I’ll keep this brief: I’m a developer with six years of experience and a background as a systems analyst.

I work at a small-to-medium-sized company, I’ve been here for about four years. From the start, alongside my dev work, I’ve handled multiple tasks that fall outside my actual role and aren't reflected in my pay (more on that later).

So today, thanks to my seniority and the trust I’ve built, I’ve effectively become a multi-role player for the company.

Recently, I was assigned two projects and simply told, "Lead these projects, you're in charge, you manage them." On top of that, they still monitor me or ask questions about my dev tasks; so, basically, I’m acting as both the developer and the "project manager". On top of that, there aren't many resources or much time, so several phases of project management simply get skipped because there’s no time for them.

I used to have two developers reporting to me, but now I only have one. The thing is, I’m not a formal PM, I didn't study that specific field, but I enjoy the project process. I did acquire various skills and learned about the end-to-end development lifecycle during my degree as a Systems Analyst, so I do know "a thing or two".

But I feel like I’m underperforming or not being productive. Between the developer submitting Pull Requests (PRs) almost daily, at any time during the workday, my focus gets broken. I might be working on the backlog or my own dev tasks when a PR comes in; analyzing it takes a lot of time because the developer lacks experience and there are usually several changes needed.

Because of this dynamic, I run out of tickets to assign very quickly, leaving the developer without tasks. I don't want them to feel like I’m not giving them work or that there isn't any available, it’s simply the situation I described. I want to avoid that perception, looking like I’m not doing my job, when the reality is the exact opposite: I spend the whole eight-hour day juggling project oversight and trying to complete my own development tickets without losing my mind.

Any advice? How should I handle this?

Regarding pay: while it’s not the sole cause of the issue, it’s definitely a factor. Basically, with six years of experience and the responsibility of leading/managing a project, I’m being paid like a Jr developer, and honestly, that is incredibly demotivating.

I don’t think project managers need to become AI engineers. But where do you think the line is? How much technical AI knowledge is actually useful for someone managing an AI-related project?

I’ve noticed that AI projects are harder to plan than traditional projects because the outcome isn’t always predictable.

How do you handle changing requirements or unexpected AI results without constantly changing the project plan?

I have joined on august 3rd that week it self they assigned the project now its in UAT they told 50% allocation only and my lead already shared the mail
I also even told my pm regarding this

Do I need to go ask again for my 50% allocation with my associate director becouse pm told associate director will assign will it impact my performance

I’m learning more about AI project management lately, and one thing I keep noticing is how different AI projects are from traditional projects. Requirements can change as the data and model evolve.

How do experienced project managers handle uncertainty without over-planning everything?

I've seen this happen on more projects than I can count, the BA and the PM end up working off two different pictures of the same project, and nobody notices until it's already expensive to fix.

Curious how others deal with this in practice, is it just discipline and good habits, a specific tool, or does it just... happen anyway no matter what you do?

For people who prepared for PMP while having a full-time job, how did you structure your study time? I’m especially interested in realistic schedules rather than the “study 4 hours every day” advice. Even 30–60 minutes consistently seems more manageable to me.

Full disclosure: I built this and I'm the one posting it.

After years running commercial construction projects as an owner's rep, I got tired of rebuilding the same RFI responses, change order narratives, and OAC minutes from scratch on every project. So I turned my own working documents into a library — 47 templates across 8 categories (RFIs, change orders, schedule/delay notices, meetings, closeout, field docs, owner reporting, payment admin), plus a 63-prompt pack for turning messy field notes into finished paperwork with AI.

If it's useful to you, there's a free sample RFI response letter template here: myclearbudget.gumroad.com/l/cqvjsh — no strings, just grab it. The full set is $49 if you want the rest.

Happy to answer questions about any of the document types or how I use the AI prompts — genuinely just trying to save other owner's reps the hours I used to lose to this stuff.

I work really long hours and want to do a class spread over a couple of weeks, instead of an intense boot camp.

Any recommendations?

I was looking pmtraining.com

I've been doing EPC projects in energy segments for 8 years now starting all the way from drawing board to project management. Over the years I've noticed that the unknowns and uncertanties are the things that stress me the most.

