Mikayla Stewart 🇨🇦

Today we reduced headcount by 22%. The business is the strongest it's ever been. So I think it's important to be direct about what I'm seeing and why. First, I made this decision and I own it. I did it because the way to operate at the highest level of productivity is changing, and to win the future, ClickUp needs to change with it. Second, this wasn't about cutting costs. Most savings from this change will flow directly back into the people who stay. We'll be introducing million-dollar salary bands. If you create outsized impact using AI, you'll be paid outside of traditional bands. Most importantly, I have the deepest gratitude for those affected. We're doing this from a position of strength specifically so we can take care of people properly. Everyone affected receives a package aimed at honoring their contributions and easing the transition. I only see two options: wait for this to play out gradually in the market or be honest about what I'm seeing and act proactively. THE 100X ORGANIZATION The primary change is that we're restructuring around what I call 100x org. The goal is 100x output. The roles required to build at the highest level are fundamentally different than they were a year ago. Incremental improvements to existing systems won't get us there. We need new ones. That means creating enough disruption to rebuild rather than iterate on what's already broken. The common narrative is that AI makes everyone more productive. It doesn't. Many of the workflows of today, if left unchanged, create bottlenecks in AI systems. These roles will evolve. But waiting for that to happen naturally means falling behind now. The 100x org is actually heavily dependent on people - infinitely more than today. This is only possible with 10x people that have embraced and adopted new ways of working. THE BUILDERS, AGENT MANAGERS, AND FRONT-LINERS — THE BUILDERS: 10X ENGINEERS I don't think most companies have internalized what's actually happening with AI in engineering. The common narrative is that AI makes all engineers more productive. That may be true in isolation, but at an organization level - that is the farthest thing from reality. Here's what we've validated recently at ClickUp: the great engineers, the ones who can orchestrate, architect, and review, are becoming 100x engineers. They're not writing code. They're directing agents that write code. The skill is judgment. AI makes the best engineers wildly more productive, and everyone else using AI slows these engineers down. Think about it - the bottlenecks are (1) orchestration - telling AI what to do, and (2) reviewing - what AI did. Everything is leapfrogged and no longer needed. So who do you want orchestrating and reviewing code? And how do you want your best engineers to spend their time? If your best engineers are spending time reviewing other people's code, then this is inherently an inefficient bottleneck. These engineers can review their agent's code much faster than reviewing human code. The new world is about enabling your 10x engineers to become 100x. The wrong strategy is to push every engineer to use infinite tokens. Companies doing this are celebrating 500% more pull requests. But customer outcomes don't match the volume of code being generated. I call this the great reckoning of AI coding, and every company will face this soon if not already. More code is just another bottleneck to the best engineers, and ultimately to your company's impact as well. — THE BUILDERS: 10X PRODUCT MANAGERS Product management and design roles are merging. Designers that have customer focus, become more like product managers. And product managers that have intuition for UX become more like designers. The bottleneck of user research is gone. It takes us just one mention of an agent to kickoff research and analyze results. The bottleneck of product <> design iteration is also gone. The product builder iterates on their own, along with agents and skills that ensure alignment with quality and strategy. Also controversial today - I believe that the wrong strategy is to have your PMs shipping code - that just introduces another bottleneck that the best engineers will waste their time on. To be clear, PMs should be coding but they should do this in a playground to iterate, validate, and scope. That code should not go to production. Everything outside of managing systems, orchestrating AI, and reviewing output becomes a bottleneck. That's why the other roles that are critical along with these are the systems managers (to reduce bottlenecks) along with a bottleneck you can't replace - customer meeting time. — THE SYSTEM MANAGERS Ironically, the people that automate their jobs with AI will always have a job. They become owners of the AI systems - agent managers. We have many examples of these people at ClickUp. The underlying systems in which we operate are absolutely critical to get right. I think most companies are delusional to think they can iterate on existing systems and compete in this new world. You must create enough disruption so that old systems are deprecated entirely. If there's any definition for 'AI native' that's what it is. — THE FRONT-LINERS In a world that will become saturated with AI communication, the human touch will matter more than anything to customers. This is a bottleneck that you shouldn't replace - even when agents are high enough quality to do video meetings. One-on-one meeting time with customers is something that shouldn't be automated. The systems around the meetings should be - so that front-liners spend nearly 100% of their time with customers. REWARDING 100X IMPACT In a world where companies are able to do so much more with less, where does that excess money go? In our case, much of the savings in this new operating model will flow directly back to those that enabled it. We must reward people that create productivity accordingly. This aligns incentives on both sides. Plus, in a world where your best people create 100x impact, you can't afford to lose them. You should aim to retain these employees for decades. The context they have and their ability to efficiently orchestrate and review will be nearly impossible to replace. Compensation bands of today should be thrown out the door. We're introducing $1 million cash/year salary bands with a path available to nearly everyone in the company if they produce 100x impact by creating or managing AI systems. THE FUTURE Nearly every company will make changes like these. The ones that do it proactively will define what comes next. The future is not fewer people. It's different work, new roles, and better rewards for those who embrace it. We're already seeing entirely new roles emerge, like Agent Managers, that didn't exist a year ago. ClickUp is positioning to lead this shift, not just internally, but for our customers too. I've never been more certain about where we're headed.

