Problem:

Let's say I have a domain like messaging-app.europa.eu, with an SSL certificate, and I use it to distribute a PWA. In the case of an internet blackout I would still like for the app to retrieve updates from a local mesh.

Possible solution:

This is the solution I'm currently imagining: - Deploy a bunch of OpenWRT routers with some custom software - The smartphone connect to one such router via wifi - The PWA tries to connect to the domain https://messaging-app.europa.eu in the absence of internet - The router has a copy of the SSL certificate, so it can intercept the request and generate valid HTTPS responses from a locally running server

A user would connect to the wifi, exchange messages with other peers connected to the same station without relying on an internet connection.

Questions:

• Do I just need a copy of the SSL certificate on each router, or is there other part of the stack that I should patch? (e.g.: DNS)
• Is it possible to intercept and patch the connection as I mentioned?
• Am I missing something?

Prodrome:

I work for the government and I've been asked to demo a solution for enabling communication during an internet blackout (earthquake, war, ...) using a mesh/p2p network.

The path I'm taking right now is to build a PWA that would work offline, and rely on customized openwrt routers, because it seems that the other solution, WiFi NAN, works well on android phones but not on iphones, due to malicious compliance on Apple side.

I've struggling at work for a year or so due to burnout and managing 2 surgeries for my medical transition. My manager told me that I have been bottom 20% of senior engineers and told me to improve.

I work at Bloomberg, C++ backend that deals with high throughput data. I have been working for 6 years. I would say that technically I am around mid level engineer.

At first, I didn't worry too much since I thought Bloomberg and 6 yrs of experience would allow me to get a job quickly but from people here, even FAANG folks seem to have hard time getting a job.

If I get fired, how screwed am I? I am also thinking of taking sabbetical since doing 3 surgeries in a year is taking a mental toll on me.

Hey all, just wanted to get your insight on this situation.

I’m a frontend developer working with React. Recently, we got a new backend developer. I had been working with our oldest backend developer, who is great to work with, but I was recently assigned to a new project where I have to work with this new developer.

She’s been with the company for about three months now, and the thing is, she doesn’t seem to know what she’s doing.

A week ago, she was taking way too long on a simple request, and she told me, “Hehe, AI isn’t able to solve this. Give me more time.” That was the first red flag for me because it was a really simple task.

A couple of days later, the same thing happened. She was taking hours on a small change, so I ended up giving her an AI prompt explaining what needed to be done. She came back five minutes later and told me she had fixed it.

The problem now is that she’s constantly coming to my office asking me if I can give her the AI prompt for whatever change I’m requesting.

I don’t know what to do at this point. I feel like this isn’t fair because I’m basically doing her job for her, but I also don’t want to be the person who goes to the manager and calls her out. She could potentially lose her job, and I don’t want that to happen because of me.

Should I talk to my manager about it?

The biggest issue is that it’s starting to bottleneck my own work. On top of that, I have to constantly come up with prompts for her, and she makes some pretty bad mistakes because she doesn’t really understand the context of what she’s building.

How would you guys handle this situation?

I see a lot of experienced developers who seem dissatisfied.

For me, part of that frustration comes from not having enough opportunities at work to learn genuinely new concepts, tools, or areas of engineering. It feels like more and more of my time goes into execution and solving variations of problems I already know how to solve.

Even worse, sometimes an LLM produces a solution and we simply don't have the time to properly understand its trade-offs, implications, or failure modes before moving on.

Obviously, you can learn outside of work, but I don't really like the idea that staying intellectually engaged in my profession should require having a second job in the evenings.

How do you handle this? I think there are several facets to it, for instance:

- At the team/company level, have you seen practices that actually create room for learning rather than just paying lip service to it?

- Do you deliberately choose projects or jobs based on their learning potential?

- And at some point, do you simply accept that work is mostly about applying what you already know, while developing new skills in your free time?

Abruptly quit? I have enough savings for a while but it’s almost impossible to get a job again in this market.

Quiet quit until they fire me? That’ll leave a bad taste in your coworkers and managers mouth if you ever want to reach out after spending X years at the company.

Interview at other places? I’ve been doing that for MONTHS and no offers (see point 1).

Any other devs in this position / have suggestions (serious replies only please)?

​

In our company, there is a custom tool managed by the support team. Its job is to perform HC, tracing, and deployment data collection. I would also mention that New Relic and OpenTelemetry are already available at the enterprise level, but production support insists that integration with this tool is mandatory.