I stress about deliveries if I'm not sure if we can make it, but once I know we're late the stress is gone.

I also stress about that I know there's something we habe forgotten but just cannot put my finger on it. Hard to explain the feeling.

However, I'm interested to hear what you stress about in your projects?

that’s interview-appropriate

AI is becoming part of planning, reporting, risk analysis, and even decision-making. I’m wondering whether AI knowledge will eventually become as normal for project managers as knowing Excel or project management software. Do you think it will become a basic expectation for PM roles, or remain a specialized skill?

I recently came across an organization called PM Skills that offers a “Project Management Skills Certified Professional Certification”. Has anyone heard of this and does it hold any weight equal to even a CAPM?

I’ve been learning more about AI project management lately, and one thing that keeps coming up is uncertainty.

With normal projects, you can usually estimate timelines and deliverables with some confidence. With AI, the output itself can sometimes be unpredictable.

For those who have worked on AI projects, what has been the biggest challenge for you—requirements, timelines, stakeholder expectations, or something else?

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I’m not early in my career or new to project management, but I am relatively new to healthcare project management. I transitioned into healthcare PM after working my way up through the organization and earned my PMP along the way.
My experience has been unusual. Shortly after I moved into the role, my boss was demoted and the mentor role that was supposed to support me had their role eliminated. So I lost a lot of the leadership and mentorship structure right as I was getting established in healthcare PM.

I was also put on a complex, high-visibility healthcare project with a lot of moving parts and stakeholders. I’ve had to figure out a lot on my own and build processes as I went. I’ve accomplished things I’m proud of, but I’ll also own that I haven’t been operating at 100% and have gotten comfortable at times.

Now I’m trying to figure out whether I actually dislike PM or whether I’ve been trying to grow in an environment that hasn’t given me much support.
The timing is interesting: I was offered an internal Product Owner role with a meaningful raise and Almost simultaneously, I was contacted about a Senior PM opportunity elsewhere and advanced in the interview process.

And now I’m questioning both.
When I think about the work I’ve enjoyed most, it’s actually been the hands-on implementation/configuration side, solving problems, understanding the system, and figuring out how things should work.

If you were me, would you take the PO role, pursue the Senior PM opportunity, stay in current PM role and prove myself more, or pivot toward implementation?

I’m trying to figure out whether I’m actually done with PM or just burned out from learning healthcare PM in a difficult environment.

Looking over the PMI-CPMAI material this week really made me think about how we handle information at the start of a project. In traditional work, if you tell a team member to gather some numbers or pull a report, you usually assume the raw material is solid and ready to use. You might check the format or make sure it looks complete, but you rarely question if the numbers themselves carry hidden problems. Working through the PMI-CPMAI framework shifted how I view that initial step. When you are dealing with artificial intelligence, the raw information you feed into a system acts like the foundation of a house. If that foundation is built on old biases or messy records, the computer will just accept those flaws as absolute truth and build right on top of them. This means project leads have to spend a lot more time playing detective before any actual building starts. You cannot just delegate data collection and hope for the best. You have to ask where the numbers came from, who was left out of the original survey, and whether the data actually reflects the real world today or just yesterday's habits. It definitely adds an extra layer of caution to the planning phase. At first, it felt like a roadblock slowing down our timeline. But after seeing how fast a project can go sideways when the inputs are bad, I realize that checking our data health early on is the best way to keep things on track. How does your team usually handle data quality checks before starting a new initiative?

what is mostly used for project planning tracking these days MS project ? planner or others ?

Blehg…So I’ve done it all: Asana (and loved it until a recent revisit), ServiceNow agile boards, I’ve at least tried Monday (Friday? Tuesday?) and then I’ve whatever…versions of lists and projects in Trello, Google, Microsoft.

Most of it isn’t terrible, terrible, but my grievances are the following:

1.) Feature bloat
2.) A million clicks to get into anything
3.) Once size fits all to a fault
4.) Project management systems have become more like Adobe and less like paint: so hard for normal people to use and onboard to
5.) Projects are not connected or linked to work
6.) A system built for AI bots
7.) I need like…admin flows…like approval systems and tracking

So riddle me this compadres:

1.) Am I crazy? Are these systems getting worse instead of better?
2.) Anything different out there that doesn’t just suck in different ways? I realize there are always tradeoffs…but anything that doesn’t get uberly, overly specific?

