Zach Gollwitzer

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Zach Gollwitzer

Zach Gollwitzer

@zg_dev

Fintech data systems and infra engineer ○ Running https://t.co/crOIdOlqX0, https://t.co/tKra6hDDCk

Cincinnati, OH Katılım Aralık 2020
513 Takip Edilen3.2K Takipçiler
Zach Gollwitzer
Zach Gollwitzer@zg_dev·
@GergelyOrosz Every product launch, pivot, layoff announcement, and employee-published video/post I’ve seen come out of Meta the last 5 years has felt dystopian. It’s amazing what a lifeline an ads business can be for a company that otherwise doesn’t appear to be making any progress
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Gergely Orosz
Gergely Orosz@GergelyOrosz·
Meta laying off 10% of staff when revenue is at an all-time high, revenue growth is a beast (33% YoY!!), profits at an all-time high: just depressing These layoffs are not because Meta needs to lay off, but because Zuck wanted to lay off for whatever reason
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Zach Gollwitzer
Zach Gollwitzer@zg_dev·
@omengue Interview processes are all over the board right now. Nobody has a standard process for testing AI usage and it’s exhausting for candidates. I’d almost rather just hand-write code in an interview so you at least know what you’re prepping for
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Olivier Mengué
Olivier Mengué@omengue·
@zg_dev Hand writing code is still a major milestone in interview process. One is supposed to be both an expert at driving agents and at writing elite code. 🤷
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Zach Gollwitzer
Zach Gollwitzer@zg_dev·
Hand-writing code, reading technical blogs and books, listening to conference talks etc is probably one of the most important habits to maintain at some level right now (even if just 1 day / week). We all know hand-writing code isn’t practical for the demands of the modern day SWE job, as scope has 10x’d at most companies who are paying attention. That’s fine and expected, but just like we built gyms when corporate work kept us inert most of the day at a desk, we need these counter-balancing “brain gym” activities to keep clarity in both our product thinking and engineering thinking. LLMs revert to the mean, so how do we keep excellence in both our products and engineering culture? These things actively sharpen our critical thinking. They are intentionally slow. Slowness IS the feature here. Slowness allows us to chew on tough concepts for a while rather than a quick follow-up to an LLM who will spit out yet another wall of text that feels smart yet your brain is incapable of internalizing because you’ve found yourself in an endless loop of re-prompting every time something doesn’t make sense. You feel like you’re absorbing so much new information and “orchestrating” everything when really, you’re being fed mountains of options and have lost the agency to steer the ship. Clear technical thinking is the single most important engineering skill right now. The LLMs are becoming experts at implementing a clear spec. We lose our quality of outputs when the LLM-induced laziness kicks in on hour 8 of tapping the keyboard and we no longer remember what the spec was. We give into the temptation to say, “I think the LLM has it from here”. But it doesn’t. It doesn’t know your business and will introduce compounding complexity if you let it. In software, the last mile is the most important, and in the agentic era having the ability to think clearly and subtract things is the path to achieving quality software.
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Zach Gollwitzer
Zach Gollwitzer@zg_dev·
@vboykis A few months ago I started making an intentional effort to fight against this and it brought me back to a clarity of thinking I forgot existed. Its like the next level of “digital detox”
Zach Gollwitzer@zg_dev

Hand-writing code, reading technical blogs and books, listening to conference talks etc is probably one of the most important habits to maintain at some level right now (even if just 1 day / week). We all know hand-writing code isn’t practical for the demands of the modern day SWE job, as scope has 10x’d at most companies who are paying attention. That’s fine and expected, but just like we built gyms when corporate work kept us inert most of the day at a desk, we need these counter-balancing “brain gym” activities to keep clarity in both our product thinking and engineering thinking. LLMs revert to the mean, so how do we keep excellence in both our products and engineering culture? These things actively sharpen our critical thinking. They are intentionally slow. Slowness IS the feature here. Slowness allows us to chew on tough concepts for a while rather than a quick follow-up to an LLM who will spit out yet another wall of text that feels smart yet your brain is incapable of internalizing because you’ve found yourself in an endless loop of re-prompting every time something doesn’t make sense. You feel like you’re absorbing so much new information and “orchestrating” everything when really, you’re being fed mountains of options and have lost the agency to steer the ship. Clear technical thinking is the single most important engineering skill right now. The LLMs are becoming experts at implementing a clear spec. We lose our quality of outputs when the LLM-induced laziness kicks in on hour 8 of tapping the keyboard and we no longer remember what the spec was. We give into the temptation to say, “I think the LLM has it from here”. But it doesn’t. It doesn’t know your business and will introduce compounding complexity if you let it. In software, the last mile is the most important, and in the agentic era having the ability to think clearly and subtract things is the path to achieving quality software.