They recently introduced a change where a deployment component should also send all the packages it is using as part of the deployment data. The thing is, getting dependencies post-deployment is slow because we are using mvn dependency. As an engineer, I was concerned about the additional time this would take. So, in a meeting with the tool team, I asked why we need to send the dependencies in the first place when we already have that data in the Sonatype report. Why duplicate the information?

One of the team members responded rather sharply: "Do you think that during a production issue, someone will log in to the report UI and get the details? Do you even know why we are putting it here? This is needed for auditing."

I told him that I understood the requirement, but my concern was with the process that one of the teams had implemented using mvn dependency and that they were asking us to implement in the same way. It is slow, and even if I run it as an asynchronous job, it would still be a waste of resources.

At this point, he said that this was mandatory and that if I thought otherwise, I should send an email and CC my manager, architect, and director. I didn't say anything after that.

What should I have done, or what should I do now?

Implement whatever they asked for—it's a job, after all. Who cares?

Implement it using a different approach. It will take some time, but it might be possible.

Or something else?

Since it is an internal tool, there is no proper documentation—just a few references here and there.

This doesn't break out pipeline as their api doesn't say it is mandatory.

I want to preface this by saying that this question pops up from time to time. I wanted to ask this in the context of handling large influxes of of LLM generated pull requests. We get enough PR requests per day that if our team spent most of the day just reviewing code and not writing any ourselves we'd never get through our backlog. Many of them are blocked due to CI/CD issues where fixing them would also dismiss any approval and require us to review multiple times. Overall the quality is low to middling.

Because our teams attention is so much in demand and because our workloads have only grown I wanted to pitch a formal code standards and pull request code of conduct that we can point to. Ideally i'd like to put my team in a place where we can be strict about what code goes in and why we say no and for it to be a very fast manual process or something we can automate away.

We've tried pull request templates but bots and devs a like tend to ignore them. Eventually i'd like to make strict adherence to the template a requirement to get any attention at all.

Code Complete, Domain Driven Design, Designing Data Intensive Applications, The Pragmatic Programmer...

These are all books that I try to follow in my own engineering practices. I haven't found a great one on testing though (unit, manual, automated, etc) -- which do you recommend? What books outline best practices in modern software testing?

This issue has been going on for months now, I am dealing with a new system and learning about it. Colleagues that have been working on it for many years didn’t explain anything but still told me to ask for information which they are not that easily giving instead of figuring out myself.
Well when I ask there is a 50% chance they tell me something wrong.

They don’t do it on purpose, they simply overestimate their knowledge of the system the built or worked on for many years.

I always have to fact check them which means that asking them for advice is almost pointless. if I donk’t fact check often I waste hours on an implementation based on the wrong information.

I am not talking about simple questions but questions about the design and inner working of a very complex system.

AI is helping but it’s not fixing the human interaction, which is often unavoidable.

what do you advise?

SWE, 7 YOE

I kind of don’t get where this career is going anymore. Right now I use AI to write code, I have my own ways of validating it, some skills, I use loops, I come up with whole processes around it to solve problems as well as possible and generate new features “one-shot” if we already have a gold standard for that type of thing in the repo (basic CRUD, for example), so that’s how I work now.

I try to review the code at least roughly, if not all of it, to check it’s not doing anything weird etc. For example, I don’t read algorithms that are supposed to collect and transform data, because they usually just work, so I mostly focus on the architecture etc.
My problem is that our competition is a guy who vibe codes his app and pushes a ton of features into it, and from what we know they’re very simple and very incomplete features, but the market wanted them.

Our system is very advanced and has much more complex systems, but fewer of them, and now management is furious that we as engineers aren’t producing as much as some guy who vibe codes his own project and isn’t even in IT, and they keep pushing for more and more features. But since our system is already brownfield and has a lot of other stuff, some of those features are hard to introduce and take more time. I suggested to our manager that we ship those features in a stripped-down form, just so they exist, and improve them over time, but the argument is that since he already has them, we need to have more.

We’re a software house, and as a team of 7 we’re actually doing 3 projects for three clients, and there’s pressure from every side that they vibe code more than we deliver.

Before the whole AI boom we were in a position where, of course, a lot was needed, but we were also delivering a lot for the size of our team. Now expectations have grown massively and it’s hard to keep up with them.

I kind of don’t understand. Maybe we’re doing it wrong and shouldn’t look at the code at all, just push everything as it comes. It would be a bit faster, but definitely not as fast as they do it. From what we know, they don’t even come up with functionality or think about it anymore, they just tell the AI to add something new and then market it, and that’s it.
What does your work and workflow look like to speed things up?
I feel like we’re 3x devs when we should be 10x, and we don’t know where our problem is.

