u/nkondratyk93

Tuesday's Intuit announcement (3,000 cut, 17% of workforce, "reduce complexity to focus on AI") is the latest in a pattern I keep noticing across industries. Klarna in 2024, Duolingo in 2025, IBM later in 2025, now Intuit. Every one of these memos names what got cut, what gets refocused, what stays. None of them name who answers when the AI is wrong.

Genuine question for the community - this isn't specific to software PM. Construction PMs whose AI tools route work orders. Banking PMs whose AI tools approve loans. Healthcare PMs whose AI tools triage referrals. Manufacturing PMs whose AI tools schedule lines. Anyone whose workflow has been partially or fully replaced by an AI system over the last two years.

When something the AI does goes wrong - bad routing, bad approval, bad triage, bad scheduling, bad customer-facing statement - is there a named human on your team or org whose job description explicitly includes "answers when this AI is wrong"? Or is the accountability implicit, defaulted, or honestly just nobody's job?

Not looking for the right answer. Looking for what people actually do. Curious whether the pattern is industry-specific or universal.

If you have a clean version of this on your team, I'd love to know what the policy or doc actually says. If you don't, also useful - want to see if the gap I'm seeing in the public announcements maps to what's actually happening inside orgs.

The piece sketches three tiers. Admin PMs are the squeezed group (hiring down ~35%). Process-integrators are shifting under their feet. Strategic PMs at the top of the curve are gaining roughly 30% in salary share.

The framework reads right to me on paper. I'm more curious what it feels like inside the day-to-day on teams that have already deployed something past the demo stage.

A few things I keep noticing in my own work. The unit of PM work on those workflows isn't really a task anymore - it's more like the service-level commitment the agent owes the team (response time, escalation path, things breaking when load doubles). Honestly half the value is just being the person who can answer "what did this cost us last quarter, and what did it return" in a sentence.

(Salesforce putting $300M of Anthropic token usage on its 2026 books last week is a small parenthetical here, not the lead - just felt like it made the spend ownership question stop being theoretical.)

Curious about other industries too - this is way more than software PM. For folks in construction, banking, healthcare, ops: does the tier shift match what you're seeing? Or is the framework mostly a tech-PM phenomenon dressed up as a universal one?

honestly i'm sitting with this on a saturday morning and i don't have a clean answer.

procurement at my org approved chatgpt for "work use" nine months ago. friday openai shipped chatgpt personal finance, which connects to 12,000+ banks and reads spending, portfolio data, subscriptions. same login your engineers use to draft project work.

so the procurement record says one thing about scope. the user authorized a second scope inside their personal session. both are legitimate. but the procurement template was written when "approved tool" meant a single static scope.

i'm not arguing this needs to be blocked. user owns their personal authorization. but the artifact next to the procurement record - the one that names what data the model sees, in what session, on whose behalf - doesn't exist in my folder. probably not in yours either.

curious how your tool-policy template handles this, especially in non-software industries where the same pattern is showing up in word + legal agents this week. is this a procurement question, a security review question, or just unowned?

honestly thinking about this after the news today. I've signed a few business cases for AI tools across different orgs (had construction PMO work + finance ops PM work in there too, not just software) and the section that's never on the template is what the org commits to doing once productivity per head goes up.

the agent section is there. the throughput projections are in there. and there's a productivity gain section, usually with someone's confidence interval. but the bit about what the org commits to doing with the freed capacity - whether it's net-new work, faster cycles, or steady headcount - never makes the template.

curious if anyone here uses a template that names it, or if you've seen the question handled in non-tech orgs (construction PMOs, healthcare program docs) and what the framing looks like there.

CNN ran a piece this weekend saying AI isn't displacing PMs, it's transforming the work itself. HBR + BCG had a similar piece last week asking who owns the agents your team is running.

I'm curious where this lands for folks here, because the audience here isn't just software PMs - construction, banking, healthcare, manufacturing all run agents now in different shapes.

For me, the change that snuck up was the writing. I write more than I did a year ago. Different audience too. The tickets I write for the people on my team look different from the ones I write for the automation that sits next to them.

What's the part of your PM job that already looks different from a year ago? Curious whether it's the writing, the scoping, the rollback calls, or something I'm not seeing from inside software.

KPMG just published a survey of 306 Canadian executives. 39% expect AI agents leading project management for their teams in 2-3 years; 66% are already moving to an integrated AI-human workforce.

Setting aside the obvious "is the timeline real" question, the agile-side question I keep coming back to is the ceremonies. What's already changed for you in the last 12 months on standups, sprint reviews, retros, planning? In particular, what's the part of the ceremony you used to drive that an agent stack now drafts or summarizes before the meeting starts? And what part of the ceremony did you protect from automation on purpose?

Asking from inside the seat. The day-level shift is harder to map to executive abstractions than I expected.

Five intelligence agencies just jointly published ‘Careful Adoption of Agentic AI Services’ (Apr 30 / May 1). First coordinated international doctrine on autonomous agent deployment. Core message: deploy incrementally and assume agents will misbehave; prioritize reversibility over efficiency. Five named risk categories: privilege creep, design and config flaws, behavioral unpredictability, structural cascade failures, interconnected agent network failures. All five are observable. They produce a signal you can route.

Genuinely curious how PMs running AI-assisted workflows in any industry (construction, banking, healthcare, telecom, manufacturing, IT delivery) are translating this into a project-level check. Specifically: there’s a sixth category the doctrine doesn’t name that I think is breaking sprint dashboards weekly. Silent failure. The agent runs, returns nothing, and the system reports complete with no error.

