In this episode, Andy talks with Ashley Herd, HR and legal leader turned management coach, and author of The Manager Method. Ashley has led HR and legal teams at organizations like McKinsey and Yum Brands, and she brings a refreshingly real-talk approach to the challenges every manager faces, especially those quiet moments of self-doubt that come with growing responsibility.
In this conversation, you'll hear Ashley's take on why imposter feelings are so common among thoughtful leaders, and how her concept of the "career quilt" reframes even the most uncomfortable professional experiences. She introduces her simple but powerful Pause, Consider, Act framework, which is a practical tool for navigating tough management moments without reacting on instinct. You'll also hear how the language we use about people shapes the way we lead them, why delegation is harder than it looks, and how accountability can be reframed as a positive force on your team. Ashley even shares how Pause, Consider, Act has made her a better parent.
If you're looking for a grounded, practical guide to leading people well (without burning yourself out) this episode is for you!
You can learn more about Ashley and her work at ManagerMethod.com.
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Thank you for joining me for this episode of The People and Projects Podcast!
Talent Triangle: Power Skills
Topics: Leadership, Management, Imposter Phenomenon, Delegation, Accountability, Empathy, Team Culture, Communication, Self-Awareness, New Managers, Personal Growth, Psychological Safety
The following music was used for this episode:
Music: Underground Shadows by MusicLFiles
License (CC BY 4.0): https://filmmusic.io/standard-license
Music: Tuesday by Sascha Ende
License (CC BY 4.0): https://filmmusic.io/standard-license
Imported Insights and Memory Palace diary subtabs so Dreaming can inspect imported source chats, compiled wiki pages, and full source pages directly from the UI. (#64505)[embed ...] rich output tag, and gate external embed URLs behind config. (#64104)providerOptions, reference audio inputs, per-asset role hints, adaptive aspect-ratio support, and a higher image-input cap so video providers can expose richer generation modes without forcing large files into memory. (#61987, #61988) Thanks @xieyongliang./api/show context-window and capability metadata during model discovery so repeated picker refreshes stop refetching unchanged models, while still retrying after empty responses and invalidating on digest changes. (#64753) Thanks @ImLukeF.invalid_scope before returning an authorization code. (#64713) Thanks @fuller-stack-dev.default. (#53918) Thanks @yhyatt.asyncCompletion in the generated zod schema so documented async completion config no longer fails with an unrecognized-key error. (#63618)numberOfVideos request field so Gemini Developer API Veo runs do not fail before OpenClaw can complete the intended Google video generation path. (#64723) Thanks @velvet-shark.openclaw completion --write-state working even if QA setup is broken. (#64648) Thanks @obviyus.message react through the gateway-owned action path so reactions use the live WhatsApp listener in both DM and group chats, matching message send and message poll. Thanks @mcaxtr.MessageThreadId, so one topic session no longer alternates between bare and topic-qualified transcript files. (#64869) Thanks @jalehman.api: "anthropic-messages" and authHeader: true into the minimax-portal config patch during openclaw configure, so re-authenticated portal setups keep Bearer auth routing working. (#64964) Thanks @ryanlee666.Read more of this story at Slashdot.

This week on the GeekWire Podcast: we take the show on the road — or rather, on the rails — recording on Sound Transit’s 2 Line as we ride the world’s first light rail on a floating bridge from Seattle’s Northgate neighborhood to Microsoft’s campus in Redmond.
It’s an engineering marvel decades in the making — the bridge, that is, not the podcast. That said, juggling a couple of handheld mics and portable recorder on a crowded train, we did have to overcome some logistical challenges to make it happen.

Along the way, we chat with fellow passengers and talk about the week’s headlines, including Anduril’s autonomous warship facility on Seattle’s ship canal, and golf star Bryson DeChambeau’s acquisition of Bellevue-based Sportsbox AI ahead of the Masters.
Then we get a behind-the-scenes look at the engineering from Sound Transit’s Henry Bendon. He explains how engineers solved the unprecedented challenge of running 55 mph trains on a bridge that constantly moves with wind, waves, and changing lake levels.
Bendon describes the surge in ridership since the Crosslake Connection opened on March 28, and what the line means for connecting the tech hubs on both sides of the lake.
After arriving in Redmond, we sit down with Microsoft President Brad Smith to talk about the company’s two-decade role in making the Crosslake Connection a reality.
Smith says the line gives people “a choice they didn’t have a month ago.”
We ask what it says about how we build big things in this region that it took nearly 60 years to get from idea to reality. “What really matters is people stuck with it,” he says.