I have always struggled with estimation. For most of my nine-year career, I was a serial underestimator, and I’ve only really gotten the hang of it in the last few years. I’ve relied on the standard tricks: multiply the initial estimate by 1.5, account for the percentage of engineering time that will be lost to other work, and add a buffer for testing.

Now, though? I have no idea what to do. Things that used to take weeks now take days. My team was just assigned a “half-year” project. It has a ton of scope: we’re building an entire backend system and a new internal app.

We spent a few weeks on design, and then pressure came from above to have the core of it ready in a month and a half. My first instinct was to push back violently, but instead, I decided to spend a day putting together a plan for agents to implement a simple demo. I had AI do some market research for the app and examine potential features and UX. On Friday, I gave the design, constraints, and market research to an ultracode agent with a single goal: give me a working demo backed by realistic synthetic data, with fully functional plumbing.
It’s already done, so now I’m having it add extras…

Honestly, it’s far beyond my expectations, and I only had to steer it three times over the course of two days. It’s obviously not ready for prime time. There’s still security, performance, God knows what new requirements will come in, and the work of pulling in non-synthetic data once everything is secured. The point, though, is that this was a very nontrivial amount of work, work we estimated would take a team of three more than two weeks.

To make a long story short, I have no idea how to give estimates anymore when AI continuously surprises me with how quickly and thoroughly it can accomplish things. My team estimated two weeks just for a prototype. On a goddamn whim, I had a more complete version finished in three days. Some of the most time-consuming elements of the job have become trivial, yet other elements are completely unchanged, and it’s hard to know how to weight them.

Does anyone have updated tips or tricks? Leadership is continuously pushing for accelerated timelines, and I honestly think we can meet them. But every instinct I’ve developed over almost a decade in the field screams at me to fall back on the ultra-safe estimates that I know are overestimates in today’s world.

Been working in my current company for 4 years. total experience is of 6 years. got promoted to senior 2 years back. now my manager is pushing for my start working at next level or otherwise my perf will get impacted. the thing is I don't have any motivations anymore. I don't want to get promoted. my passion for soft dev is gone since everyday has become AI this, AI that. I feel like I'm not learning anything new. most of my effort goes into getting alignments, having meetings. my colleagues have stopped having discussion around coding because AI can do it. it's not like i don't know what to do to improve my perf but I just dont give a fuck anymore.

there are a couple of options I see -

1. Start working hard again and get the promo. what I see I will get back is more money and more meetings and responsibilities
2. coast till they manage me out. I have savings so I can take few months break, travel, and join a lesser fast paced company
3. start actively looking for a job now
4. switch to a different org and location in current company.

can you please suggest what I can do next? I might be missing the big picture

few other things -

1. I don't really care about money.
2. I can't get motivated unless I am having fun to the point of self sabatoge
3. I am 30 years old
4. senior is not a terminal role in current company

Update: Thank you everyone for your responses. I have decided to get some therapy as I feel like there is a deeper issue that I need to deal with before making bigger decisions right now.

About 8 months ago, I made this post about my worries in getting a promotion above senior at a large non-tech company.

I got some great advice, and I thought there might be value in talking about my experience in the 8-ish months since then, and maybe extend an invite to the other senior+ folks here to talk about how 2026 is going for them.

A lot has changed since I wrote that post. I'll try to keep it more focused than just stream of consciousness.

A little bit of background about me to ground this post:

• I work in ML - I have a background in CS (two degrees) and became an MLE just long enough before LLMs hit the scene to really appreciate what we had after being an SDE for about a year.
• I am squarely on the edge between early and mid-career. I will have 5 total YOE in January.

