Deep Work Sessions Structure

I used to believe more hours = more productivity. I was wrong. I used to be a slave to my to-do list, constantly looking for “more hours”. But, as Sahil Bloom shows us so wonderfully in this excerpt from his new book, 'The 5 Types of Wealth'... You don’t need more hours. You need better balance. Because not all time is created equal. Here's an overview of the four types of professional time (courtesy of Sahil)  and how you can use this wisdom to better structure your days: 🔴 Management Time – Meetings, emails, coordination. 🟢 Creation Time – Deep work, building, producing. 🔵 Consumption Time – Learning, reading, listening. 🟡 Ideation Time – Thinking, brainstorming, strategizing. When you mismanage these, your days feel chaotic. When you balance them, your work (and life) flow. I’ve snapped a photo from Sahil’s book so you can visually see how these four categories can bring better balance to your week. The main point is to start being more intentional about how you use your time, and group similar activities together. Here's how I've applied some of these lessons in my own life  (and how you can too): ✅ Stop checking your email in the morning I used to start my day in my inbox. But you can't plan your days around other people’s priorities. Spend the first 90 minutes each day in deep work before even glancing at your email. ✅ Create “meeting-free” days Back-to-back meetings kill focus. Implement at least one no-meeting day each week, reserving that time instead for your biggest needle-movers. ✅ Batch small tasks together Multitasking is a massive productivity killer. Instead of endlessly switching between small tasks, I now stack my admin work into a defined 30-minute block. Less task switching + more focus = greater output. ✅ Schedule time to think Yes, there is such a thing as “time to think”! Set aside at least 30 minutes of screen-free time each day. Your best ideas often come when you're by yourself. ✅ “Audit” your time every week I used to pack my weeks blindly. Now, I review where I'm spending my time and adjust the split, depending on my priorities. If you see yourself spending too much time in one category, you may need to rebalance. Look at your week. What dominates your schedule? Are you making real progress or are you just keeping busy? And if you need a blueprint for mastering your time - as well as the social, mental, physical, and financial aspects of your life - then Sahil’s new book 'The 5 Types of Wealth' is an absolute must-read. Order it here and take charge of your life: https://lnkd.in/dnPpts2e ⏳ Remember, time is your most precious asset. Once spent, you can never earn it back. So take control and make it count.

As a product leader, have you ever felt like you're constantly working two jobs? Meetings by day, real work by night. You're not alone As product leaders, we're constantly juggling two distinct roles: the strategic thinker 🧠 and the team manager 👥. Finding the right balance between deep work and rapid context switching can be a daunting challenge, especially in today's hybrid work environment. In my latest article, I discuss the concept of the Maker's Schedule vs. Manager's Schedule, why product managers and leaders need to do both, and provide a four-step approach to designing a time management strategy that enables you to excel: 1️⃣ Audit and plan your time to align with priorities 2️⃣ Implement your ideal schedule by culling meetings and blocking off deep work time 3️⃣ Protect your time by saying "no," setting boundaries, and coordinating with your team 4️⃣ Create mental space for deep work using warm-up tasks, managing energy, and transition rituals Mastering the maker-manager balance is an ongoing journey that requires intentionality and experimentation. By understanding the demands of both roles and implementing these strategies, you can significantly boost your productivity and impact as a product leader. 📈💡 Want to learn more? Check out the full article and let me know your thoughts! What strategies have you found effective for managing your time as a product leader? 👇 #ProductManagement #TimeManagement #Leadership #DeepWork #ProductLeaders

