Engineering Team Management Skills

Micromanagement is the fastest way to kill motivation. It's not leadership. It's fear in disguise. Great leaders trust. Poor ones hover. Micromanagers think they're helping. But they're not. The good news? You don’t have to stay stuck in this trap. Whether you’ve been micromanaged or fallen into the habit yourself, here’s what you need to know, as we head into 2025: What Micromanagement Really Does: 🚫 Stifles Creativity ↳ Teams can’t innovate when they’re constantly second-guessed. 🔗 Breeds Dependence ↳ If every decision requires approval, teams stop thinking for themselves. ⏱️ Wastes Time ↳ Endless hovering distracts everyone—including you. 😠 Creates Resentment ↳ Nobody thrives under a helicopter boss. If you’re ready to step into 2025 as a stronger leader, I've put together 3 frameworks and tools to help: 1️⃣ The GROW Coaching Model A goal-setting and problem-solving framework that helps leaders and their teams clarify priorities and focus on outcomes. Here’s what it stands for: • Goal: Define what success looks like for your team or project. • Reality: Assess the current situation—what’s working and what’s holding the team back? • Options: Brainstorm solutions together to inspire ownership and creativity. • Will: Commit to an action plan that the team drives forward. 2️⃣ Kanban Boards A visual system for managing tasks and workflows that reduces micromanagement while maintaining clarity and transparency. How to use it: • Visualize the Workflow: Map out every task and step in the process so everyone knows what’s happening. • Limit Work in Progress (WIP): Prevent overload by capping how many tasks can be actively worked on at a time. • Quickly Spot Bottlenecks: Debug issues that lead to bottlenecking at certain parts of process. 3️⃣ Feedback Loops Support autonomy by creating intentional, structured opportunities for communication and growth. Here’s how: • Establish a Cadence: Set consistent 1-on-1s or team meetings to discuss progress, challenges, and wins. • Focus on Growth: Use these sessions to encourage problem-solving and personal development, not micromanagement. • Empower Teams: Ask open-ended questions (“What do you need to succeed?”) and trust their answers. By empowering your team, you don’t lose control—you gain it. Great leaders hire great people. Then they help them thrive. Your job? Remove obstacles, not become one. How do you empower your team? Drop your thoughts in the comments ⬇️. ♻ Repost to help your network in 2025. And follow Eric Partaker for more.

Ten years ago, many of these roles didn’t even exist. Today, they are at the core of every successful AI initiative. This visual from Gartner perfectly captures how the AI landscape is evolving: → Traditional roles like Data Scientists and Data Engineers remain critical. → Emerging roles like Prompt Engineer, Model Validator, and Knowledge Engineer are becoming increasingly important. → "Must-have" roles like AI Architects, ML Engineers, and AI Risk & Governance Specialists are now essential for scaling AI responsibly. Building AI systems today demands 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝘁𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗲𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲. It requires collaboration across multiple disciplines — business understanding, model development, model validation, activation, deployment, and ongoing monitoring. The future belongs to teams that can integrate technical innovation with operational excellence and ethical oversight. If you're planning your career or building your team — 𝘁𝗵𝗲 𝗔𝗜 𝗼𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝘆 𝗶𝘀 𝗺𝘂𝗰𝗵 𝗯𝗶𝗴𝗴𝗲𝗿 𝗮𝗻𝗱 𝗯𝗿𝗼𝗮𝗱𝗲𝗿 𝘁𝗵𝗮𝗻 𝗲𝘃𝗲𝗿 𝗯𝗲𝗳𝗼𝗿𝗲. Image credit - Garnter

The ability to create clarity when there’s no shortage of chaos, opinions, and competing priorities is a rare skill. In any reasonably competent company, this skill alone will help take you quite far, fairly quickly. Concretely, this means creating clarity on the main problems, clarity on the right solutions, and clarity on the action plan & priorities. Very few people can do this well even though most people possess the intelligence necessary to do it. This is because most people in the workplace have been conditioned to add more information, sound more clever, satisfy more stakeholders, and feign more precision & certainty than is possible. Few understand that clarity in a chaotic situation can only emerge from subtraction, never from addition. Clarity comes from communicating what stands out as most important, why it is most important, how it will be achieved, and last but not the least, giving people a way of thinking about why it is okay, even great, that we aren’t doing All The Other Things.