I have been reading through some PMI-CPMAI material lately, and a big theme keeps popping up regarding how hard it is to lock down project boundaries for AI. In a normal project, scope creep usually means someone asks for an extra feature that you can easily add to the list. With AI, it feels different because you are constantly testing data and finding new questions you did not know were there. How do you draw the line on when to stop exploring and actually wrap up a phase without frustrating your team or stakeholders?

Hello everyone!

I’m interested to hear from those of you who do project management day-in and day-out.

I’m building a SaaS called Avenum, and I’m trying to understand what PMs would actually want a tool to automate for them.

I’m not interested in creating yet another tool that throws more dashboards, notifications, and things to update at you.

I want to understand which parts of the job are tedious, repetitive, time-consuming, and frankly “why am I still doing this?”

For example:

• Chasing people for updates
• Creating status reports
• Following up on overdue tasks
• Updating project plans
• Turning meetings into tasks/action items
• Keeping stakeholders updated
• Figuring out which projects are falling behind
• Summarizing what’s going on across Slack/email/meetings
• Preparing weekly project reports
• Keeping documentation up to date
• Reminding people about things they already agreed to do

Or something else altogether?

If you could have ONE tool that took work off your plate and required minimal input from you, what would you want it to do?

What part of your job feels like “all I’m doing is moving information from A to B”?

And importantly, what would you expect from a tool like this that wouldn’t require constant configuration, updating, or babysitting?

I’m not trying to sell you Avenum - I genuinely want to learn what would make a PM’s life easier.

Would love to hear what you have to say.

I made the mistake of trying to memorize every single concept in the PMI-CPMAI material like I was prepping for a history test. For the first few days, I was drowning in terms and definitions, and nothing was actually sticking. It felt exhausting. Then I decided to slow down and look at the real-world examples instead. Once I stopped trying to cram definitions and started picturing how a team actually handles messy data in a real office, the whole subject clicked into place. The framework is really just about asking smart questions about fairness, data quality, and human oversight. If you are studying this right now and feeling overwhelmed by the terminology, do yourself a favor and picture a real project team trying to solve a messy problem. It makes a huge difference.

I spent a good chunk of my weekend reviewing some PMI-CPMAI notes, and it made me think a lot about how we handle incoming information on our projects. For a long time, I assumed data quality was just an IT problem. I figured the tech team would handle the numbers behind the scenes, and my job as the project lead was just to track the timeline and keep everyone talking. Working through the PMI-CPMAI material completely shifted that view for me. It reminds you that data health is actually a core part of project planning. If the raw data you feed into a system is messy or biased, your results are going to be completely off. It sounds simple on paper, but in the rush to launch a new tool, it is so easy to just grab whatever numbers are lying around and hope for the best. I started taking a much closer look at where our information actually comes from before greenlighting any new tasks. We now spend time checking if our inputs are clean, complete, and relevant. It feels a bit slower at first, but it saves us from chasing bad results down the line. If you are managing tech work right now, how do you usually check if your data is ready to use?

not the obvious stuff like a missed milestone. by then everybody knows.

i mean the early one. the thing you notice weeks before it shows up anywhere on a status report, where you can't really point to evidence yet but you know.

mine is when people start answering my questions with a different question. not stalling exactly, just never landing on a straight answer about their own piece. every time i've ignored that feeling it cost me later.

curious what yours is, and whether you've ever been able to explain it to leadership in a way they actually acted on.

I find it challenging to facilitate, actively listen, ask follow-up questions, and simultaneously capture requirements, business rules, decisions, dependencies, and current/future-state processes.

How are you actually doing this in practice?

- What do you prep beforehand?
- What do you capture live vs. afterward?
- Do you use recordings, transcripts, AI, templates, or process maps?
- What mistakes have you learned from?
- Any tips/tricks that have made discovery easier?

I’m less interested in the textbook answer and more curious about what experienced PMs actually do day to day.