2026-08-10 23:01:49
Listen now on YouTube • Spotify • Apple Podcasts
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Claire built an AI agent that reviews pull requests, scores their risk, auto-approves the safest ones, and sends anything questionable to Slack. In this episode, she breaks down how she built the entire thing in one Codex session using Vercel Eve, and why letting AI review AI-generated code may be a lot less risky than it sounds.
You don’t need a human to review every AI-generated PR. That may sound reckless, but it’s increasingly looking like the smarter operating model. Intercom has already shown this can work at scale: PRs approved by its AI system move five times as fast as human-reviewed ones and have a lower revert rate. In other words, the AI-reviewed code isn’t just shipping faster—it’s less likely to need fixing after it reaches production.
The key is having a clear way to separate changes that can skip human review from ones that can’t. The risk model used here scores each PR across six dimensions: the size of the change, its blast radius, how easily it can be reversed, its data and security implications, its operational impact, and whether tests and CI have actually been completed. Anything below 24 points is classified as low risk and cleared by the agent; anything above 64 goes straight to a human for review. The exact numbers matter less than turning a vague judgment call into a repeatable system.
Vercel’s Eve may be the fastest way to deploy a serious internal AI agent across Slack and GitHub without spending weeks building infrastructure. It handles the annoying plumbing—connectors, refresh tokens, sandboxing, and routing across channels—so the actual work becomes writing instructions and skills in Markdown instead of babysitting OAuth flows.
A useful internal agent can now be built and deployed in a single Codex session, starting with a prompt that’s only a couple of sentences long. In this case, the initial ask was essentially: build a GitHub bot that waits for checks to pass; grades each PR as low, medium, or high risk; and automatically approves the low-risk ones. Everything after that was steering and refinement, not a giant up-front specification.
Browser use removes much of the configuration tax that makes agent setup feel harder than it should. Creating a Slack bot and GitHub app manually normally means clicking through endless permission screens, choosing scopes, and managing tokens. Codex handled almost all of that through the browser. The human’s job was mostly to click “save” and complete 2FA. What usually takes hours took minutes.
SOC 2 compliance and automatically approved PRs are not inherently at odds. The important part is making the process legible: the risk model needs to be reflected in the company’s code-review and security policies, every decision needs to be logged, and the resulting audit trail needs to be easy to query and defend. The security team’s role is to help design the right framework, not simply block automation because it feels unfamiliar.
The operational design matters just as much as the underlying technology. Merge Mommy doesn’t actually merge anything. Instead, it posts a gray check in GitHub as a signal, then sends a Slack message with the risk score and a note saying the PR is ready to approve and merge. That small handoff preserves human accountability for the final action while eliminating most of the cognitive work involved in reviewing a routine change.
Evals are what keep internal agents trustworthy after the novelty wears off. Intercom logs every PR review its agent produces and then has an engineer assess whether the score and recommendation were correct. That’s the same discipline strong teams already bring to customer-facing AI products. Internal agents may feel less visible, but when they touch something as important as the codebase, they need the same protection against regressions.
The surprising thing about building an Eve agent is how little “building” is actually involved. The full instructions for Merge Mommy fit on roughly a page: a few paragraphs, a handful of bullets, and a short skill file. There isn’t much framework-specific magic to learn. The core skill is simply being able to explain, clearly and precisely, what the agent should do.
How I Built ‘Merge Mommy’: My AI Bot for Auto-Reviewing Pull Requests with Vercel Eve: https://www.chatprd.ai/how-i-ai/merge-mommy-vercel-eve-ai-bot-for-auto-reviewing-pull-requests
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Hyperagent—Deploy fleets of agents that handle real work
Grace Clarke is an AI educator and former marketing consultant who rebuilt her entire service business around Claude. In this episode, she walks through the three Claude skills that run her business: an hourly client pipeline, a proposal builder, and a voice guide that teaches Claude how she thinks. She also shows how she replaced Gmail with her own Claude-powered inbox, why she believes intent engineering matters more than prompt engineering, and how non-technical people can start building useful AI workflows without writing code.