Ok, raise your hand if you've ever been the "fuzzy meeting person." 🙋♀️ 🙋♀️ 🙋♀️ I’d schedule sessions with no clear agenda, no defined outcome, basically, “let's chat and figure it out.” I’d leave half-exhausted, half-confused, thinking: "Did anything just get decided? Who’s doing what? Could this have been an email?" Probably everyone else thought that too. Waste of time. It took me a while, but I realized: the problem wasn’t the team. It was me. My meetings lacked clarity + intent. So I decided to get scientific about it. I started analyzing my meeting transcriptions with CoPilot. I wanted to see: - How much time I spent talking vs listening - How often I stated an explicit decision - Where confusion or rambling crept in The results were… eye-opening. I wasn’t just scheduling fuzzy meetings, I was enabling them. Here’s the system I built to fix it: Step 1. Define the single purpose (SO IMPORTANT) Every meeting needs a north star: “By the end, what should people know, decide, or do?” Step 2. Structure the agenda around outcomes List topics → assign a single desired outcome + time limit. Step 3. Prep key points, lead with decisions Skip long-winded context. Deliver the decision first, context second. Step 4. Track your talk ratio Use AI to see if you’re dominating or clarifying. Adjust accordingly. Step 5. End with explicit next steps Who does what, by when. No assumptions. Step 6. Follow up in writing 1–2 bullets summarizing decisions + assigned owners (you can do this with AI). Send within 24 hours. I also send transcripts if necessary. The transformation? Meetings went from draining and fuzzy → purposeful, productive, and trust-building. My coworkers leave knowing exactly what to do, and I finally stopped wondering why work wasn’t getting done. People like me more (hopefully?). Also, generally reduced my meeting frequency by 20ish%. Effectiveness frees us time, who knew. Moral: meetings are time, money, and trust. If people feel like you schedule fuzzy meetings, they'll be less committed. Use those steps to focus more on your clarity and intent. How do you make meetings more effective?

Productivity isn’t what people do more of; it’s what leaders remove. I learned this the hard way. Recently I was hit with SSNHL (sensorineural hearing loss). Overnight, my “always on” operating system crashed. No amount of caffeine or late-night heroics could brute-force me back to normal. That shock rewired how I lead. It taught me that high output isn’t about squeezing, it's about designing systems where excellence is sustainable. Leaders. We need an operating rule: Design the work so your best people never have to be heroes. Here’s the weekly, 30-min leadership ritual I use to increase output without burning people out. It runs on 3 simple, metrics. 1️⃣ Capacity (Do we have the oxygen?) - What to track: Workload vs. bandwidth at the team level (story points/OKR load vs. true capacity), and the top 3 systemic constraints throttling flow (people bottlenecks, approvals, tool friction). - What to do: Remove 1 constraint every week. Not all 3, just one. Shift scope, defer work, or break the dependency. Output is a function of constraint removal, not pep talks. - Anti-pattern to kill: “We’ll make it work.” That’s a tax on tomorrow’s quality and morale. 2️⃣ Context-switches (Are we protecting deep work?) - What to track: Interruptions per person (meetings, Slack/Teams pings, unplanned asks), time in meetings vs. maker time, and number of concurrent “priorities.” - What to do: Cap work-in-progress. Ring-fence 10–15 hours of maker time per week per builder. Bundle decisions into twice-weekly “decision hours” to reduce ad-hoc interrupts. - Anti-pattern to kill: “Jump on a quick call?” Quick calls are death by a thousand cuts. 3️⃣ Recovery (Are we restoring the system?) - What to track: Actual time off taken, detachment quality (did people truly unplug?), and energy signals (morale pulse, defect rates, cycle time drift). - What to do: Institutionalize recovery. Friday “no new work” blocks, mandatory cool-down after ship, rotations off the front line, and leaders modeling real disconnection. - Anti-pattern to kill: Celebrating burnout as commitment. Burnout is not a badge, it's a backlog of unmet leadership duties. Capacity focuses leadership attention on leverage, constraint removal turns busy teams into productive teams. Context-switch control preserves cognition, fewer switches equals higher quality and speed. Recovery compounds performance, rested systems learn, adapt, and out-innovate exhausted ones. If you only do one thing this week, do this: 1️⃣ Cancel one recurring meeting that adds 0 value. 2️⃣ Eliminate 1 dependency blocking a high-impact stream. 3️⃣ Protect one 3-hour deep-work block for your top builder. I am still recovering and thankful to the Polish Healthcare System every day I can access. I can’t get back the hearing I lost. But I found a leadership rule I wish I’d learned sooner: sustainable systems beat unsustainable heroics, every time. Which of the three metrics capacity, context-switches, or recovery resonates more? 