We discuss the unlikely duo of Microsoft and Amazon — fierce competitors in cloud computing and AI — collaborating on regional transit and civic issues. “When it comes to local issues, we’re not competing with Amazon, we’re working together,” Smith says.
And finally, we challenge him with a trivia question that hits close to home.
Subscribe to GeekWire in Apple Podcasts, Spotify, or wherever you listen.
Philip Su has spent two decades at the highest levels of software engineering — Microsoft, Meta (where he reached Distinguished Engineer, IC9), OpenAI, and now building his own product solo with AI. In this episode, he makes a provocative case: the individual contributor role as we know it is over, code reviews are becoming a liability, and the best engineers are already managing AI agents instead of writing code themselves.
"Every day at work, I lifted six tons of packages with my arms. No one learned my name. And it was the structure — the ability to leave work behind when I clocked out — that pulled me out of a spiral."
Philip's path through tech is anything but typical. After scaling Facebook's London engineering office from a dozen engineers to 500+, he stepped away from Big Tech entirely. During Peak 2021, he worked the floor at Amazon's flagship warehouse south of Seattle — 11-hour shifts, processing 15,000 packages a day. He documented the experience in his Peak Salvation podcast, exploring depression, the divide between the wealthy and the working class, and the maddening inefficiencies inside one of the world's largest employers. That experience reshaped how he thinks about work, systems, and what actually matters when you strip away titles and stock options. He later joined OpenAI as an individual contributor — going from leading hundreds of engineers to writing code again — before leaving to build Superphonic, an AI-powered podcast player.
"We'll one day be scared, positively petrified, to use any mission-critical software known to have allowed human interference in its codebase."
Philip borrows the concept of "lights-out" from data centers that run with zero human workers and applies it to codebases. A lights-out codebase is one where no human ever sees or edits the code. He's already built two apps this way — Tanya's Snowfield and OTD: On This Day — without looking at a single line of code from repository creation through production release. His argument is not just about efficiency. Code reviewers are becoming the bottleneck. The volume of AI-generated code is already too high for humans to keep up, and the same LLM that wrote the code often catches bugs that another instance of itself introduced. Philip has been running both Codex and Cursor as PR reviewers on GitHub, and has been surprised by how often they identify issues in both human- and AI-generated code. He believes we are approaching a threshold where human intervention in codebases will be seen as risky and irresponsible — not the other way around.
"You're not building the thing anymore. You're pondering and tweaking the machine that builds the thing."
In his widely discussed essay "AI Killed the Individual Contributor", Philip argues that maximizing productivity with AI now requires engineers to spend their time on what are essentially management tasks: setting priorities, resolving conflicts, delegating to agents, reviewing output, and giving feedback. The IC role isn't disappearing because AI codes better — it's disappearing because the highest-leverage use of an engineer's time has shifted from writing code to orchestrating the systems that write code. Right now, it feels like managing a team of barely competent interns. But Philip expects that to change fast. Soon it will feel like managing high performers who are faster and more capable than you — and the engineers who thrive will be the ones who learned to let go of the keyboard and focus on judgment, direction, and taste.
"20x productivity means we have 20x fewer PMs than we need."
Philip is putting his thesis to the test with Superphonic, an AI-powered podcast player he's building essentially as a solo founder. What would have required a team two years ago, he now ships alone — leveraging AI agents for coding, testing, and review. But the productivity multiplier creates its own problems. When you can build 20x faster, the bottleneck shifts from engineering capacity to product judgment. You need to know what to build, not just how to build it. Philip's reference to The Mythical Man-Month is deliberate: adding more people (or agents) doesn't solve the fundamental challenge of building the right thing. The hardest part of being both the architect and the manager of your AI agents is knowing when the model breaks down — when you need to step in and do the work yourself rather than delegating.
"There is a lot more that can be done to increase the quality of AI output even if all progress on foundation models stops."
For Scrum Masters and agile coaches helping teams adopt AI tools, Philip's warning is clear: don't treat AI as just another developer on the team. The integration requires rethinking how work is structured, how quality is assured, and what it means to be an engineer. Teams that bolt AI onto existing workflows without changing the underlying process will get marginal gains at best. The ones that redesign their workflows around AI capabilities — including accepting that humans may not need to review every line of code — will see transformational results. Philip's practical advice: do the work yourself first. Understand what the AI is doing before you delegate wholesale. The engineers who skip this step lose the judgment they need to manage the output effectively.
Philip Su is a Distinguished Engineer (IC9) who scaled Facebook's London office from a dozen engineers to 500+, served as site lead at OpenAI, and now builds Superphonic — an AI-powered podcast player. He writes about the future of software work at Molochinations on Substack. LinkedIn
You can link with Philip Su on LinkedIn.