You don’t need to be technical to build a business workflow with Claude. You need to be clear about what’s broken. Grace started by opening Claude Code and talking for a few minutes about everything driving her crazy: too many emails, client communication that didn’t feel warm enough, and 20 hours of admin every week. Claude helped turn that into an operating system for her business.
Intent engineering matters more than prompt engineering. Grace doesn’t spend time crafting the perfect prompt. She explains the problem, describes the outcome she wants, and asks Claude to come back with a proposal. Her philosophy is simple: the burden of figuring out what to do next shouldn’t always fall on the person. Give Claude enough context, and it should be able to study how you work and bring you strong ideas to react to.
Grace’s voice guide isn’t really a writing guide. It’s closer to a “think like Grace” file. It captures how she makes decisions, what she believes about teaching versus consulting, what good communication sounds like, and even the kinds of LinkedIn posts she never wants to resemble. Whenever she sees something that makes her cringe, she sends Claude a voice note and updates the guide.
Doing all of your email inside Gmail means almost none of that work compounds. Every response contains useful context: how a client communicates, what tone works with them, what they care about, and the history of the relationship. But if that context stays buried in Gmail, the AI never gets smarter from it. Grace moved her inbox workflow into Claude so every interaction can become useful context for the next one.
Grace has developed a surprisingly elegant way to move between Claude Code and Cowork. She uses Claude Code when she wants something proactive that will go figure things out. Then, when she wants a more visual and approachable environment, she has Claude Code create a Markdown handoff file and drops it into a new Cowork session. The result is a simple way to carry context from one environment to another without starting over.
The biggest barrier to adopting AI may be less about fear and more about muscle memory. Grace used to give students carefully engineered prompts so they could experience an immediate win. Her students told her that approach was actually making things harder. What helped more was building the habit of reaching for AI in the first place. Now she’ll do things like send a Slack reminder telling students to screenshot whatever they’re working on and drop it into Claude. No perfect prompt, no required outcome—just practice.
Skill files may be one of the most underrated ideas in agentic AI. Grace runs much of her business around three of them: a pipeline operator, a proposal maker, and a voice guide. Each is essentially a documented set of instructions Claude can reuse. She teaches students to build them the same way they would train a new employee: explain the job, walk through how it should be done, correct mistakes, and keep improving the instructions over time.
One of the best ways to sell someone on AI is to show them what it can do before explaining it. Grace gives new clients a password-protected, branded, interactive welcome experience she built in Claude. It’s part onboarding, part proposal, and part demo. By the time a client enters the password and starts clicking around, they already understand what makes this new way of working different.
Grace Clarke’s Claude Workflows for Business Automation and Rebuilding Gmail
https://www.chatprd.ai/how-i-ai/claude-workflows-for-business-automation-and-managing-gmail
↳ Automate Client Proposals and Onboarding with a Claude “Pipeline Operator”
↳ How to Rebuild Your Gmail Inbox Inside Claude to Manage Email
↳ Create an Automated Workout Tracker with a Simple Claude Voice Note
If you’re enjoying these episodes, reply and let me know what you’d love to learn more about: AI workflows, hiring, growth, product strategy—anything.
Catch you next week,
Lenny
P.S. Want every new episode delivered the moment it drops? Hit “Follow” on your favorite podcast app.
2026-08-10 20:01:44
Grace Clarke is an AI educator and former marketing consultant who taught herself Claude Code earlier this year and built a curriculum out of the process. She now runs her entire service business on tools she’s built with Claude, including a pipeline operator, a proposal maker, and a Gmail replacement she created in under 30 minutes, and teaches individuals and teams to do the same.
