r/EngineeringManagers

If the job of software engineering is to deliver business outcomes, is business going to care less about the code?

Hear me out.

We all know that business has never cared about the code. What they want to care about is the derivative of the code which in most of the cases is related to money.

The reason they have had to actually care about the code is the cost of maintenance. If the code is bad, managing change is expensive.

Now, with agentic engineering industrializing the SDLC, the code itself is becoming less important, if it can be reliably generated from another substrate. This substrate is what can be loosely defined as the “business know-how, processes and workflows”.

So my question to you folks is, do you believe business is going to stop caring about the code entirely and shift its focus elsewhere?

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u/Sad-CTO — 9 hours ago
▲ 6 r/EngineeringManagers+1 crossposts

Engineering managers: how do you prevent valuable Slack discussions from disappearing?

In my team I notice senior engineers write detailed explanations in Slack, but months later nobody can find them. Curious how others solve this.

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u/AsparagusOk893 — 12 hours ago

Is anyone else’s company automating software development this aggressively with AI?

After the arrival of Claude, my company has started building a lot of AI “skills” to automate the software development lifecycle.

Some of the skills our CTO has created include:
Jira Ticket Creator
Batch Ticket Analyzer
Interactive Tickets
Auto QA
Manual QA Assistant

For example, the Batch Ticket skill reads a Jira ticket, searches across all of our repositories, identifies the likely root cause, and prepares an implementation plan.

Once the code is implemented, it automatically triggers Auto QA, which runs Playwright tests, attaches the test evidence to the Jira ticket, creates a PR against the target branch, and updates the ticket status.

Lately, management has been saying that developers won’t be writing much code in the future—they’ll mainly review AI-generated code.

To be honest, this makes me a little concerned. It feels like they’re gradually building an AI-driven workflow that automates more and more of the engineering process, and I can’t help wondering whether this could eventually lead to layoffs.

Is anyone else seeing something similar at their company? Is your engineering team building internal AI agents or workflows like this, or is this still uncommon where you work?

I’d be interested to hear what your company is doing and how your developers feel about it.

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u/Pretty_Classic_5058 — 1 day ago

What's the biggest reason a sprint slips even when Jira looks healthy?

I've noticed that teams can have a sprint where most work is still marked "In Progress" or appears to be moving, yet the sprint slips near the end.

In your experience, what's usually happening behind the scenes?

Is it dependencies, QA, code reviews, environments, changing priorities, CI/CD, or something else entirely?

I'm interested in hearing real examples from engineering teams. What patterns have you seen?

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Thinking of killing our team’s knowledge sharing meetings

Hello,

I’m the manager of a software engineering team and I’ve scheduled a weekly call (~45min) with the team so that everybody can share what they’re working on, debate about technical challenges, discuss new technologies and so on.

Obviously I thought it would be a good initiative in the team and would bring people together and help spread knowledge.

I was flat out wrong and nobody is talking and they don’t even ask questions or interact with what I’m saying (expect for one person).

I’m the only one sharing things, and if I don’t share anything, nobody speaks and we end up cancelling the meeting.

Have you ever experience something similar ?

Most of my team members are working on different topics but I thought it would be interesting to share the knowledge.

If you have any recommandation, thanks !

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u/Cyliad — 2 days ago

Does anyone else see failed CI builds become a game of pass-the-parcel?

At my work, the fix usually isn't the slow part.

The slow part is figuring out whether it's the application, the pipeline, a flaky test, a dependency, or some cloud/platform issue. Developers end up digging through thousands of log lines or waiting for someone from DevOps or Platform to weigh in.

I'm curious how other engineering teams handle this.

Do your developers own CI failures end-to-end, or do they regularly bounce between engineering, platform, and cloud teams before someone finds the real cause?

Has anyone found a process that consistently reduces that back-and-forth?

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u/michaelmanleyhypley — 1 day ago

How do you track team members progress?

Every month I ask my reportees to prepare a document describing what they did in the last one month and I provide them feedback. This helps me and team member with the data when we do performance review half yearly.

