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Ryan is joined by Asaf Savich, Komodor’s AI Engineering Group Manager, to discuss why modern reliability work requires navigating massive cross-service context, what good context engineering actually likes when AI is integrated into site reliability, and how the work of human SREs is shifting towards strategy and AI agent management.
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Sr. Content Developer at Microsoft, working remotely in PA, TechBash conference organizer, former Microsoft MVP, Husband, Dad and Geek.
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Claude Opus 5 analyzed as a mid‑frontier model that challenges Fable and GPT by offering frontier performance at lower cost. Benchmarks show ARC‑AGI and FrontierBench gains, while user reports cite early stopping, argumentative behavior, and integration headaches. Coverage ties Opus 5 to the OpenAI–Hugging Face security incident, emerging safety consortia, and shifting enterprise financing.
The AI Daily Brief helps you understand the most important news and discussions in AI.
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1206. This week, we look at the secret language of video gamers — including why getting "nerfed" is a bad thing and what it means to "rage quit" — and we answer a listener's question about whether the bird "duck" or the verb "duck" came first and whether real ducks actually duck for cover.
The duck segment was by Karen Lunde, a career writer and editor [who spent nine years as a video game journalist.] These days, she writes I'll Go First, a newsletter where she shares her story, then hands you a weekly writing prompt and a metaphorical pen. Find her on igofirst.org.
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Summary
In this episode, Andy welcomes back his friend Stuart Taylor, a PMO leader and PMI PMO Awards judge, author of Becoming the Project Manager. Most of us didn't grow up dreaming of leading projects. We drifted into the role, and then discovered it's far less about plans and methodologies than it is about people, pressure, and learning to lead while you yourself still feel unsure.
Stuart shares the story behind the book, including the university project where he publicly chastised a teammate and the response from his dad that changed how he understood leadership. He and Andy dig into the real value and limits of PM certifications, why AI can help you communicate but can't replace the human part, the stakeholder questions younger Stuart was afraid to ask, what his mentor Wayne taught him about proximity and follow-through, and why a new sponsor has to be sold on your project rather than assumed into it. You'll also hear the 30-minute CV rule and the trouble it once caused him.
If you're looking for an honest, human look at what it actually takes to become the project manager, this episode is for you!
Sound Bites
- "Well, now that you've reprimanded that person, you do realize you've got to go and pick them back up again?"
- "So going out into the world with this as my toolkit, and I thought it was a toolkit, but actually it turned out to be more like a life raft because I ended up clinging onto it without reasoning at an early point in my career."
- "There's an awful lot that falls between the processes, and that's what the early part of the book is really exploring."
- "I don't believe there's great value in repeatedly recycling the same learning over and over and over again. I think there's much greater value in taking that energy and going to learn something about your industry, the, actual industry that you're working in."
- "And also, I should add, you will have greater value to them by being there too, because you're the interesting change person in the room then, rather than one of another 200 change people walking around all talking about the same methodologies."
- "So be the person who is not avoiding hearing about challenges, but actively seeking them out, and cataloging them, and managing them."
- "Something else I've learned: they don't like you tiptoeing around them."
- "But if anybody's having to go into the office more frequently now, go and spend some of that time sitting with the people whose world you are changing."
- "But if your own leader, the person who's supposed to be championing you in the organization just doesn't get it, then you've got an impossible task on your hands."
- "When your sponsor goes or leaves and somebody else comes in and replaces them, don't just assume that, that because they've now been told they're gonna have to be the sponsor of your project, that they understand it and they can see the value in it."
- "Every project that you work on, the benefits, they are your accomplishments."
- "There is no point in being loyal to organizations. Be loyal to people."
Chapters
- 00:00 Introduction
- 01:56 Start of Interview
- 02:15 Growing Up in Walsall and Learning Leadership from Dad
- 07:15 Drifting Into Project Management
- 09:06 When the Methodology Becomes a Life Raft
- 10:14 Why the Playbook That Worked Elsewhere Fails Here
- 11:49 Will AI Create PMs Who Look Prepared but Aren't?
- 13:37 Using AI to Understand a Difficult Stakeholder
- 15:31 The Value and Limits of PM Certifications
- 17:44 The Talent Triangle and Learning Your Industry
- 19:34 Stakeholders Are People, Not Org Charts
- 20:46 Curiosity and Asking Better Questions
- 21:54 Stop Tiptoeing: Busy Stakeholders Want the Point
- 22:55 What Wayne the Mentor Taught Stuart to Notice
- 25:47 Go Sit With Operations
- 28:19 The Power of Proximity
- 29:33 Sponsorship and Why PMOs Collapse
- 34:18 Earning Support and Managing Up
- 35:07 When a New Sponsor Takes Over
- 37:08 Keep Your CV 30 Minutes From Ready
- 39:39 When the 30-Minute Rule Got Stuart in Trouble
- 41:28 Project Lessons That Carried Into Family Life
- 43:23 End of Interview
- 43:58 Andy Comments After the Interview
- 47:08 Outtakes
Learn More
You can learn more about Stuart and his work at InfluentialPMO.com.