Listen or watch on YouTube, Spotify, or Apple Podcasts
How to build an hourly pipeline in Claude that moves clients through your process automatically
Why Grace ditched traditional proposals for password-protected, interactive HTML documents built in Claude
How she uses a “voice guide” skill file so every Claude output sounds like her, not like AI slop
The two-step forcing function she teaches non-technical clients to build the muscle of opening Claude
Why she started building in Claude Code, then handed the work off to Cowork via a Markdown session file
How she replaced Gmail entirely with a custom inbox
Why she teaches “intent engineering” instead of prompt engineering, and what that looks like in practice
How she uses Claude on her phone, on walks, to track workouts and manage plants alongside client work
Bolt.new—Turn your idea into a real product
Hyperagent—Deploy fleets of agents that handle real work
(00:00) Grace’s background and why she started building with Claude
(04:48) The pipeline operator: what it is and how it runs her business every hour
(08:48) Building the muscle memory to use AI
(12:02) What goes into building a skill file (voice guide, proposal rules, versioning)
(13:50) How she built her proposal maker
(16:15) The voice guide: teaching Claude how she thinks, not just how she writes
(21:22) Live demo of the custom Gmail replacement built in Cowork
(30:44) Workout tracking, plant photos, and tiny daily Claude habits
(34:51) The biggest misconception holding people back from adopting AI
(38:36) What Grace does when Claude is not giving her what she wants
(40:38) Claude builds a proposal for Claire in real time
• Claude: https://claude.ai
• Claude Code: https://claude.ai/code
• Netlify: https://www.netlify.com
• Google Forms: https://forms.google.com
• Google Sheets: https://sheets.google.com
• Google Cloud (for service accounts and custom connectors): https://cloud.google.com
• Stratechery by Ben Thompson: https://stratechery.com
LinkedIn: https://www.linkedin.com/in/gracegclarke/
ChatPRD: https://www.chatprd.ai/
Website: https://clairevo.com/
LinkedIn: https://www.linkedin.com/in/clairevo/
Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].
2026-08-09 20:31:29
Adam Ward is the Head of Talent at Cursor, one of the fastest-growing developer tools in history. Before joining Cursor, he founded Growth by Design, an independent recruiting and talent strategy firm that helped build teams at the most ambitious AI and technology companies in the world. Adam has spent more than 20 years building elite, high-talent-density teams across the industry and is widely regarded as one of the most effective and creative recruiters in tech.
Listen on YouTube, Spotify, and Apple Podcasts
Inside today’s “tale of two cities” talent market
Why the traditional recruiting funnel—what Adam calls the “funnel of doom”—leads to mediocre hires
Adam’s three-step playbook: scoping, mapping, and relentless pursuit
The worst question to ask when sourcing great talent
The rise of the forward deployed engineer—and how to become one
The biggest mistake founders make when hiring their first recruiter
WorkOS—Make your app enterprise-ready, with SSO, SCIM, RBAC, and more
Mercury—Radically different banking, now with Command
• LinkedIn: https://www.linkedin.com/in/adampward
• Cursor: https://cursor.com
• Trilogy: https://trilogy.com
• Brie Wolfson on LinkedIn: https://www.linkedin.com/in/brie-wolfson-17758724
• Inside Cursor: https://colossus.com/article/inside-cursor
• SpaceX: https://www.spacex.com
• Joe Gebbia’s website: https://joegebbia.com
• The rise of Cursor: The $300M ARR AI tool that engineers can’t stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell
• The Pitt on HBO Max: https://www.hbomax.com/shows/pitt-2024/e6e7bad9-d48d-4434-b334-7c651ffc4bdf
• The Bear on Hulu: https://www.hulu.com/series/the-bear-05eb6a8e-90ed-4947-8c0b-e6536cbddd5f
• Granola: https://www.granola.ai
• Wispr Flow: https://wisprflow.ai
• 11 products I love, free for a year—the biggest Product Pass expansion in 2 years: https://www.lennysnewsletter.com/p/productpass-summer2026launch
• How to debug a team that isn’t working: the Waterline Model: https://www.lennysnewsletter.com/p/how-to-debug-a-team-that-isnt-working
• The high-growth handbook: Molly Graham’s frameworks for leading through chaos, change, and scale: https://www.lennysnewsletter.com/p/the-high-growth-handbook-molly-graham
• Emotional Intelligence: Why It Can Matter More Than IQ: https://www.amazon.com/dp/055338371X
• High Growth Handbook: Scaling Startups from 10 to 10,000 People: https://www.amazon.com/High-Growth-Handbook-Elad-Gil/dp/1732265100
• Scaling People: Tactics for Management and Company Building: https://press.stripe.com/scaling-people
Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].
Lenny may be an investor in the companies discussed.