𝑴𝒂𝒔𝒕𝒆𝒓𝒊𝒏𝒈 𝑻𝒊𝒎𝒆 𝑴𝒂𝒏𝒂𝒈𝒆𝒎𝒆𝒏𝒕: 𝑻𝒉𝒆 𝑷𝒐𝒘𝒆𝒓 𝒐𝒇 𝑻𝒊𝒎𝒆 𝑩𝒍𝒐𝒄𝒌𝒊𝒏𝒈 Time blocking is an effective technique to take control of your day and ensure that your highest-priority tasks get the attention they deserve. This method involves dividing your day into specific blocks of time, with each block dedicated to a particular task or activity. By doing so, you can optimize your productivity, reduce stress, and maintain focus throughout the day. Imagine starting your day with a clear plan. Time blocking helps you work smarter by ensuring that each part of your day is aligned with your natural rhythms and priorities. By structuring your day with intention and clarity, you can tackle your to-do list with greater efficiency, focus, and satisfaction. Remember, the goal of time blocking isn’t just to fill your schedule, but to create a balanced workflow that supports both your professional goals and personal well-being. Imagine you're an architect, not of buildings, but of time. Every morning, you wake up with a blueprint for your day, carefully crafted to make the most of your hours. This blueprint is your time-blocked schedule, and it’s your secret weapon for success. The day begins at dawn. The morning is your prime time—your mind is sharp, and your creativity is at its peak. You know this is the perfect moment to tackle the most critical task on your list: strategic planning. In early morning hours, you immerse yourself in deep thinking, laying the foundation for the day’s work. No distractions, just pure focus on what matters most. As the morning sun rises higher, your energy shifts. It’s time to interact with others, so you step into the collaborative phase of your day. The afternoon is reserved for meetings, brainstorming sessions, and teamwork. You’ve blocked out this time specifically because you know you’ll be at your best when engaging with colleagues and tackling problems together. As the day winds down, so does your energy. The late afternoon arrives, and it’s time to handle the routine tasks that don’t require as much mental heavy lifting. You dive into your inbox, respond to emails, and tie up loose ends. It’s a satisfying way to close out the day, knowing you’ve managed your time wisely. But what makes this time-blocked schedule truly effective is the boundaries you’ve set. You’ve communicated with your team, letting them know when you’re available and when you need to be left alone. This respect for your own time ensures that each block is used to its fullest potential, allowing you to move through your day with intention and purpose. By the end of the day, you’ve accomplished what you set out to do, and it’s all because you’ve structured your day with care. Time blocking isn’t just about organizing tasks; it’s about crafting a life that balances productivity and well-being, ensuring you’re not just busy, but truly effective. #TimeManagement #Efficiency #StressManagement #Productivity

You have a stack. Now what? A stack without routines is fragile. A routine without workflows doesn’t scale. And a workflow without intention becomes automation theater. In Chapter 7 of Artificial Organizations, we explore how leaders can redesign the routines that already run their week into repeatable AI workflows that improve clarity, consistency, and decision-making. This session focuses on the shift from isolated AI usage to end-to-end executive workflows. I’ll walk through: - why workflows matter more than tools - how high-performing leaders stack behaviors, not software - the executive workflow pattern: Capture → Summarize → Classify → Distribute → Track - how to redesign Weekly Business Reviews into decision engines - what makes an ExecutiveGPT actually useful - why structure, inputs, and guardrails matter more than prompting tricks - how leaders create systems that improve execution without scaling administrative overhead The discussion includes practical examples from leadership, operations, and HR teams building reusable workflows inside real operating environments, including the Progyny case study on scaling employee experience with clear intent, strong boundaries, and real usage. This chapter is about workflow design. The leaders getting the most value from AI are not chasing more tools. They are redesigning how information moves, how decisions are supported, and how execution compounds over time. Because leverage doesn’t come from executing tasks more productively. It comes from performing the work that matters consistently better.