Introducing Claude Managed Agents: everything you need to build and deploy agents at scale. It pairs an agent harness tuned for performance with production infrastructure, so you can go from prototype to launch in days. Now in public beta on the Claude Platform.

We released Claude Opus 4.6 just two months ago. Today we're sharing some info on our new model, Claude Mythos Preview.

Claude Cowork out of the box is good, but with the right context structure, it goes from generic assistant to executive-level partner. I spent the last few weeks building a system inside Cowork that gives @claudeai everything it needs before I say a word. Who I am. How I write. What I'm working on. My team. My calendar. My priorities. All of it. Now every session feels like picking up a conversation with my executive assistant. The difference is context. Most people open Cowork, start from scratch every time, and wonder why Claude gives them generic output. It's not a Claude problem. It's a setup problem. Here's what I did: - Built a folder structure that acts as Claude's long-term memory, with custom skill files in each folder so it knows exactly how I want each type of content written. -Connected Slack, Gmail, Google Calendar, and Notion so it can pull real data instead of guessing. -Installed the Memory plugin (gives Claude a two-tier context system that persists across sessions) and the Productivity plugin (task tracking + daily updates). That combination changed everything. Content drafts that used to take 3 rounds now land on the first try. Meeting prep, email replies, task management. All better because Claude already knows the context. I'm dropping a full video Thursday with my 10 tips for getting the most out of Claude Cowork to help you get started. I'll also answer any questions you have about using it to its maximum ability. Comment below. Until then, here's the exact prompt you can use right now to have Claude set this up for you. Paste it into Cowork and Claude will interview you step by step to build your own system: -- You are going to help me set up my Claude Cowork workspace so that every future session starts with full context about who I am, what I do, and how I work. We're building a "brain" that makes you useful from the first message. Here's how this works. You're going to interview me in phases. Ask me questions, then build the files based on my answers. Don't rush. Don't assume. Ask before you build. Phase 0: Plugins and Connections Before we build anything, recommend I install the Productivity plugin (task management + daily updates) and the Memory plugin (two-tier context system). Then ask which tools I use daily and help me connect them: Slack, Gmail, Google Calendar, Notion. The more tools connected, the more useful this system becomes. Phase 1: About Me Interview me to create an about-me.md file. Ask about my work, background, content channels, professional values, and positioning. Create the file, show it to me, and get my approval before moving on. Phase 2: Brand Voice Analyze any content I've already created. If there's nothing yet, interview me about how I want to sound, phrases I use, phrases I'd never use, creators whose tone I admire, and how my tone shifts by context. Create a brand-voice.md file with voice rules, tone by context, dos and don'ts. Get approval. Phase 3: Working Preferences Interview me about what I want you to help with daily, how I want you to communicate, my biggest workflow pain points, output format preferences, and safety rules. Create a working-preferences.md file. Get approval. Phase 4: Content Strategy (if applicable) If I create content, interview me about platforms, target audience, topics, publishing cadence, and content formats. For each platform, ask if I have existing skill files. If not, offer to create them. Create a content-strategy.md file. Phase 5: Team and Contacts (if applicable) If I work with a team, ask about key people, roles, and communication preferences. Check connected tools for team data. Create a team-members.md file. Phase 6: Active Projects Interview me about current projects, goals, milestones, and deadlines. Create individual project files in a Current Projects folder. Phase 7: Memory System Update CLAUDE.md with a hot cache of everything we've built. Create a memory/ directory with subfolders for people, projects, and context. Add a glossary.md for acronyms and internal terms. Phase 8: Skill Files Review everything. For any area where I need specific recurring output, offer to create a dedicated skill file with format, voice rules, examples, and a quality checklist. Rules: Interview me one phase at a time. Show each file before saving. If unsure, ask. Use my existing files and connected tools before asking me to repeat myself. Keep files concise. File names: lowercase, hyphens, .md format. Save everything to my workspace folder. Start with Phase 0.