2026-08-09 01:08:14
👋 Hello and welcome to this week’s edition of ✨ Community Wisdom ✨ a subscriber-only email, delivered every Saturday, highlighting the most helpful conversations in our members-only Slack community.
2026-08-05 20:04:01
AI writes most of my code now, and that created a new problem: a PR queue I couldn’t keep up with. In this episode, I walk through how I built Merge Mommy, a Vercel Eve agent that reads every PR after checks pass, scores it across six risk dimensions, auto-approves the low-risk ones, and pings me in Slack for anything that needs a human. I built the whole thing in one Codex session, it’s SOC 2 compatible, and it’s already cleared my backlog.
Listen or watch on YouTube, Spotify, or Apple Podcasts
Why AI-generated PRs create a review bottleneck and why the answer isn’t reviewing all of them
How Intercom 5x’d PR approval speed and reduced revert rates by putting AI in the review loop
Why Vercel Eve is the simplest framework I’ve found for deploying AI agents in Slack and GitHub
How I built a full PR review agent in Codex with one prompt and a few steering turns
The six components I use to score PR risk (blast radius, reversibility, data security, ops impact, verification gap, and change surface)
How I used Chrome browser use to handle Slack bot and GitHub app configuration so I never had to click through setup screens manually
Why auto-approved PRs can be SOC 2 compliant as long as the process is auditable, queryable, and in your risk policy
How to set up Slack escalation so low-risk PRs become a two-click merge with no manual review
WorkOS—Make your app Enterprise Ready, with SSO, SCIM, RBAC, and more
(00:00) The PR review backlog problem nobody’s talking about
(02:35) Why you don’t have to review every AI-generated PR
(05:14) How Intercom built AI-approved PRs (and proved they’re safer)
(06:10) How the Eve framework works (directory, skills, channels, connectors)
(09:16) The Codex prompt I used to build the entire bot
(11:36) What the agent actually does: read, score, approve, or escalate
(13:07) Setting up your Eve agent
(15:47) The six-component risk scoring model
(17:23) Merge Mommy in action: three live PR examples
(21:10) Recap and how to build your own version
• Vercel Eve: https://vercel.com/eve
• Vercel AI SDK: https://sdk.vercel.ai/
• Vercel Chat SDK: https://chat-sdk.dev/
• Codex (OpenAI): https://openai.com/codex
• AI is approving our pull requests: Here’s how we made it safe: https://www.intercom.com/blog/ai-is-approving-our-pull-requests-heres-how-we-made-it-safe/
• Review is the bottleneck now: How we let AI approve pull requests (safely): https://rewind.com/blog/ai-approve-pull-requests-safely/
ChatPRD: https://www.chatprd.ai/
Website: https://clairevo.com/
LinkedIn: https://www.linkedin.com/in/clairevo/
Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].
2026-08-04 21:02:53
👋 Hey there, I’m Lenny. Each week, I share deeply researched product, growth, and career advice. For more: Lenny’s Podcast | Lennybot | How I AI | Become an AI-Native Builder and other favorite AI/PM courses
P.S. Get a full free year of Cursor, Notion, Replit, Lovable, Factory, Wispr Flow, Linear, ElevenLabs, PostHog, Brain.fm, Waking Up, and more, by becoming an Insider subscriber (while supplies last). Learn more.
Molly Graham’s first guest post, The Waterline Model, quickly rose to be my 7th most popular post of all time—extra impressive for not being about AI. I suspect this post will rise even faster.
Below, Molly introduces the concept of emergence as an alternative to conventional career advice. What she describes is exactly what my career path has looked like, and it’s a pattern I’ve seen across most of the successful people I know. If you’re worried about not having a plan for your career, or if your plan isn’t going according to plan, you’ll feel better after reading this post.
If you’re not familiar with Molly, she’s . . . incredible. She was an early employee at Google and Facebook, COO at Quip (working closely with Bret Taylor), helped build the Chan Zuckerberg Initiative (working closely with Priscilla Chan and Mark Zuckerberg), co-founder of Glue Club, co-founder of The Guild, and most recently, host of TED’s WorkLife podcast (taking over for Adam Grant). At 22, she was leading 75-day wilderness expeditions in Patagonia and Alaska for the National Outdoor Leadership School. Tl;dr, she’s seen and done a lot.