𝗛𝗼𝘄 𝘁𝗼 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗲 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄 𝗪𝗶𝘁𝗵𝗼𝘂𝘁 𝗪𝗮𝘀𝘁𝗶𝗻𝗴 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 I often hear leaders say, "We need to optimize our workflow with digital tools." But here's what usually happens: They buy a fancy new tool. Spend weeks setting it up. Train the team. And then... Nothing changes. Why? Because they didn't solve the real problem. Here's how to actually optimize your workflow: 1. Map out your current process What steps do you take? Where are the bottlenecks? What takes the most time? 2. Identify the root causes Is it a people problem? A process problem? Or a technology problem? 3. Set clear goals What does "optimized" look like? How will you measure success? 4. Choose the right tool Look for one that solves your specific problems Not just the one with the coolest features 5. Implement in phases Start small Get quick wins Build momentum 6. Measure and adjust Track your progress Be ready to change course if needed I've seen teams cut their workflow time in half using this approach. Without spending a fortune on new tech. The key? Focus on the problem, not the solution. What's holding your team back from peak efficiency?

Too many learning designers obsess over learning goals. But learning goals alone don’t drive results. A goal without a plan is a wish. A plan without habits is a dead end. If you’re not designing for execution, you’re designing for failure. What you need is a GPS. 📍 Goal = Your Destination (Where are we going?) 🗺 Plan = Your Route (How do we get there?) 🔁 Systems = Your Driving Habits (What keeps us moving forward?) Without all three, learning gets off track. Here’s how to make them work together: STEP 1: Set a Clear Goal 📍 A goal defines success. It answers: What should the learner achieve at the end? What doesn't work: ❌ "Improve digital literacy" (What does that even mean?) ❌ "Complete compliance training" (Nobody cares) ❌ "Learn leadership skills" (Too vague to be useful) Instead, give your learners real destinations: ✅ "Build and launch a working website for your side project by next month" ✅ "Prevent a data breach by identifying the top 3 security risks in your daily work" ✅ "Lead your first team meeting using our new decision-making framework" 👉 WHAT TO DO: Write your learning goal using this formula: "By the end of this course, learners will be able to [specific skill or outcome]." STEP 2: Create a Realistic Plan 🗺 A learning plan without milestones is like a road trip without rest stops – it leads to burnout and abandonment. Your plan should include: - A structured learning path (What concepts come first? What builds on them?) - Delivery methods (Instructor-led, self-paced, hands-on?) Milestones & check-ins (How do you track progress?) 💡 Example Plan for a Web Development Course: Week 1: HTML Basics (text, images, links) Week 2: CSS Fundamentals (styling, layouts) Week 3: Hands-on Project (Build a personal site) Week 4: Peer review & iteration 👉 WHAT TO DO: Start with the final assessment or project, then reverse-engineer your learning plan. Plan for failure. Build recovery routes and alternative paths. Your learners will thank you. STEP 3: Build Supporting Systems 🔁 Here's where the rubber meets road. Systems aren't sexy, but they separate success from wishful thinking. 💡 Example Habits for Learners: Reflect after each lesson (Journaling habit) Apply skills in small, real-world tasks (Practice habit) Engage in discussion forums (Community habit) 👉 WHAT TO DO: Pick 2–3 small habits to reinforce learning effectiveness. STEP 4: Track & Adjust 📐 A great plan still needs real-time tracking to adjust the course. - Completion Rates – Are learners dropping off? Where? - Knowledge Checks – Are they grasping key concepts? - Engagement Metrics – Are they interacting with content/peers? - Post-Course Outcomes – Are they applying what they learned? 💡 Example: If learners struggle in Week 2, add a quick video explainer or hands-on exercise before moving forward. 👉 WHAT TO DO: Use a simple feedback loop: Observe → Adjust → Test → Repeat. So before launching your next course, ask yourself: "Is my GPS in place?"