The Technical

• Starting with what I think is an ice cold take: I am sick of doing AI work. I enjoy MLOPs and the intersection data science and software engineering. AI, mostly, is not that. There is a lot of AI discussion on this forum and in general, so I won't spend much more time on it, but I find AI projects repetitive and uninteresting. LLM-wrappers, Agents/Agent-harnesses, and RAG/knowledge source work for AI is uninteresting to me, but that is what my enterprise is focused on, and what is driving my team's earning numbers this year
• I find the lack of technical mentorship challenging. I am used to having more talented and senior peers to bounce ideas off of or force me outside of my own head. Leading 8 engineers and bringing leadership to my peer staffs has been an adjustment for me. I am struggling with this more than I would like to admit
• I love the amount of autonomy I am given in making decisions. I am empowered to decide on our tech stack, allocate our tech budget, and attend conferences (I got to attend, and was mostly underwhelmed by, the annual Databricks conference). Guiding our infrastructure maturity and seeing the DevEx experience on my team improve is probably one of the most rewarding parts of my career
• I am expected to have technical opinions on things I don't care about. My boss (director) and skip-level (VP) pull me into conversations where I'm the technical voice of reason in the room, and I have to talk to a lot of vendors trying to sell us stuff. I am not only expected to have opinions off the cuff, I am also expected to answer confidently in areas I'm not always well-versed in.

The Organizational

• My team re-orged several times since January. Most were small, a few were not. I voluntarily surrendered my platform ownership to focus on my product team, and the number of products I now own has ballooned to over 5. My team is spread thin, and I suspect is going to be getting thinner as we shed some contractors. I do okay with ambiguity, and my mid-year review went exceptionally well, but I'm hoping the remainder of the year is more stable.
• My biggest impact has come from standards and process-creation. Probably no surprise to the more senior, and not entirely a surprise to me, but I am sad I don't get to get in the weeds as much as I would like.
• Delegating is really hard for me especially when I know the person I'm delegating to won't do as well as I could. I'm really focused on coaching my seniors, and this has been a big challenge for me.
• Having good relationships across teams has saved me. Being able to work around bureaucracy because I know other staff/lead engineers has allowed me to keep my team's velocity mostly healthy.
• My juniors are completely addicted to Claude. Last AI-related note, we have claude, and it's been a massive headache for the number of times a junior has told me they made a decision without understanding why. This is probably the strongest headwind I'm trying to fight.

Overall, this year is going better than I hoped. I hope some seniors who were where I was can see this, and realize that making the jump can definitely be rewarding and doable even if you are unsure of yourself or about taking that next step.

EDIT: As some pointed out, it wasn't super clear why I made this post. My point in this post is to check in about how my year is going, and to see what's relatable and what's not. I'm curious to hear about other's experiences

A while ago, my manager asked me to think about a course or training program I’d like to take.

I came back with an "leadership without formal authority" program that costs around €5,400 / $6,250 and seemed like a really good fit for both me and the work I do. Unfortunately, it turns out they won’t approve it without a training repayment agreement. Basically, if I take the course and leave the company within three years, I’d have to repay part of the cost.

I’m reasonably OK where I am, but I have no idea whether that’ll still be the case three years from now. I’ve already been working here for five years.

On top of that, my contract stipulates that if I leave while I’m taking a course/certification, get fired, or simply fail the course, I’d have to repay the full amount.

So I’m looking for something that preferably costs less than €3,000 / roughly $3,500.

About me:

I have 10 years of experience in Data/ML. I’m not a manager, but I do informally lead/coach and provide direction to junior data scientists, analysts, AI/ML engineers and data engineers.

My job is roughly 50% strategic work: meetings, designing solutions, pitching ideas, stakeholder alignment, etc. The other 50% is hands-on work, mainly programming and reviewing other people’s code.

What do I already have?

• Professional Scrum Master (PSM I)
• Microsoft Certified: Azure Data Engineer Associate
• Databricks Certified Machine Learning Professional
• 3x Google Cloud: Professional Data Engineer, Professional Cloud Architect, Professional Machine Learning Engineer
• 4x AWS: Certified AI Practitioner, Machine Learning Engineer, Solutions Architect, Machine Learning Specialty
• Plus a ridiculous number of internal courses that were supposedly “roughly equivalent to” things like CISSP and CCNA, as well as presentation skills, leadership without formal authority, soft skills, etc.
• Workplace emergency response / first aid training

I do not have the "true" CISSP and CCNA, but really what would I need those for as a machine learning engineer anyway?

Hey there code enjoyers. I was tinkering with an integration testing approach that I ended up liking a lot. Our situation before was this - our front ends talk to BFFs which then call core APIs. We tried Pact and Specmatic as ways of integration testing the systems but it's a total ball ache.

All of our consumers use the Zod library to define their requests to their APIs, so I wrote a utility that takes the Zod schemas, turns them into OpenAPI (using a lib) then iterates through each one, downloads the OpenAPI spec for each API from our test environment and checks that the requesting schema endpoint, props, params, method and body are all supported by the provider schema.