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vicki
vicki@vboykis·
Something happens to my brain after agentic coding that I can’t describe. It’s like cognitive offloading which folks have already written about, but even more. It feels like I can’t think through problems anymore. Like a fog. Using agentic but losing my hard-won agency.
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Zach Gollwitzer retweetledi
Nic Barker
Nic Barker@nicbarkeragain·
One of the biggest problems with using LLMs as a google replacement for programming, is that getting zero relevant results on google used to be a signal that you had the wrong idea about the root cause. Whereas LLMs will happily indulge any terrible idea you suggest.
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Zach Gollwitzer
Zach Gollwitzer@zg_dev·
@arvidkahl Even at these numbers, it’s in the hundreds of TPS, which isn’t unprecedented. I think the real challenge is the entire system was probably architected around upper bound constraints that seemed like hard ceilings (what a human can produce) and AI codegen broke those assumptions
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Zach Gollwitzer
Zach Gollwitzer@zg_dev·
They need a massive simplification of the UI and to completely scrap the “copilot auto-complete” stuff with Duo which feels super outdated at this point. Insert provider-agnostic AI flows at the edges of the SDLC and make CI/CD runners 10x better than GH Structurally, they’ve got a lot of opportunity esp since they’re mostly making money off slow-to-adopt enterprises, but execution risk is huge, and so far they really haven’t proven they can out-execute anyone, including GitHub (who hasn’t set a high standard)
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Dan Loewenherz
Dan Loewenherz@dwlz·
I thought this morning that maybe the market is mispricing GitLab. For context, their stock has fallen in value by >50% over the last year. So I spent some time this morning testing out the product end-to-end (creating a repo, checking out trending projects, pushing code, opening a merge request and reviewing, etc.). Well, there is a reason not everyone is talking about migrating to them during this otherwise obvious moment of opportunity: the product is just not that different than GitHub, and in a lot of ways it's IMVHO just worse. Unless they reinvent the product in a big way, GitLab doesn't seem to be well positioned to take advantage of GitHub's current moment of weakness. Their products are just too similar to each other. Ultimately, I decided the company is not worth buying at this moment in time. Maybe that'll change, but right now the source control products I'm paying attention to don't resemble GitHub at all; whatever comes next will look completely different.
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Zach Gollwitzer
Zach Gollwitzer@zg_dev·
GitLab has a solid core product for the AI era and I think their stock has been over-punished given both the financials + pure play offering. They’ve got answers for the entire SDLC, are provider agnostic, and have a perfect chance to capitalize on the “sandboxed agents” trend running at relevant points in the SDLC. That said, 100% agree w/this. The UI/UX is completely overwhelming. There is too much on each page, and it distracts from the good stuff the platform offers. A massive UI overhaul would be a great way to re-launch their product and convince the market they’re a serious alternative for more than just big enterprises.
Jason Cox@jasonbcox0

There's a lot of confused people in this thread on why GitLab isn't an acceptable drop-in replacement for Github. I will periodically add some examples. These are UX monstrosities that make it *unusable*