Modern data systems are not just built with tools - they’re built with design patterns that ensure reliability, scalability, and clarity as pipelines grow more complex. Here’s the breakdown of the core Data Engineering Design Patterns every engineer should understand. Each pattern solves a specific challenge across ingestion, storage, transformation, orchestration, quality, and scalability. Here’s a concise overview of the patterns: 1. Ingestion Design Patterns Data enters systems in different ways depending on freshness and volume needs. Batch ingestion handles scheduled loads, streaming ingestion captures real-time events, and CDC captures only row-level changes - ensuring efficient, timely, and fault-tolerant data collection. 2. Storage Design Patterns Choosing the right storage model shapes everything downstream. Data lakes keep raw, flexible data; data warehouses offer structured, analytics-ready storage; and lakehouses bridge both worlds by combining schema flexibility with high-performance querying. 3. Transformation Design Patterns ETL and ELT define when and where transformations happen. ETL transforms data before loading for strict governance, while ELT loads raw data first for faster, scalable cloud-based processing. Incremental processing focuses only on changed data to improve efficiency. 4. Orchestration & Workflow Patterns Pipelines require coordination. DAG-based workflows define execution order clearly, while event-driven patterns trigger pipelines based on system activity rather than schedules - improving responsiveness and decoupling systems. 5. Reliability & Fault-Tolerance Patterns Failure is inevitable, so pipelines must be resilient. Idempotent pipelines ensure repeated runs produce the same results, retry and dead-letter patterns detect or recover from failures, and backfill patterns safely reprocess historical data when needed. 6. Data Quality & Governance Patterns Trustworthy pipelines depend on clean, governed data. Validation enforces correctness, schema evolution handles safe structural changes, and lineage tracks how data flows - enabling debugging, compliance, and confident analytics. 7. Serving & Consumption Patterns How data is exposed matters as much as how it's processed. Semantic layers provide consistent business definitions, while API-based serving enables secure, controlled access for apps and downstream systems. 8. Performance & Scalability Patterns Systems grow, and patterns keep them fast. Partitioning improves query performance by slicing data, while caching accelerates repeated lookups and reduces compute cost. 9. Cost Optimization Patterns Efficient systems balance performance with spend. Tiered storage moves cold data to cheaper layers, and on-demand compute scales resources only when needed - reducing waste and controlling cost. These patterns form the foundation of modern data platforms - helping engineers design pipelines that are scalable, reliable, and easy to evolve.

Most AI tool lists miss the point. The advantage doesn’t come from knowing more tools. It comes from knowing where they fit in your workflow. Right now most people use AI like this: → Try a tool → Generate something → Move on No structure. No repeatability. So the productivity gains stay small. The real leverage appears when you treat AI tools like a stack, not a collection of apps. Almost every modern AI workflow fits into four layers. If you understand these layers, you can build systems that run every week without starting from scratch. 1️⃣ Thinking layer Tools that help you clarify problems and structure ideas. → ChatGPT → Claude Use them to: → research unfamiliar topics → break down complex problems → outline strategies and plans → stress-test ideas before execution Most people jump straight to creation. The real value often starts one step earlier: better thinking. 2️⃣ Creation layer Tools that turn ideas into assets. → writing tools (Jasper, Writesonic) → design tools (Canva AI, Flair) → image tools (Midjourney, DALL-E, Stable Diffusion) → video tools (Runway, HeyGen, Synthesia) This layer turns raw ideas into: → presentations → visuals → videos → marketing assets → documentation Think of it as production infrastructure for knowledge work. 3️⃣ Automation layer Tools that connect steps together. → Zapier → Make → Bardeen Instead of repeating tasks manually, these tools: → move information between systems → trigger actions automatically → remove repetitive work Example: Research → draft → create visuals → publish. Automation turns that into a repeatable pipeline. 4️⃣ Deployment layer Tools that deliver work to customers and teams. → websites (Framer, Durable) → chatbots (Chatbase, SiteGPT) → marketing tools (AdCreative, Simplified) This is where work becomes: → websites → marketing campaigns → customer experiences → digital products Without deployment, great AI output never reaches the real world. If you run a business or lead a team, here’s a simple playbook. Step 1 Pick one tool per layer. You don’t need ten tools doing the same job. Step 2 Design one repeatable workflow. Example: → research with ChatGPT → draft content → create visuals in Canva → automate publishing with Zapier Step 3 Automate the steps that repeat every week. Anything you do more than three times should become a system. Step 4 Improve the workflow over time. Small improvements compound faster than constantly switching tools. The people getting the most value from AI right now are not the ones testing every new tool. They are the ones building simple systems that run every day. Tools will change. Workflows compound. 💾 Save this if you’re building your AI stack. ♻️ Repost to help others move from experimenting with AI to actually using it in their work. ➕ Follow Gabriel Millien for practical insights on AI execution and building real leverage with AI. Image credit: Aditya Goenka