u/oren_k9

For those of you who have worked in software engineering management roles, like team lead, group manager, and so on, and then went back to writing code either part time or full time:

Do you feel that coding with AI has affected the way you manage people?

The reason I’m asking is this:

When I code with AI, it sometimes feels like I’m managing agents in extreme micromanagement mode. No compromises, no mercy, no shame in asking dumb questions, and sometimes maybe not using the nicest language either.

Do you feel like you’re able to keep that completely separate when managing human developers? Or do you feel that some of the way you manage AI agents leaks into the way you manage people, even a little?

For those of you who have worked in software engineering management roles, like team lead, group manager, and so on, and then went back to writing code either part time or full time:

Do you feel that coding with AI has affected the way you manage people?

The reason I’m asking is this:

When I code with AI, it sometimes feels like I’m managing agents in extreme micromanagement mode. No compromises, no mercy, no shame in asking dumb questions, and sometimes maybe not using the nicest language either.

Do you feel like you’re able to keep that completely separate when managing human developers? Or do you feel that some of the way you manage AI agents leaks into the way you manage people, even a little?

Saw a post from a senior tech recruiter on why "Director" hiring fundamentally changed in 2026 - sharing because it matches what I'm seeing:

A senior tech recruiter posted something the other day that's been rattling around in my head, and I think it's worth sharing here because the pattern she described matches what I'm seeing across my own network.

Her core thesis: we're still hiring directors and group managers like it's 2024, and that's becoming a real problem.

The "classic" director - the one whose job is to manage large teams, run cadence meetings, set policy, build slide decks, and approve reports up the chain - is increasingly the wrong hire. What companies actually need is someone fundamentally different: a hands-on leader who genuinely understands AI at an implementation level and basically runs a small human team alongside a "team" of AI agents doing what used to require a whole department.

She backed it up with a few data points:

LinkedIn's Economic Graph shows roughly a 35% jump in demand for technical skills at the director / group-manager level, AI-fluent managers reportedly get about 2.5x more headhunter visibility, and middle management has shrunk roughly 20% in the last two years as AI flattens orgs.

Take all of this with the usual grain of recruiter-data salt - the 2.5x number is obviously LinkedIn-platform data with some recency bias baked in - but the direction feels right. Every founder I've talked to in the last six months is essentially asking the same question:

why am I paying someone $250K+ to coordinate when the coordination itself is increasingly automatable?

She also pointed out something I hadn't fully internalized:

even companies that DO get the shift fall into what she calls the "DIY trap":

They post the role on job boards, get a flood of applicants, and miss the actual best candidates entirely - because per LinkedIn Talent Solutions and Gartner, around 75% of high-performing talent are passive candidates who aren't browsing job boards in the first place. Hiring at this level almost always means going to find someone, not waiting for them to apply.

The part I actually found useful was her breakdown of what these recruiters are now looking for in the new "Hands-on Director" profile.

Six traits, and they map pretty well to what I've seen actually work in practice:

- IC Leader, not just a manager. They write their own PRDs (with AI), join architecture conversations, and don't just rubber-stamp work coming up the chain. If they can't ship anything themselves, they're not a fit.

- Hands-on with AI and automation. Not "I've used ChatGPT." Actually deploys AI agents, builds automated workflows end-to-end, and gets the kind of output from a 4-person team that used to require 20+.

- Edge-case problem solving. As AI eats the predictable 80%, the manager's value lives in the hard problems the machine can't solve yet. If most of their experience is running the predictable stuff, that's exactly the part getting commoditized.

- Short chain of command, willing to get their hands dirty. Looks at raw data directly instead of going through analysts. Dives into architecture decisions. In some cases does actual code review. The director who only consumes pre-digested summaries is the wrong hire now.

- Conducting a human-AI hybrid team. Knowing where humans belong in the loop and where they don't. This is honestly the skill I see people get wrong most often - they either over-automate and ship garbage, or under-automate and stay slow.

- Ego-aside leadership. Comfortable managing a small, capable team instead of empire-building. Measured by impact, not headcount. This is the cultural shift that probably kills the most director-level hires - people who came up in the "I manage 40 people" era really struggle to optimize for output rather than org-chart size.