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Zach Gollwitzer
Zach Gollwitzer@zg_dev·
@AbhiramTek38379 @_CallMeMacy A CRM build would be a great learning project. Teaches basic data modeling, contact lifecycles/reconciliation across multiple systems, background jobs, SMTP providers I'd build by hand without AI if learning is the primary goal
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Abhiram Teki
Abhiram Teki@AbhiramTek38379·
@zg_dev @_CallMeMacy But what would you recommend for beginners. Who are just starting their programming and web development journey. About the ai usage By the way your channel helped me a lot while starting the web development journey.
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Macy Mills
Macy Mills@_CallMeMacy·
Lately, I've been advising founders to vibecode their own CRM that reads their emails, calendars, and keeps things up to date in real time. It took me 2 hours to create my own using Claude Code (and I've never coded in my life). Am I crazy for suggesting this or do others agree?
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Zach Gollwitzer
Zach Gollwitzer@zg_dev·
I think customers would be much happier with 2 separate status pages: 1. Uptime - traditional status page with incidents that affect uptime metrics, are deterministic known bugs, and can be fixed fast 2. Quality - a status page that acknowledges degradation of outputs based on some combo of open benchmarking and customer reports (this issue was overwhelmingly prevalent amongst Claude power users here on X) I get that these degradations could take days or weeks of correlation data to pinpoint. It was the fact that Anthropic blamed the users and didn’t acknowledge it could be something that was changed internally that caused problems. No, customers wouldn’t be happy seeing issues go up on the “quality status page”, but would at least appreciate acknowledgement of the issue These sorts of issues just can’t be represented properly on a traditional status page
ClaudeDevs@ClaudeDevs

Over the past month, some of you reported Claude Code's quality had slipped. We investigated, and published a post-mortem on the three issues we found. All are fixed in v2.1.116+ and we’ve reset usage limits for all subscribers.

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Zach Gollwitzer
Zach Gollwitzer@zg_dev·
Regardless of how they handled it, it is wild to live in a new world where bugs take weeks to identify, customers are gaslit in the process, and even when you identify, fix, and publish a post-mortem, you still can’t provide 100% attribution to a root cause “We changed our system prompt which degraded responses” could only be caught by evals, which involves at least some judgment and opinion; a stark contrast to how we’ve evaluated and fixed software for decades
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Muratcan Koylan
Muratcan Koylan@muratcan·
The frustrating part is that the Claude Code team, along with people deep in AI psychosis, have been gaslighting anyone who raises concerns about Claude Code's recent issues. "your reasoning setting is wrong" "oh that benchmark is wrong" "we checked our code, nothing is wrong" "skill issues" "Hate" is a strong word, but when you're paying a lot of money for a product and it actually makes your job harder, to the point where people make you start questioning the quality of your own work, it really becomes a problem. I'm glad they identified the issue, and I genuinely want them to succeed, along with Cursor, Codex, OpenCode, and others, we need more alternatives, but we also absolutely need open benchmarks. anthropic.com/engineering/ap…
Muratcan Koylan tweet media
Muratcan Koylan@muratcan

WE DON'T HATE CLAUDE CODE ENOUGH WHY ARE WE PAYING THOUSANDS OF DOLLARS IF YOUR EVERY RELEASE IS MAKING THE HARNESS LESS USABLE?