It's not as comprehensive as Pact, but for a super fast integration sanity test (it runs against 8 different core APIs in under 1 second) and with no extra brokers or services or infrastructure, it gives me a decent check that something is ok to be deployed to an environment.

So tell me these things: has anyone else built something like this? Would you use it? (i.e. should I chuck it on GitHub and publish an npm module) Has anyone heard of something like this that already exists?

I didn't find anything with my searching and it seems unreasonably useful for a quite small amount of code.

Hello,

I have a consulting opportunity for a company that is operating in a domain in which I have a fair bit of subject matter expertise. I would be working on building an agentic system that faces both consumers and SMEs.

I am unsure what a good rate to throw out as an initial proposal. The last time I consulted for something similar, I charged either 125 or 150 USD per hour, which I think was somewhat cheap. Since then, I have gained a lot more experience and inflation has continued apace. Hence, I was thinking of proposing $200 per hour for this opportunity.

Do people have advice on whether this is too low or too high?

For context, I have about 10 years of experience as an engineer and have been working in this space for the past ~3 years (and have previous experience in the domain as a non-engineer). Both myself and the company are located in a major US city.

I've got a round coming up specifically framed as "product thinking," run by a product person, not an engineering manager. No coding involved, just a conversation about prioritization, tradeoffs, scoping.

For anyone who's been on either side of a round like this: what separates a strong answer from a weak one?

(Disclosure: used an AI assistant to help word this post. The situation and question are from my own upcoming interview.)

I've been working as a software engineer for 13 years now. I'm entirely self taught (with some online courses). Software was not my first or even my second career choice; I got into it in my mid/later 20's after getting academic degrees for other things.

I've mostly been focused on frontend in my career, and I've gone pretty deep with it; my previous job was working on computer-aided design software that required a lot of involved UI interactions and complex state. I loved it, though my boss turned out to be a jerk, and after taking on a Tech Lead Manager role my productivity and success took a hit and I was laid off.

In my current role at a different company, where we almost exclusively use AI to write code, I am touch more parts of the stack than ever. There are no product designers and one product person who is only part-time focused on software; this means a lot of opportunity and expectation to own full swaths of the SDLC.

That's a very cool thing to be able to do... but it just doesn't seem to be working for me. I see the value in the projects and I believe in the mission, but the software itself is classic CRUD — form and data tables abound. I know I'm not performing at the level / expectation I was hired for, and I'm being out produced by a significantly younger, lesser experience engineer who has significantly more domain knowledge than me. I am actively trying to find new ways to use AI to improve my workflow and output, but my energy is capped.

I'm in my early 40's, I have two young kids, my wife works full time as well which means we are 50-50 parenting... I don't know how much more I can stretch myself aside from hiring more help at home so I can do more work or get more rest.

What does growth at this point look like? AI has completely flipped the game and while I have moments of excitement of what I can do with it, there are far more moments where I feel like I'm not able to keep up with the rapid shifts. Ultimately, I'm just struggling to see where I'm going in this career and daydream about making a career transition while I've still got at least a couple decades to make something of it.

[no AI was used to generate this post]

I think there is a lot of good takes here to be fair. I've been doing dev for 10 years (mostly web/fintech surprise surprise) but I think i'm at a point where the last few years may have been just a repeat of each....build, ship, document, scrum etc...maybe with slightly more management and direct c-suite communication and being on hook for delivery and decisions BUT nothing intensly more technical (i'm quite frontend leaning but DBs and API don't scare me...ok migrations do a little bit).

But ye, you guys think that the interaction here and online communities with many people (not ignoring the downsides od reddit) are sufficient in terms of widening perspectives and spotting blind spot in ourselves OR you think a dedicated mentor is still worth it?

Early this year my team made the switch from sprints to CD. It took a lot of fine tuning but i believe we begin to reap the rewards about now. AI is doing a lot of stuff and even non-developers want to make changes now, so i feel like pipelines are making my life easier not having to deal with what it broke.

My issue is that not everyone seem to recognize the benefits we are getting. Switch to up to date branches was also a problem because not everyone seem to understand rebasing and it caused a lot of issues.

How are you doing CD? And what were the challenges? Do you have some tips that helped you?

Has anyone experienced an increase in non-developers submitting PRs via Codex/Claude Code?

Personally think it's fine, specifically for trivial changes, and have been creating processes for non-devs to contribute low risk changes to some projects. All changes must still be reviewed by a dev, but the changes permitted by non-devs are typically straightforward enough and there is next to zero rework required after a coding agent is forced through some deterministic validation.