The bigger takeaway for anyone building right now: if you're hiring a director or group manager and your JD still reads like 2022 (heavy on "stakeholder management," "team leadership," "reporting cadence"), you're going to hire someone who looks great on paper and gets passed by the actual best operators in your space.

Curious if anyone else is seeing this play out - especially anyone who's recently hired (or interviewed for) this kind of role.

Are candidates who fit this profile actually showing up, or is the pool still mostly the older model?

Saw a post from a senior tech recruiter on why "Director" hiring fundamentally changed in 2026 - sharing because it matches what I'm seeing:

A senior tech recruiter posted something the other day that's been rattling around in my head, and I think it's worth sharing here because the pattern she described matches what I'm seeing across my own network.

Her core thesis: we're still hiring directors and group managers like it's 2024, and that's becoming a real problem.
The "classic" director - the one whose job is to manage large teams, run cadence meetings, set policy, build slide decks, and approve reports up the chain - is increasingly the wrong hire. What companies actually need is someone fundamentally different: a hands-on leader who genuinely understands AI at an implementation level and basically runs a small human team alongside a "team" of AI agents doing what used to require a whole department.

She backed it up with a few data points:
LinkedIn's Economic Graph shows roughly a 35% jump in demand for technical skills at the director / group-manager level, AI-fluent managers reportedly get about 2.5x more headhunter visibility, and middle management has shrunk roughly 20% in the last two years as AI flattens orgs.
Take all of this with the usual grain of recruiter-data salt - the 2.5x number is obviously LinkedIn-platform data with some recency bias baked in - but the direction feels right. Every founder I've talked to in the last six months is essentially asking the same question:
why am I paying someone $250K+ to coordinate when the coordination itself is increasingly automatable?

She also pointed out something I hadn't fully internalized:
even companies that DO get the shift fall into what she calls the "DIY trap":
They post the role on job boards, get a flood of applicants, and miss the actual best candidates entirely - because per LinkedIn Talent Solutions and Gartner, around 75% of high-performing talent are passive candidates who aren't browsing job boards in the first place. Hiring at this level almost always means going to find someone, not waiting for them to apply.

The part I actually found useful was her breakdown of what these recruiters are now looking for in the new "Hands-on Director" profile.
Six traits, and they map pretty well to what I've seen actually work in practice:

- IC Leader, not just a manager. They write their own PRDs (with AI), join architecture conversations, and don't just rubber-stamp work coming up the chain. If they can't ship anything themselves, they're not a fit.

- Hands-on with AI and automation. Not "I've used ChatGPT." Actually deploys AI agents, builds automated workflows end-to-end, and gets the kind of output from a 4-person team that used to require 20+.

- Edge-case problem solving. As AI eats the predictable 80%, the manager's value lives in the hard problems the machine can't solve yet. If most of their experience is running the predictable stuff, that's exactly the part getting commoditized.

- Short chain of command, willing to get their hands dirty. Looks at raw data directly instead of going through analysts. Dives into architecture decisions. In some cases does actual code review. The director who only consumes pre-digested summaries is the wrong hire now.

- Conducting a human-AI hybrid team. Knowing where humans belong in the loop and where they don't. This is honestly the skill I see people get wrong most often - they either over-automate and ship garbage, or under-automate and stay slow.

- Ego-aside leadership. Comfortable managing a small, capable team instead of empire-building. Measured by impact, not headcount. This is the cultural shift that probably kills the most director-level hires - people who came up in the "I manage 40 people" era really struggle to optimize for output rather than org-chart size.

The bigger takeaway for anyone building right now: if you're hiring a director or group manager and your JD still reads like 2022 (heavy on "stakeholder management," "team leadership," "reporting cadence"), you're going to hire someone who looks great on paper and gets passed by the actual best operators in your space.

Curious if anyone else is seeing this play out - especially anyone who's recently hired (or interviewed for) this kind of role.
Are candidates who fit this profile actually showing up, or is the pool still mostly the older model?

as Solo Founders, building their own product, I really wonder -
How large is your code base (lines of code)?
- up to 100K LoC
- 100K-500K LoC
- 500K-1M LoC
- 1M+ LoC