Let’s get into it.
Sheryl Sandberg once told me that everyone should have a two-year plan and a 20-year plan. The first, I could figure out; 20 always looked fuzzy.
I’ve never had a career plan. And I’ve always felt a little broken because of it.
We’re taught that careers should look like a set of stairs—you decide where you want to end up and march upward. When you look at many successful people, their careers can often appear like that from the outside.
My resume includes jobs at some big-name companies, C-level titles, and fun-looking solo ventures, but I have always wondered if it suffered from lack of design or clear destination in mind. At times, it has felt more like a game of chutes and ladders than any kind of stairs.
But recently, a conversation with Mark Rober completely changed how I think about my career. Don’t know Mark? Ask any 8-year-old who he is. He is one of the most popular creators on YouTube—76 million followers, 16 billion views—and he’s built that audience by making science genuinely fun and accessible. He’s put out one video a month on YouTube for 15 years, with remarkable consistency.
I asked him how he’s stayed grounded across a career on a platform with its own relentless pressures. Mark said he’s never had a long-term plan. Fifteen years of consistency, and none of it was by design. Instead, he has a clear set of principles that guide him, and he focuses only on the next step in front of him. And then, according to Mark, “good shit’s gonna happen.”
Then Mark introduced me to the scientific concept of emergence, a process that occurs in nature when multiple parts come together to form a complex whole without a clear plan or intention. I had a strange feeling when I heard him talk about how he trusts an emergent philosophy to guide his own career. He was describing something I’d already been doing for years, without ever having a name for it.
Emergence tells us there’s a different way to build a career: not by optimizing toward a destination but by getting really clear on your principles, learning to follow your energy, and trusting that the path will reveal itself. In some ways, an emergent career is harder to manage than having a plan and staying loyal to it. There are moments of real uncertainty, and stretches where you can’t see where you’re going. But all of that uncertainty (and all of that faith) is exactly what creates room for the opportunities you couldn’t have seen coming—which, in my experience, are the ones that matter most to a career that works for you.
A murmuration of starlings—thousands of birds moving together in those wild, shape-shifting clouds you see in videos—has no choreographer. Each bird follows three simple rules: stay close to your neighbors, don’t collide, and move in the same general direction. That’s it. From those three rules, something breathtaking appears. An outcome no single bird designed or planned.
Same with a beehive. No bee has the blueprint for the colony. Each bee just follows its local rules—tend the larvae, forage for pollen, respond to signals. But the colony as a whole can regulate its own temperature, navigate to food sources miles away, and survive for decades. A single ant isn’t intelligent in any impressive way. Yet an ant colony can find food, build bridges, regulate temperature, wage war, and adapt to changes in its environment. That capability doesn’t exist in any one of them; it only comes together in the colony as a whole.
That’s the strange magic of emergence: the whole becomes capable of things that are completely invisible at the level of the parts. Emergence is what happens when simple, consistent principles—applied locally, over time—produce something complex and beautiful that couldn’t have been predicted or designed in advance.
In an emergent career, you are both the individual bird and the whole murmuration—the one following the rules and the one becoming something those rules couldn’t have predicted. Every decision you make, every person you work with, every risk you take or don’t take—those are your local rules in action. You can’t see the pattern they’re creating from inside it. You can only see the next step. Yet over time, something emerges. A body of work, a reputation. Something that looks, in retrospect, like it was designed, even though no single decision along the way felt like a plan.
My whole career has been example after example of the power of emergence, but I’ll give you the best one, which is also the most recent. I stepped off the traditional career path four years ago with no plan. I simply started saying no to the jobs I was known for—COO roles at bigger and more impressive companies—because they no longer brought me joy. It was scary, and it felt necessary. I explored a bunch of different paths and worked hard to learn to listen to the parts of myself other than my ego. It was hard. I felt exhausted and confused a lot, particularly when someone offered me some new fancy job I knew I’d be great at. My ego really, really wanted to say yes. I kept saying no.