What does your sprint or project-completion check look like when an agent’s in the loop, or is it still ‘task marked done in the system’?

Boris Cherny posted today on X: in the last 30 days, 100% of his contributions to Claude Code were written by Claude Code itself - 259 PRs, 497 commits, 40k lines added, 38k removed. The head of the team no longer writes code.

Engineering reading: "AI dev productivity is real."

The leadership reading is harder and I think more interesting. The senior PM's daily work product is shifting from "ship the artifact" (PRDs, launch plans) to "make the call" (what to build, what to kill, what to ship behind a flag).

For senior PMs here - is your work product still the artifact, or already the call, or some mix? And if it's the call, how do you make it visible in promo packets and performance reviews that were built around shipped artifacts? Genuinely curious what the split looks like at different companies.

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Curious how teams here are thinking about agents now that Microsoft shipped Agent 365 to GA on May 1. The bundle gives every agent an Entra identity and hooks Defender for the audit trail by default. Purview manages data scope and Intune handles device policy. Most teams have been figuring this out as an in-house project last quarter, and Microsoft just turned it into configuration.

For PMs whose org isn't on M365 E7 (most of us), the question changed from "is this worth building" to "how does our equivalent stack up against a bundled SKU." Not asking about Microsoft specifically. Asking what fields you'd want a directory entry for an AI agent to have. Manager-of-record is the obvious one. The autonomy level (read / draft / commit) is another.

What's everyone else putting in the equivalent of an agent's HR record? We're filling out our own and I want to know what we're forgetting.

Quick context. Julie Zhuo published on Lenny's newsletter this week arguing the same leadership skills that work for managing people apply to managing AI. I think she's right about most of it but there's one instinct I keep catching myself reaching for that doesn't transfer.

It's the "you get what I'm asking for, run with it" shorthand you'd use with a senior person you've worked with for months. With AI agents that same shorthand ships the wrong thing fast because the agent doesn't push back the way a colleague would. The relationship is doing work you didn't notice it was doing.

Honestly curious if other PMs across industries have noticed the same. Not looking for tool recommendations - looking for the moment you noticed an instinct misfiring. Which people-management habit have you actively had to retrain when working with AI tools or agents in your delivery process?

something i ran into this week that i think shows up across industries, not just software.

a vendor we already pay for shipped a feature that lets their AI agents act inside our internal tools - send messages, schedule things, write to records. free for a few days, then billed per action. the agent is already deployed because we already pay for the parent product. the only thing that changes next week is the meter starts.

the part that surprised me. when i asked who in our org authorized this scope, the answer was "the buyer accepted the terms when we procured the parent product 14 months ago." that authorization predates the agent existing. nobody at that meeting was knowingly authorizing an AI agent to act inside our channels.

i think this is the structural pattern. enterprise click-through ≠ scope authorization for agents acting in tools. doesn't matter if you're in construction, banking, healthcare, retail. most orgs have at least one procured tool that came with agentic capabilities they didn't separately scope.

what i'm trying to figure out. who in your team would run the evaluation if the deadline were six days away? PM? security? legal? the person who signed the original contract? i can see arguments for each. honestly curious how your org would actually decide it, especially if you're outside software.

Genuine question for the room - cross-industry, not just software PMs.

We've all seen the contracts get signed. The CIO bought the tool. The VP ships the platform. Six months later somebody in finance asks where the productivity number went.

In every org I've talked to lately, that question lands on a person who legitimately doesn't have the data. Their dashboards measure deployment, not behavior change. Whether the team's daily ritual actually shifted is somebody else's job. Except nobody on the org chart actually has that job.

I don't think this is software-specific. Construction is buying AI estimators. Banking is buying AI underwriting. Healthcare is buying AI documentation. Same shape: tool lands, workflow may or may not change, nobody signs for the gap.

For the PMs here - when your org bought a major AI tool in the last 6 months:

- who owns whether the work actually changed?

- is it written into anyone's role?

- if not, who do you think SHOULD own it?

Not asking rhetorically, I'm trying to map who's solving this and who's still in the "tbd" column. Honest answers welcome including "nobody, and we're hoping it works out."

happened in my industry recently. two vendors we evaluate against each other shipped competing flagship products one day apart. one was the established proprietary offering with an enterprise SLA. one was a newer open-source alternative our internal team could self-host.

the procurement call is on my desk by friday and i realized our usual deck was a cost comparison and not much else.

i ended up writing five rows on a page that i think actually decide it:

1. capability parity - run both against three of our recurring workflows for a week and document where output diverges.

2. total cost of ownership instead of sticker price. self-hosting brings ops headcount, monitoring, ongoing patching the vendor deck never models.

3. data sovereignty. self-hosted gets you sovereignty by inspection (you audit the path); proprietary with residency guarantees gets you sovereignty by contract (you sue if breached). different standards.

4. vendor lock-in shape. open-source flexibility comes with operational debt; proprietary reliability comes with roadmap dependency. both lock you in. pick the one your team can absorb.

5. enterprise support tier. when the system breaks at 3am, who picks up? this row never makes the deck and always shows up in the postmortem.

curious which of these gets weighted heaviest in your industry, and which tends to get under-weighted until something breaks. seen this play out the same way across construction, banking, healthcare, software shops. wondering if it is the same in yours.