10 tips from my book "Leading Effective Engineering Teams" I recently announced my new book "Leading Effective Engineering Teams"! After leading engineering teams at scale and seeing what works, I wanted to share just a few of the ideas from the book that could help others. Build psychological safety - Our research in Google's "Project Aristotle" revealed this as the #1 predictor of team success. I share specific techniques to build environments where engineers feel safe to take risks and innovate. Empower without micromanaging - I've seen firsthand how trust and autonomy drive 3x better outcomes. I outline my framework for setting clear guardrails while giving teams the space to own solutions. Scale your effectiveness systematically - I present my 3 E's model (Enable, Empower, Expand) for scaling team effectiveness from the ground up, based on proven patterns from Google. Foster clear communication - Drawing from thousands of 1:1s and team meetings, I provide strategies that have consistently improved team alignment and execution. Define clear success metrics in terms of outcomes (e.g. how does the work help users and the business) vs. outputs - I share the OKR frameworks we used at Google to measurably boost team effectiveness by 23%. Prioritize career development - I share more about a GROW model I've refined over years of mentoring engineers into successful tech leaders. Structure for innovation - Learn the specific organizational patterns that enabled my teams at Google to consistently ship breakthrough features. Lead with data - I reveal the key metrics and dashboards I've found most valuable for making better decisions and driving continuous improvement. Balance technical and leadership skills - Based on my journey from engineer to leader, I provide a roadmap for developing both technical depth and leadership breadth. Proactively feed opportunities and starve the problems - I share my framework for identifying and nurturing high-impact opportunities while preventing issues before they arise. The book includes real case studies, practical templates, and concrete techniques from my experience leading teams at Google. I wrote this to help engineering leaders at all levels build more effective, impactful teams. I hope the tips and book are helpful in some way! 🔗 Available now: https://lnkd.in/gVVQSwZr #programming #softwarenengineering #leadership

Airport platform safety is crucial to prevent costly and dangerous incidents! ✈️🌟 In this high-pressure environment, a simple mistake can lead to serious consequences. From aircraft collisions to mishandled cargo, every detail matters. But there’s one thing that can make all the difference: proper training and supervision! 🛠️ Why is it so important? Ramp personnel training is essential, but it’s not enough. You also need highly skilled supervisors who can act quickly to prevent accidents. Their presence on the platform ensures procedures are followed and helps minimize distractions. 🚧 The risks on the platform include: Aircraft collisions Unsafe loading and unloading Poor communication 📚 How does supervision help? Immediate action: Supervisors can stop an error before it turns into a serious incident. Promotes discipline: Their presence keeps staff adhering to safety standards. Identifies issues in time: They spot areas that need improvement in procedures. 🌍 In summary: Combining staff training and effective supervision is the key to ensuring platform safety. Investing in training is protecting what matters most: lives, aircraft, and operations. Safety starts with each one of us! 👷♀️👷♂️ #AirportSafety #TrainingAndSupervision #AccidentPrevention #SafeRamp