I want to understand how others are doing? If my approach has any cons?

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u/Round_Chipmunk_ — 2 days ago
▲ 304 r/EngineeringManagers+12 crossposts

CTOs, engineering managers, and staff engineers are rushing to deploy autonomous AI agents across their businesses – either through their own volition or because of the clamor of demand from rank-and-file workers. However, they should think twice, a new study shows.

Enterprise large language model (LLM) agents are likely leaking company secrets, and throwing more compute at the problem is only making it worse, the study finds.

In part, that’s because of the AI’s ability to retrieve and synthesize vast amounts of internal data, from Slack messages to board transcripts, to automate tasks. By gathering that information, they also create issues with contextual integrity.

When retrieving dense corporate data, these agents routinely fail to disentangle essential task data from sensitive, contextually inappropriate information. Higher task completion rates often directly correlate with increased privacy violations.

Read the full story: https://leaddev.com/ai/frontier-ai-models-haemorrhage-sensitive-data

u/OfficialLeadDev — 3 days ago

the status updates became the actual work and I’m not sure how to stop it

Spent most of friday writing the weekly update for leadership. Again. Pulled the Jira stuff, chased three people on Slack to find out where things actually landed, rewrote it twice so it'd read right to the VP. Couple hours gone. The thing it was reporting on didn't take much longer than that to build.
And it's never just once. Something slips, someone upstairs asks for a status, and producing the status eats the time we'd have used to unblock the actual thing. At some point the updates kind of became the work.

What I can't figure out is whether that's me being bad at this or just the job now. Half of me wants to make it vanish - one doc people can read on their own time, kill the syncs. But I think the reason they keep asking is they don't really trust the system to tell them, and a tidier report doesn't fix that.

So for people who've been at this longer: is it just overhead you've made peace with, or did something actually change it? And the honest one - when you have to show leadership your team was worth it, what do you reach for?

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u/Conscious-Fact9532 — 2 days ago

Gut check this for me - toxic or not?

I moved to a startup fairly recently as an engineering manager, leaving a stable job to do it. During interviews I did my diligence — asked about leadership, product, culture, remote setup — and it read as a good fit with a boss I'd want to work for.

Since starting, a few things haven't matched what I was told. The remote policy is changing, and the product area I was hired to run wasn't as real as it sounded.

But the bigger issue is cultural. There's a persistent lack of trust in the engineers. Communication from the top is thin. Strong, experienced teams get overruled on technical decisions with regularity. And effectively no one below the exec level owns a decision — people make a safe call, then route it upward for approval, so there's constant churn and rework.

The part that really shifted my read: a major product direction was set unilaterally at the top, with essentially no engineering involvement, and it's being celebrated by the business. I get why from a business angle — but the teams now have no clear sense of what role they play. And the execution quality coming out of that process is rough: little to no testing, shortcuts everywhere, no real engineering discipline, and things break constantly as a result.

When I raised career growth with my manager, the implication I took away was that it's contingent on nights and weekends.

The throughline is that the engineering leadership and culture-building I was hired for don't actually seem wanted. There's little appetite for building sustainable process or a real engineering org. I feel less like a leader and more like a senior IC who also writes performance reviews.

Is this just normal startup stuff, or did I misjudge this?

Anonymized with Claude, my apologies for clanker words.

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u/throaway101919 — 2 days ago

Is it a myth that tech people can’t think from a business perspective?

I’ve often heard people say that engineers and developers are great at solving technical problems but struggle to think from a business perspective.
Do you think this is just a stereotype, or is there some truth to it?

Why do you think this perception exists?

Have you worked with technical people who also had strong business instincts?

If you’re an engineer, how did you develop your business mindset?

I’m curious to hear perspectives from founders, engineers, product managers, and anyone who has worked closely with technical teams.

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u/Pretty_Classic_5058 — 3 days ago

You don't need a roadmap to start lean. You need a first problem to fix.

Something I see a lot with people (usually newer plant managers or founders) who are excited about lean and want to do it "right" ... they try to build the master plan first. Full current-state map, future-state map, multi-year roadmap, phase gates.... the works. Then six weeks later nothing has actually changed on the floor because they are still planning!