I built the leadership communities Glue Club and The Guild. I wrote on LinkedIn and Substack. Not because I had a vision for what any of this could become or because any of it made sense to anyone else, but because they made me happy every day. I was learning, working with people I loved, and having the kind of impact that mattered to me. All of it brought me energy, and I was committed to focusing on that compass. That said, more than any other time in my career, I felt like I was walking through a dark tunnel, with no sense of where I was going. Every magical moment in my career has been entangled with periods of confusion, discomfort, and darkness.
Then TED asked me to give a talk, and I said yes because I was excited about what I would learn and how I could connect with people through the talk. It felt a little random at the time but turned out to matter more than I expected. Someone on my team said, “I think this might be the beginning of something.” I said, “I just want the talk to be good.”
A year after my talk came out, TED came back and asked me to take over WorkLife, the podcast that TED and Adam Grant had spent seven years building. When they made that offer, it was like someone had turned the lights on in the tunnel. They saw me in a way that I could not see myself. That offer transformed my weird, disconnected pile of projects into a whole that felt like magic.
When I’ve talked to successful people about their own career path, almost all of them have a story that sounds like emergence.
As an example, I asked my friend Claire Hughes Johnson, the former COO of Stripe, about how she’s made career decisions and how she thinks about her life’s work. On paper, Claire’s path—politics, to senior operations and product leadership at Google, to COO of Stripe—looks very methodical and designed. But in conversation, she makes it clear that she never had a plan and was just focused on the right next step:
“Am I learning? Am I motivated? Am I in the right job? Is this the right impact? Is this what I want to be doing? . . . I think some people look [at my career] and they’re like, oh, you charted this course of success.
No, I was kind of unsatisfied, and just kept trying to find the thing . . . I don’t feel like I will figure out what my life’s work is. It will end up being the work that I did.”
It’s pretty weird to hear someone as successful as Claire say, even at this point in her career, that she doesn’t know what her life’s work is. But it honestly made me feel less crazy. As Claire explains it, she has two principles—she wants to learn and have a significant impact—and focuses on making the best next decision based on those.
To embrace emergence in your career, you have to do exactly what Claire does. You have to push past the traditional questions “How do I get where I want to go?” or “What is my life’s work?” and focus instead on asking, “What’s the right next step for someone with my principles, my energy, my values?”
That can be a harder question: Knowing your principles requires knowing yourself. Taking the next step in line with them often requires risk. You must tolerate uncertainty and real discomfort. You have to bet on yourself and have faith that the path will reveal itself.
After reflecting on my own experiences and hearing so many stories from brilliant successful people through WorkLife, I’ve come to believe that the two keys to an emergent career are defining (and redefining) your own local rules to help you make the next best decision, and following a few universal principles that increase the likelihood of career magic.
And then releasing control and having faith that those two frameworks will lead you to where you’re supposed to be.
Developing your local rules that guide how you make decisions requires listening to yourself and the data you collect over the days, months, and years of work. The ongoing challenge of an emergent career is honing and evolving those rules over time and experience.
I didn’t go looking to prove this theory. I stumbled on it by asking successful people how they made decisions. When they answered, they all offered up their own principles as guiding forces.
Mark Rober’s local rules are: focus on content that teaches, not just entertains; quality over quantity always; and sustainability over everything. He talked about how each of these have helped him decide when to grow his company and when to ignore the YouTube algorithm’s demand for daily posts.
Claire Hughes Johnson told me her compass has always been two words: learning and impact. If a decision gives her both, she moves toward it. If it doesn’t, she doesn’t.
One of my greatest mentors, Patty Stonesifer—an early executive at Microsoft, the first CEO of the Gates Foundation, and one of the first independent board members of Amazon—described four principles that she articulates in a mission statement: love and be loved, seek justice, learn, and laugh. She uses them to evaluate how she spends her time (she literally has a monthly worksheet she prints out to plan and evaluate her time against her principles).
Adam Grant, the organizational psychologist, has three. He talked about the principles that guide how he chooses which book to write next on WorkLife, but in a follow-up email, he crystallized his career decision principles down to: interest (“Will I wake up in the morning excited about it?”), importance (“Does it align with my values?”), and impact (“Can I make a unique contribution?”).
While writing this post, I asked Lenny what his are, and he said: follow my energy, keep the quality bar high, and be useful.
