a chance to rethink how we lead, collaborate, and build companies in deeply meaningful ways.
Instead of worrying about “holding onto sands in an hourglass,” I’m grateful to be building something at this transformative moment. I hope others see this time the same way—as a rare opportunity to shape the future, rather than simply react to it.
Take a look below at what we’re building at Cloverleaf.
How Curiosity Becomes a Competitive Advantage in Leadership
We don’t often talk about curiosity as a leadership skill. It’s usually framed as a personality trait—something you either have or you don’t. But I’ve come to see it differently. Curiosity is a discipline. It can be practiced, expanded, and even reawakened—especially if it’s been buried under years of expertise, routine, or responsibility.
Scott Shigeoka, in his book Seek, makes the case that curiosity isn’t just a nice-to-have. It’s essential. And research backs him up.
Studies show that curiosity correlates with better problem-solving, stronger relationships, and even longevity. Peter Drucker, one of the most respected management thinkers of all time, used to pick an entirely new subject to study every two years—something completely unrelated to his work. Why? Because he believed curiosity was fuel for his creativity and clarity.
And yet, in many work environments, curiosity is quietly squeezed out by efficiency. The question isn’t “What’s possible?”—it’s “How fast can we get through this meeting?”
But if you’re a leader trying to navigate change—whether it’s brought on by technology, shifting markets, or generational transitions—you don’t just need efficiency. You need to ask better questions. You need to be open to being wrong. You need to create space to explore.
Curiosity isn’t soft. It’s not fluffy. It’s a leadership edge.
Your Best Chapter Could Still Be Ahead
The older I get, the more I believe this: growth doesn’t stop when you hit a certain age—it just changes form. It stops being about climbing ladders or collecting titles and starts becoming about curiosity, meaning, and contribution. But you only access that kind of growth if you’re willing to get uncomfortable again. If you’re willing to be a beginner.
That’s the invitation in front of all of us—especially right now. Whether you’re navigating midlife questions about identity, or trying to make sense of how AI will reshape your work, the instinct to hunker down and cling to what you know is real. But so is the opportunity to lean in, get curious, and build something new.
I’ve found more creativity, energy, and meaning in these past few years than I ever expected—not because I had it all figured out, but because I gave myself permission to not know, to explore, and to learn forward.
So whether it’s launching something new, diving into AI, or picking up a hobby that reminds you what it feels like to be joyfully bad at something—my hope is that you won’t choose fear.
Choose learning.
Your best chapter might still be the one you haven’t written yet.