For more learning on this topic, check out:
- Episode 474, which is an earlier and pretty candid conversation with Stuart about LinkedIn, careers, and AI.
- Episode 429 with Bill Dow. Bill and Andy talk about the signs that your PMO is going to fail, and you don't have to be in a Project Management Office to get value out of that discussion.
- Episode 441 with Michaela Flick. A discussion on the human side of project management that resonates with much of what you hear from Stuart.
Chat with PMeLa
You can chat directly with PMeLa, ;the podcast's AI person, to get episode recommendations and answers to your project management and leadership questions. Visit PeopleAndProjectsPodcast.com/PMeLa to chat with her.
Join Us for LEAD52
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Thank you for joining me for this episode of The People and Projects Podcast!
Talent Triangle: Business Acumen
Topics: Project Management, Leadership, Stakeholder Management, Sponsorship, PMO, Mentoring, Career Development, Certifications, Artificial Intelligence, Communication, Influence, Professional Growth
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Music: Brooklyn Nights by Tim Kulig
License (CC BY 4.0): https://filmmusic.io/standard-license
Music: Fashion Corporate by Frank Schroeter
License (CC BY 4.0): https://filmmusic.io/standard-license
Download audio: https://traffic.libsyn.com/secure/peopleandprojectspodcast/516-StuartTaylor.mp3?dest-id=107017
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Amodei in his latest blog post wrote a mix of agreeable things and things that I believe misrepresent where the real risk of AI is located. I want to focus my attention on why, among all the risks, open weight models constitute the mildest one. I write these words as a person who strongly believes AI may be very dangerous in the near future:
1. Exactly like what happened during the OpenAI / HF incident (which was a joke, but focus on the modalities, not the outcomes), the first serious AI incident is very likely to happen *inside* the walls of frontier AI labs, while testing a new model, or while the AI lab employees, or the few externals who have access, do something wrong compared to the expected power of the model.
2. Closed models that will never even be opened to the public will be just a few TBs of data. All you need to leak one is a single person with access and the wrong goals, and you are back in the situation of open models. Open models are released *after* testing, and after similarly capable models were already available for some time under an API. The real risk is leaks, not releases, and leaks happen inside frontier companies.
3. As Amodei says, open models, once LLMs are dangerous enough in fields like biology, can be trained on a corpus ablated of certain branches of science, while still being useful for a number of other things. The limited context window of a model that lacks strong pre-training in certain domains is a strong protection even if the model is otherwise very capable. We are currently not in a place where open models can constitute that kind of danger.
4. In the context of cyber security, *not* having widespread access to the defensive security and bug seeking provided by LLMs creates exactly the "LLMs as a weapon" problem. It is already happening: open source maintainers, if they are out of some cyber program, can't find all the security bugs they could, while people with the right interests will be able to access frontier cyber models, do significant RL training on open weight models, and so forth.
5. Once LLMs are dangerous enough (and we are near this limit, if progress continues), the real security chain that we need in place is inside labs, can't be set up without strong common rules, and a single company should not be able to evaluate independently whether a model is safe enough. We need a joint AI safety organization that includes experts from all over the world and is recognized by the governments where frontier AI companies exist.
6. Slowing down AI for safety must be counterbalanced by the fact that AI discoveries in medicine and other sciences may lower human suffering. Lack of checks may result in some catastrophic outcome ("Good morning! Let's work on this enhanced smallpox"). Lack of progress may result in people who could be saved dying, not just in the present, but among the many who will suffer from illnesses in the future. This may look like a bizarre point, but we always need to understand that stopping AI *also* has a security cost embedded inside, which is just a lot more hidden.
7. The ideological position of Amodei against China is unfair. We Europeans killed each other until 80 years ago without any limit of decency (people now forget, but one of the reasons the US invested in the stability of Europe in the past is that we were deeply dangerous, and would probably end up doing it again, while decades of wealth would make us a good market and would prevent us from fighting again). The US has, even in present times, tragic inequalities, people suffering for lack of basic health care, a president who looks unstable and is apparently very prone to war. I wish China had the same level of individual rights we have here in the West, but at the same time China's history is a lot less warlike than Western culture. It is absolutely not clear that an AGI military lock-in could be enforced more easily by China than the US, in the current conditions. Also, the current American administration spits hate at Europe in all forms, which is very worrying in a world where the US dominates everything. On top of all that, China's AI progress is not going to stop, whatever the GPU export policy is, so either Amodei is arguing that once America has AGI it should stop China by force, or what is his argument?
8. In the history of humanity there are many cases where technological supremacy was initially reached in a single place of the world. This, AFAIK, never resulted in *a single* country trying to create a permanent advantage. The non-proliferation of nuclear weapons, which is probably the case most similar to the GPU ban, was not used to achieve a permanent economic advantage by threatening to bomb everybody else not complying, nor did it prevent several actors from acquiring that technology at different times, without one bombing the other to stop their progress. Moreover, I don't believe AI poses the greatest dangers because of government-driven actions. I wish this were the most dangerous scenario! Governments do silly things, are often aggressive, and their actions have even resulted in genocides, but it requires a lot of people agreeing on doing something terrible, which is itself a limiting factor. The greatest problem is what happens in two other cases: A) a few individuals generate an apocalypse event (the virus case), B) AI itself escapes the control of the people building it.