Mine, for the early part of my career, were three things: learning, people, and mission. I thought of it as a three-legged stool.
Learning, for me, didn’t mean a little learning—it meant a curve so steep I was terrified. I get energy from being in over my head. People meant I needed to be surrounded by people I was excited to learn from. And mission meant I needed to feel like the problem I was working on actually mattered and that I personally wanted to devote my time and energy to solving it. Not every important problem is the right one for me.
The point of these rules is to guide your personal decision-making. When presented with two choices, how do you decide what the right next step is? How do you explain why something that might feel so right to someone else feels wrong for you?
When Bret Taylor asked me to join him at Quip and help figure out the business, I ran it through my principles almost instinctively. Learning? Terrifying amounts of it—I’d never built a SaaS business, never done sales or marketing before. People? Bret is someone I was excited to keep learning from, and I knew he’d assemble an extraordinary team. Mission? Well, productivity software for teams didn’t feel especially meaningful to me—my stool had one wobbly leg—but I felt that the other two were so strong that it didn’t matter. I went in with my eyes open about why I was there and placed a bet based on my principles.
My local rules have changed over time—what I needed from work at 30 was different from what I needed at 40—and almost everyone’s do. Sometimes career decisions help you discover a rule (or a nuance of a rule) that you didn’t know was so important to you. That happened to Patty Stonesifer in the middle of her career. After leaving a senior executive role at Microsoft, she accepted a senior position at DreamWorks because it sounded cool. But about three months in, Bill and Melinda Gates approached her with the opportunity to help create and build the Gates Foundation, and she realized that at DreamWorks she was missing some pieces that were really important to her. That gut check led her to create her mission statement and articulate her “seek justice” pillar.
In that WorkLife conversation, she also shared that her enthusiasm for learning, one of her principles, can overpower everything and, like my wobbly stool legs, she’s had to think about ensuring that there is the right balance across the different principles to not let one of them guide all the decisions.
For me, the only principle that hasn’t changed at all is learning. I still need to be terrified or I’m bored. But I’ve gotten much more clear on the impact that matters to me, and the people leg of my principles has gotten more specific—I need people I look forward to working with every day, people who see me clearly, and people I can clearly unlock. I’ve added some new rules too, like “seek joy,” which wasn’t a priority for me earlier in my career. These days, loving my hours and days is one of the main ways I measure my overall career satisfaction.
The most powerful signal I’ve found for defining your own local rules is your energy. Not your ambitions, not what looks good on paper, not what your parents think—what work energizes you. The question to ask is “What actually lights me up today?” not “What should I want?”
There are a bunch of exercises out there that can help you do this. Here are two that have been really useful to me:
Spend a week scoring your energy after every part of your day. For many of us, this can be broken down into 30- or 60-minute segments like meetings or work blocks. At the end of the day, sit down and score each 30-minute block on a scale from 1 to 10. My coach, Maggie Hensle, had me do this when I was at a lost moment in one job, and it came back all 1s and 10s. My day was filled with an almost equal amount of work that lit me up and work that made me want to bash my head against the wall. But most importantly, when I really dissected the 10s, I realized that the best work for me was coaching, mentoring, sponsoring, and connecting with people. It was an important insight that indirectly led me to the community work that I do now.
Identify your peak moments. Whenever I am trying to understand the work that lights people up, I ask them a series of questions: “Looking back over the past three to five years, what are three key moments when you felt like you were at your best? What are the work moments you are proudest of over those years? When you think about activities where the time flew by or you felt like you could have kept going forever, what were they?” Questions like these help you describe the type of work that excites you and brings out the best in you. The ideal way to do this exercise is with a coach or a best friend—someone who is rooting for you and will hear the patterns when you describe your answers. That person can share back with you some of the words or themes that come up over and over again.
Whatever exercise you choose, you are looking for patterns. Those patterns are your local rules in disguise.
Knowing your local rules tells you how to decide on your best next step. But the truth is that there are also universal principles that increase the odds of magic. These behaviors and actions are not a plan. Instead, they’re creating the conditions for “good shit” to happen (to borrow Mark Rober’s words). And without them, you’re probably leaving a lot of magic on the table.