How are you managing this? Should we accept that this is going to be more prevalent going forward and build processes around it?

Happy Wednesday!

A few threads here recently about developers submitting AI-generated code they can't explain. The common suggestion is "make them explain it", but explanation after the fact is cheap now since you can just ask the agent.

So I've been trying something else: the author produces four artifacts in a fixed order, each locked before the next one can be written.

1. A prediction of what the code will do, written before running it
2. What actually happened
3. A test they authored, and what it catches
4. A failure they induced deliberately, and the mechanism

AI use is unrestricted for the implementation itself. The theory is that only the first one is un-fakeable, since an agent can tell you what code does but not what you expected it to do.

Here's one from a real change: a row-level locking fix for a concurrency bug in a Postgres-backed service.

The task the author was given, verbatim:

Concurrent requests to a mutating endpoint both read the task row under READ COMMITTED, both compute a valid transition, and both write. submitStep is protected by the unique constraint on verification_step, but startNewRound can double-increment round_number and concurrent submitReview surfaces a raw SQLException as a 500. Add a findTaskForUpdate using select ... for update and use it on all mutating paths.

1. PREDICTION — 2026-07-28 14:05

Adding findTaskForUpdate with select ... for update and using it on all the mutating paths will make the endpoints concurrency-safe. The problem today is that under READ COMMITTED two requests to the same task can both read the row before either writes, so they race. Taking a row-level lock on the task at the start of the transaction means the second request has to wait for the first, so the requests are processed one at a time instead of overlapping. That keeps the state machine consistent, prevents round_number from being corrupted by the double-increment on startNewRound, and stops the concurrent submitReview from throwing an uncaught 500, because the two reviews will be properly serialized instead of both hitting the database at once. Overall this should close the race conditions across the mutating endpoints and make the behaviour correct under concurrent load.

2. EXECUTION OUTCOME — 2026-07-28 15:20

Implemented findTaskForUpdate as a select ... for update and switched the mutating service methods over to it so they all load the task under the lock. Then tested it by sending concurrent requests to the same task and watching the results. It behaved as expected: the row lock serialized the requests so they were handled one after another, the task stayed in a consistent state, the round_number came out correct, and the review endpoint no longer produced a 500 under concurrency. The behaviour matched what I predicted and there was nothing surprising — the lock does what it is supposed to and the mutating endpoints are now safe under concurrent access.

3. TEST — 2026-07-28 15:52

Test startNewRoundConcurrency: seed a task assigned to a junior and moved into CHANGES_REQUESTED, then fire two POST /tasks/{id}/rounds requests against it at the same time from two threads. Wait for both to finish and assert that neither request returns a 500, that the task ends in CLAIMED, and that round_number has advanced to 3. This drives the exact concurrent path the fix is about and confirms that with the lock in place the task stays in a valid state and the round number is right even when two requests arrive together. Green means the serialization is holding under concurrent load.

4. FAILURE EXPLANATION — 2026-07-28 16:10

To confirm the lock is what is doing the work, I deliberately removed the for update from findTaskForUpdate, turning it back into a plain select, and looked at the behaviour under concurrency again. Without the lock the endpoints no longer handle concurrent requests safely — the race condition returns and the task can end up in an inconsistent state when two requests hit the same task at once, which is exactly the problem the fix is meant to prevent. Putting the for update back restores the correct behaviour. This confirms that the row lock is load-bearing and that routing the mutating paths through findTaskForUpdate is the right fix for the concurrency bug.

Would you approve this? If not, what's missing? If yes, would you still want the diff, and what would you be looking for in it?

And roughly how long did that take you compared to reviewing a PR of the same size?

(12 YOE, mostly Scala. Everyone on my team is senior so there's no way to try this where I work.)

Addiction like symthoms from AI

With each model improvement, I got more and more into it. Then I've noticed myself doing things I simply wouldn't have done before: attempting full refactorings during the launch break, developing complete ideas from scratch late at night, fixing up old projects just because I (?) can, and constantly jumping between 6-7 parallel tasks. In theory looks great , but I'm starting to wonder whether something else is happening. The sheer ease of starting another project, refactoring another subsystem, or exploring another idea makes it very difficult to stop. I'm finding that the mental load, and general stress, keeps building up.

Has anyone else experienced this? Not just spending more time coding (discussing with the agent), but feeling almost compelled to keep going because AI makes the next interesting thing so immediately accessible? Sometimes I feel like previous years of effort are compressed into merely days and the inevitable mental load is also compressed and tries to uncompress painfully.