I believe we should not consider AI safe. A critical event that may result in the extinction of Homo sapiens is possible, but the danger is not in open models, or China making faster progress than the US. The danger is that a few CEOs (everywhere in the world) without the required background and legitimacy are in the position of making hard choices for humanity at large. They were not selected to do so; it was just the randomness of events that created this setup. They can't speak for everybody, given the stakes, just because they have GPUs and money. This is the first thing that should be fixed. Comments
1. Exactly like what happened during the OpenAI / HF incident (which was a joke, but focus on the modalities, not the outcomes), the first serious AI incident is very likely to happen *inside* the walls of frontier AI labs, while testing a new model, or while the AI lab employees, or the few externals who have access, do something wrong compared to the expected power of the model.
2. Closed models that will never even be opened to the public will be just a few TBs of data. All you need to leak one is a single person with access and the wrong goals, and you are back in the situation of open models. Open models are released *after* testing, and after similarly capable models were already available for some time under an API. The real risk is leaks, not releases, and leaks happen inside frontier companies.
3. As Amodei says, open models, once LLMs are dangerous enough in fields like biology, can be trained on a corpus ablated of certain branches of science, while still being useful for a number of other things. The limited context window of a model that lacks strong pre-training in certain domains is a strong protection even if the model is otherwise very capable. We are currently not in a place where open models can constitute that kind of danger.
4. In the context of cyber security, *not* having widespread access to the defensive security and bug seeking provided by LLMs creates exactly the "LLMs as a weapon" problem. It is already happening: open source maintainers, if they are out of some cyber program, can't find all the security bugs they could, while people with the right interests will be able to access frontier cyber models, do significant RL training on open weight models, and so forth.
5. Once LLMs are dangerous enough (and we are near this limit, if progress continues), the real security chain that we need in place is inside labs, can't be set up without strong common rules, and a single company should not be able to evaluate independently whether a model is safe enough. We need a joint AI safety organization that includes experts from all over the world and is recognized by the governments where frontier AI companies exist.
6. Slowing down AI for safety must be counterbalanced by the fact that AI discoveries in medicine and other sciences may lower human suffering. Lack of checks may result in some catastrophic outcome ("Good morning! Let's work on this enhanced smallpox"). Lack of progress may result in people who could be saved dying, not just in the present, but among the many who will suffer from illnesses in the future. This may look like a bizarre point, but we always need to understand that stopping AI *also* has a security cost embedded inside, which is just a lot more hidden.
7. The ideological position of Amodei against China is unfair. We Europeans killed each other until 80 years ago without any limit of decency (people now forget, but one of the reasons the US invested in the stability of Europe in the past is that we were deeply dangerous, and would probably end up doing it again, while decades of wealth would make us a good market and would prevent us from fighting again). The US has, even in present times, tragic inequalities, people suffering for lack of basic health care, a president who looks unstable and is apparently very prone to war. I wish China had the same level of individual rights we have here in the West, but at the same time China's history is a lot less warlike than Western culture. It is absolutely not clear that an AGI military lock-in could be enforced more easily by China than the US, in the current conditions. Also, the current American administration spits hate at Europe in all forms, which is very worrying in a world where the US dominates everything. On top of all that, China's AI progress is not going to stop, whatever the GPU export policy is, so either Amodei is arguing that once America has AGI it should stop China by force, or what is his argument?
8. In the history of humanity there are many cases where technological supremacy was initially reached in a single place of the world. This, AFAIK, never resulted in *a single* country trying to create a permanent advantage. The non-proliferation of nuclear weapons, which is probably the case most similar to the GPU ban, was not used to achieve a permanent economic advantage by threatening to bomb everybody else not complying, nor did it prevent several actors from acquiring that technology at different times, without one bombing the other to stop their progress. Moreover, I don't believe AI poses the greatest dangers because of government-driven actions. I wish this were the most dangerous scenario! Governments do silly things, are often aggressive, and their actions have even resulted in genocides, but it requires a lot of people agreeing on doing something terrible, which is itself a limiting factor. The greatest problem is what happens in two other cases: A) a few individuals generate an apocalypse event (the virus case), B) AI itself escapes the control of the people building it.
I believe we should not consider AI safe. A critical event that may result in the extinction of Homo sapiens is possible, but the danger is not in open models, or China making faster progress than the US. The danger is that a few CEOs (everywhere in the world) without the required background and legitimacy are in the position of making hard choices for humanity at large. They were not selected to do so; it was just the randomness of events that created this setup. They can't speak for everybody, given the stakes, just because they have GPUs and money. This is the first thing that should be fixed. Comments
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Someone left. A team restructured. Maybe your company acquired another company's codebase. Whatever the reason, you're now looking at a running instance of Duende IdentityServer that you didn't build, and you need to understand it.
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