The First 10 Minutes Tell You Everything When I walk into a plant for the first time, I don’t start with the KPIs. I start with the floor. Here are 5 things I look for in the first 10 minutes: 1) I-beam storage – If I see items tucked inside or leaning against building columns, that’s an operator asking for 5S help. 2) Floor condition – Clean, marked, and free of debris? Or cluttered and worn? The floor tells a story about pride and ownership. 3) Visual controls – Can I tell the status of work, machines, and flow at a glance without asking questions? 4) Operator engagement – Do people make eye contact, greet me, or explain what’s happening? Or is it heads-down, hoping I keep walking? 5) Standardized work in action – Are processes consistent from one station to another, or is everyone “doing it their way”? These aren’t about catching people doing something wrong. They’re about spotting the habits, systems, and culture that drive everything else. Because if the basics aren’t right, the metrics won’t be either. What’s the first thing you look for when you walk into a plant? #LeanManufacturing #5S #OperationalExcellence #ManufacturingLeadership #ContinuousImprovement #PlantWalks #VisualManagement

Gamma: 3 engineers per product manager. Last year "standard" was 10. AI is changing the math of teams. The Gamma stat surprised my former boss Tamar Yehoshua, now Atlassian's chief product and AI officer. It should stop anyone still designing teams the way we did two years ago, let alone ten. Contrary to consensus (and Big Tech vibes), engineering job postings are at a three-year high. This may be Jevons paradox at work: when something becomes cheaper (engineering capacity, thanks to AI) we demand more of it. We can accelerate roadmaps, greenlight projects previously too expensive, extend engineering capability to new parts of the business. Sounds simple, but it's incredibly hard to do. Hiring, performance and team structures in engineering are changing rapidly; Katya Laviolette at 1Password described their massive shifts towards communication, problem solving and judgement over tech skills. But that's just the start of massive, broader org implications. The new constraint isn't how fast engineers can build: It's how well product managers understand customers, and how fast the rest of the organization can act. Three knock-on effects most orgs haven't confronted: 🔸 Without clarity on what to build, AI-accelerated engineering produces output and features, not value. 🔸 When marketing, sales, and support can't absorb the new pace, the bottleneck moves downstream. 🔸 Smaller, faster teams create more coordination challenges, not fewer. Engineering may be the first function to show what "AI transformation" actually requires: fundamental rethinking of systems, org design, and leadership. Massive implications for leaders, especially in HR who are also wrestling with how to redesign their own teams, as Sunita Solao points out. One place to start: redesign product development teams and processes, not just headcount. Make sure the PMs and designers working with your engineers have the capacity and authority to decide what gets built, and to stop what shouldn't. 👉 My latest in Charter, based on interviews with dozens of product, engineering, and HR leaders, linked in comments. 📎 Special thanks to Katya, Sunita, Mike Brevoort, great new data from Julie Bedard, Matthew Kropp and team at BCG and, in a very weird way, Block's Jack Dorsey (you need to read it). Is your company redesigning how work gets done, or just shifting headcount and hoping something works out? #AI #Transformation #OrgDesign

Starting a new role as a Maintenance Manager often comes with an unspoken expectation to perform miracles. “Just make it work.” “Do your magic.” And so it begins — quick fixes, temporary patches, anything to keep the line running. But over time, the real questions surface: How much operational neglect has been normalized? How much reactive maintenance is hiding the absence of a structured plan? In several plants I’ve managed, I’ve encountered the same mindset: 🗨️ “If the line is running, don’t stop it.” 🗨️ “We’ll fix it when it breaks.” 🗨️ “Everything we make gets sold — downtime is just waste.” But here’s the truth: a production line that never stops for preventive maintenance will eventually stop for corrective failure. And when it does, the cost — in time, resources, and lost output — is much higher. Proper maintenance isn’t just about fixing machines. It’s about managing risk, ensuring continuity, and enabling operational excellence. That requires more than good intentions. It requires a working maintenance strategy, built on: ✅ Cross-functional collaboration between planning, production, and maintenance. ✅ Clear preventive maintenance schedules aligned with production forecasts. ✅ Data-driven decisions based on machine history and failure patterns. ✅ Shared KPIs that reflect not just output, but equipment availability and efficiency. ✅ Ownership and communication, so that maintenance is not a “service department” — it’s a partner in performance. One of the hardest conversations I’ve had was trying to justify planned downtime to a leadership team that saw any stop as a loss. I used the analogy of a car needing regular service, only to hear: 🗨️ “Fine, once a year you can stop.” 🤦♂️ But that mindset doesn’t scale. You can’t grow efficiency on top of neglected assets. True performance comes from a healthy tension between the need to produce and the need to maintain — with leadership that understands both. Maintenance doesn’t exist to slow production down. It exists to make sure production can speed up — and sustain it.