I made this mistake myself early on. Thought I needed a complete, defensible plan before I could touch anything. Turns out that's backwards, at least for how you start.

Here's the thing about problems on your floor (or in your process, if you're not literally manufacturing something): they are not evenly distributed. Picture a pyramid. Big wide base of simple, obvious problems: a tool that's never in the same place twice, a form that gets filled out three different ways, a handoff nobody owns. Small tip of genuinely hard, cross-functional, needs-real-analysis problems.

Most people start planning for the tip of the pyramid. You should start by clearing the base. It's not glamorous. It won't get you a case study. But it does two things a fancy roadmap doesn't: it gets you a fast, visible win, and it gets your people used to the idea that they're allowed to change how things work. That second part matters more than people think: a workforce that's never been asked to fix anything doesn't magically start solving problems just because you handed them a roadmap. They start because you let them fix something small and it stuck.

You don't need experts to start this way either. Lean, at the start, is closer to systematic common sense applied consistently than it is to a body of certified knowledge. Certifications and designations rarely matter... the deep tools matter later. At the start, they are often just an excuse to delay.

One caveat that I think matters and doesn't get said enough: this "start small, don't overplan" advice is for getting moving. It is not permission to stay tactical forever. At some point you do need the bigger picture. Otherwise you get a pile of disconnected local improvements that don't add up to anything at the system level. But that's a problem for month six, not week one.

For anyone who tried to build the full roadmap before doing anything, how'd that go? Did it ever actually launch, or did it die in the planning phase?

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u/Informal-Tutor-8153 — 2 days ago

We shipped 270 tasks in 7 days with just 3 engineers.

This is what real Agentic Engineering Loop looks like!

270 tasks in 1 week, just 3 engineers. Many of these tasks are very complex.

My traditional engineering mind would never have imagined the scale at which we're moving now.

I managed teams where 10 engineers would get 20-30 tasks done and still have a lot of spill over. We are now able to do literally 10x of that, and we are just getting started.

The responsibility of the team now is moving from doing the tasks to building the loop that gets the tasks done. There has been a big shift even for us, a team who has been at the edge of Agentic Engineering.

We are currently at a place where 70%+ of our tasks get done mostly autonomously, we aim to push that to 95% soon and also double the number of tasks the system can process.

It's systems engineering at the end, but with agents and humans as components in the pipeline.

Ask me anything about our stack, workflows, orchestration, review process, failures, costs, metrics, or how we got here. If it's useful to other engineers, I'll answer as openly as I can.

https://preview.redd.it/bre880sevtah1.png?width=371&format=png&auto=webp&s=805f0baa11c5116f05946cf98c9cc4b9f4f07383

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u/prasadpilla — 3 days ago
▲ 1 r/EngineeringManagers+2 crossposts

Understanding the Capabilities and Responsibilities of Using FEA

Several years ago, the powerful computer simulation tool Finite Element Analysis (FEA) was primarily used in the aerospace and nuclear industries. Over the years, the capability was made available thru timesharing and then finally on standalone systems. Today, we have access to this powerful tool through integrated CAD programs like INVENTOR and SOLIDWORKS. The is great. When designing we can access deflection and stress contour plots instantaneously. However, with this great capability comes a responsibility to use it properly.

Capability – How did we reach this point? To answer this question, I think it helps to review the historical record of stress analysis methods and how these were developed. I think an early turning point in stress analysis was the development of the Euler – Bernoulli equation of the Flexural Formula which occurred in the year 1750. We know this as stress = Mc/I. This method equates the beam deflection to a radius. Integration of this foundational equation, we then arrive at the Flexural Formula. From this point, many various conditions of support and load application have been developed, all based on the concept of beam theory.

Many Engineering designs can still be solved using basic beam theory. The I beam in the basement of your house is likely selected this way. Using basic beam theory end supports and a center support located at the round column, together with the floor above “worst case” floor loading; the beam can be safely selected. This is great for a basic problem like this application. But what above short deep beams that may not conform to the basic assumptions of beam theory.