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Zach Gollwitzer
Zach Gollwitzer@zg_dev·
3-4 in parallel is my max. Guess I don’t have as many cores hardwired in my brain as some. I think it also comes down to: - your tolerance for bugs / bad software design (mine is low) - your budget - your project scope (in real world enterprise software, most ppl don’t have enough scope/access to truly justify 24/7 agents outside package upgrades and simple bug triage) The “overnight agents” narrative seems to be highly experimental, although there are some companies out there who I genuinely believe have at least cracked a basic proficiency here, even if for simple routine tasks (ie Stripe, Ramp, etc). But then again, these are companies with huge R&D budgets and time to experiment. I don’t buy the narrative outside of these contexts (sure, I believe the LOC narrative; just not the “enterprise grade quality + extra LOC” one)
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Ronan Berder
Ronan Berder@hunvreus·
Talking to smarter folks than me, I'm convinced many of the AI folks in my timeline are full of shit. Nobody is "running 20 agents over night" and building stuff for actual users. Maybe some are building internal tools or disposable software. Maybe. But building software people like using? That doesn't get hacked on day one or blow up after the 3rd user? Nope. I don't even understand what that's supposed to look like. Do you work out a 57 pages document that perfectly describes what you want to build and then summon 14 agents and have them run wild for 6 hours? And what comes out on the other end isn't a broken pile of shit? Nope. Not buying it. PS: it may also be that I have an IQ of 82 and can't figure it out.
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Zach Gollwitzer
Zach Gollwitzer@zg_dev·
@siddharthkp The friction of slowness, and the costliness of bad design decisions is how any great SWE became great, and we’ve deleted that layer from the SDLC. I imagine this is more of a talent pipeline issue 5 years down the road than anything else, but I feel this
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siddharth ☻
siddharth ☻@siddharthkp·
staff/senior engineer thought:
siddharth ☻ tweet media
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Zach Gollwitzer
Zach Gollwitzer@zg_dev·
I feel like RLS can potentially make sense as a fallback, or, if the team strategically places a lot of logic in the DB (eg fns, triggers, check constraints, etc) and is already incorporating those changes in the SDLC To me, the biggest issue here in the vibe-coding era is abstracting away the entire idea of authorization from app development. If the platform granularly handles it, but leaves it to the user to get right, you’ve now got a situation where the “dev” (maybe technical, maybe not) isn’t thinking about authorization day to day, and even worse, the agent has no context around it either. So yeah, a massive footgun
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David Cramer
David Cramer@zeeg·
RLS was a mistake and folks exposing that level of complexity to less technical users is asking for trouble. It was a mistake in Firebase. It’s a mistake in Supabase. It will be a mistake in the next product too. I personally - even knowing how to secure it - would never touch it. It’s the worst security footgun you can imagine. One small mistake and your data is available to the world.
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Zach Gollwitzer
Zach Gollwitzer@zg_dev·
> build a beautiful codebase with strong patterns manually > drop an agent in there and say, “this codebase is a mess, we need to refactor” > without pause, the agent will always reply, “honestly, you’re right. Want me to start with XYZ module?” It’s this sycophantic behavior that makes everything 10x as hard because as the dev, you have to keep a lot of mental discipline to always stay in the driver seat The second you get lazy, which is easy when you’ve talked to an agent for 8 hours and you’re tired, the agent will follow your terrible, fatigued ideas and you’ll generate so much bad code in those last couple hours that the previous work isn’t worth much It’s the same thing we’ve always dealt with. More bugs are introduced when we’re tired and it’s often best to step away from the keyboard before doing too much damage In today’s world, not only do we generate 10x as much code during this fatigued state, but we also have this urge to leave the agent with a task to work on while we step away
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Dan Greenheck
Dan Greenheck@dangreenheck·
I've been using Claude Code exclusively for 6 months and I'm still not convinced on this whole AI thing. There are some *seriously* insidious problems that worry me, and I don't see them being fixed any time soon. Every release of a new model, I see hundreds of posts where people think because they one-shotted X or Y, software jobs are cooked (I've probably made one or two of these posts myself). But none of those examples are actually representative of real-world software. If I set it to work on an ambiguous or highly complex problem that has a lot of branching in the solution space, I've noticed the following: - It can often generate a working solution in one-shot, which gives me a false sense of confidence that the AI knows exactly what it's doing. - As I continue to work the problem, I've noticed the AI will start to narrow its focus more and more, not considering how a fix or solution plays into the big picture. - The quality of a solution depends on *how* I prompt it, which is really, really bad. Software engineering should be deterministic, not a dice roll. - It will often ignore instructions I have explicitly stated in the rules file, which removes any confidence I have in the code it generates. - It consistently overstates its confidence in a solution. I literally just got this response from Claude: "I overstated that. Honest answer: it depends on the scene and implementation; the 2–4× figure was too confident." If I had never pushed back, I would have been operating on incorrect information. - It is far too agreeable. If I'm not careful in my wording, the AI will blindly follow my instructions, even if they are suboptimal. I want a real coding partner that challenges my ideas, not an ass-kisser. Don't get me wrong—AI has helped me build some amazing things faster than I ever could without it. But the more I use it, the more I begin to question the direction things are headed. If the AI was more direct about what it (not) capable of, it'd be a lot easier to work with. But being gaslit every step of the way makes the process stressful as hell. Going back to manual coding isn't even an option since the value of having AI *potentially* generating the correct code in 1/10 or 1/100 of the time is literally too good to pass up on. Sorry for the rant, drank way too much cold brew this morning.
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Zach Gollwitzer
Zach Gollwitzer@zg_dev·
It’s crazy to think that malicious hackers, many of which are highly technical are using the same AI tools to build their exploits while the industry is reducing the tech workforce, relaxing code standards (implicitly), and pushing more LOC than ever before
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