As Chief Engineer of strategic ballistic missile submarine USS Kentucky, I felt I had to have every answer. I was in every action, every system, every repair. The stakes were too high for anything less. But here’s the truth: that approach was untenable. No single person can shoulder that weight forever. What saved me—and what made our team world-class—wasn’t my control. It was: ✅ Delegation — trusting officers and sailors to own their watch. ✅ Intent-based leadership — giving clear direction, not micromanagement. ✅ Trust-based communication — speaking up early, listening deeply. ✅ Transparent expectations — clarity about what “good” looked like. ✅ Deep but meaningful checking — not hovering, but verifying. Scaling your business is no different. Early founders often try to be in every decision, every hire, every customer interaction. But just like on a submarine, that weight will break you—and stall your team. The transition from “I control everything” to “we achieve everything together” is what transforms brilliant engineers and scientists into enduring leaders. 💡 Where are you in that journey—holding every answer, or scaling through trust? #Leadership #ScalingUp #Delegation #ExecutiveCoaching #EngineeringLeadership #CoreX #Trust #IntentBasedLeadership #focalpountcoaching

Learn: 1. What PMs do that most annoys engineers 2. Why major rewrites are almost always a trap 3. How to organize and best work with platform teams 4. What most surprises IC's once they become managers 5. Why you should consider having fewer 1:1's ...and much more Camille Fournier is the author of The Manager’s Path, which many consider the definitive guide for navigating one’s career path in tech. Camille was previously the CTO of Rent The Runway, VP of Technology at Goldman Sachs, Head of Platform Engineering at Two Sigma, and Global Head of Engineering and Architecture at JPMorganChase. She is about to release new newest book, Platform Engineering: A Guide for Technical, Product, and People Leaders. Listen now 👇 - YouTube: https://lnkd.in/gChnZGNr - Spotify: https://lnkd.in/g3nU8bJU - Apple: https://lnkd.in/gPcpwm_G Some key takeaways: 1. PMs can avoid annoying engineers by: a. Ensuring that engineers receive recognition for their contributions: Publicly recognize and credit engineers for their contributions to product successes. Go beyond just thanking them; let them take the lead in presenting their work and achievements. b. Understanding and caring about technical details: Take time to learn about the technical aspects of projects. Even a basic understanding shows respect for the complexity of the work and helps facilitate better communication and decision-making. c. Avoiding playing “telephone” between engineers and stakeholders: If you find yourself acting as a middleman too frequently, consider connecting engineers directly with relevant stakeholders. This reduces the risk of miscommunication and ensures that technical concerns and insights are addressed in real time. d. Including engineers in ideation and creative processes: Actively involve engineers in brainstorming sessions and planning stages. Encourage them to share their ideas and feedback early on to foster a collaborative environment and keep them engaged in the product development process. 2. Engineers often feel tempted to propose large-scale rewrites when frustrated by outdated, complex systems. However, rewriting the internal system can be deceptively complex, requiring substantial time and resources to migrate data and potentially delaying other crucial work. Before deciding to rebuild, consider whether the issue affects everyone or just engineers. Legacy systems, despite their flaws, often have significant functionality and thoughtful design built over time and have been adapted to handle various situations. 3. If you’re considering transitioning from engineering to management, aim to gain substantial technical expertise first. Spending around 10 years or having significant hands-on experience in your technical field can help you maintain credibility and confidence in your technical skills.