In the early years of 1900, the Russian Scientist / Engineer Stephen Timoshenko laid down the fundamental equations for a new stress analysis method called Theory of Elasticity. This method looked at the same beam using a differential equation element for the deflection rather than the entire beam shape following a radius. For deeper beams, we could apply this method to pick up the web compression and shear deflection that exists. However, I find the math gets so complicated for solving simple 2D structures that it makes this method impractical for design Engineering. Nevertheless, these basic equations have led us to many plate and shell equations and other important findings in Engineering Mechanics.

The solution we now have available for today’s Engineering of structures is Finite Element Analysis (FEA). This method is based on matrix algebra and solving massive matrixes. The size of these matrixes makes this approach a computer based solution. The method includes various element types and has applications in stress, heat transfer, fluid dynamics, and advanced methods that combine all of the above.  As noted above, the method is integrated into CAD systems making this tool available to generate output very quickly. Along with this powerful capability, we have a responsibility to be sure this data is accurate.

Responsibilities – Using FEA requires an accurate model that represents the real world. Here are a few tips that should be considered. Note this is only a brief list, but it is a starting point.

1)    Boundary Constraints – Boundary constraints must be accurate. If possible, I like to use the boundary constraints to just keep the model stable. If you use this approach accurately, the solution phase should be left with little residual reaction at these locations.

2)    Peak Stress Levels at a Boundary Constraint Location – If you see peak stress levels at a boundary constraint location, this is a red flag. Resulting stress could be incorrect.  

3)    Avoid Loading Models with a Single Force at a Single Node – This is likely excessively deflecting the corresponding corner of the element. Look at the part you are modelling. The loading likely comes into the part as a pressure and not a point load.

4)    Verify Your Results – Use another method to confirm the FEA output. If it is a pressure vessel, check the output with a theoretical stress equation.

FEA simulations now allow us to solve 2D and 3D random shapes that do not conform to any traditional design. It is very powerful, but the responsibility to use it correctly is a real aspect of this approach.

From Anthony Rante, P.E.  Author of “FEA Applications in Machine Design”

u/Content_Tale6681 — 2 days ago

Tell me about your problems in your environment

I want to know what are the problems your facing in your daily life or in workspace or kn any field i want to start a startup so i want problem statements

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u/dr_tenma0309 — 3 days ago

I interviewed 30 candidates last week: Are CVs/Github becoming a weaker signal for software engineers?

i’ve been thinking about this after interviewing a number of engineers recently.

CVs are polished.
Linkedin profiles are polished.
GitHub can be polished too.

I feel like they’re becoming much weaker signals of whether someone can actually build and understands the systems they worked on.

So I’m curious:

What gives you confidence that an engineer can actually do the job before the interview?

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u/dyscooo — 4 days ago

I just noticed that teamwork are more requires skills than communication in software engineer job descriptions.

How do people really understand if someone has teamwork skills or not just from an interview?

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u/FFarahi — 3 days ago
▲ 6 r/EngineeringManagers+1 crossposts

What’s the biggest bottleneck during incident investigations for your team?

I’ve been reading a lot of incident postmortems lately, and one thing that stands out is how different every team’s investigation process is.

Some people jump straight into logs, others start with dashboards or traces, while some rely heavily on service dependencies.

In your experience, what’s the biggest bottleneck during the first 20–30 minutes of an incident? Is it finding the right signal, correlating information across systems, or something completely different?

what has actually improved your team’s workflow.

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u/ashhash6007 — 4 days ago

Need guidance and tips please

I am joining a new organisation as a senior engineer manager. It is one of MBB and I was a tech lead with managing experience to a smaller team.

What are some of the things I shd do to manage work, and set myself for success in my leadership role.

I am reasonably good with respect to technical strength.

Any guidance is really appreciated.

I have been feeling Imposter Syndrome as well lately and pushing myself to go out of my comfort zone.

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u/Will_Dewitt — 4 days ago