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Discussion (65 Comments)Read Original on HackerNews
I imagine they smushed 2 of the most well-known AI-isms together on purpose here to troll the AI-weary. Might as well I guess, if this type of language annoys you then the whole feature probably will too.
The full statement:
> This isn't just a new feature — it’s a new way to build software: open, collaborative, and powered by both human ingenuity and judgement and agent scale. Teams that build this way won't just move faster. They'll build things no one else can.
I am not sure how just drawing contrasts between two things without actually drawing any kind of causal relationship to explain _why_ something is better or _how_ it does it, came to be a good thing. It is the kind of vaccuous statement that some poor tired sod with his remaining system 1 capacity just YOLOd into the blogoshpere and, like you said, the weary who don't know any better get FOMOed by. PSA: you arent missing anything.
All I do now is spend all day on calls with people whose shit exploded and I'm trying to scrub it off the walls, ceiling and the customers.
Why in the world would I want to become someone that doesn't write code?
I test it. I have another AI do code review. I push it to test, then after tests to production.
For some common tasks, that I don't find interesting it is great. I do a lot of CRUD, I honestly cannot imagine writing these apps without AI.
It made curious and freed my brain to think about other things. I am now playing with hardware and plan on launching a niche product. This would not be possible if I 100% committed to programming without AI.
If anything, my setup has gotten ever so simpler as models got better.
Maybe in a few years being a good coder will be like being a good taxi driver with self driving. You know the best spots and the ai can't drive the most unusual roads but effectively 95% of all driving is self driving.
Why would this person be more skilled? And more importantly, what does it mean to be "skilled" in the era of AI?
I'm trying to be open-minded to both sides, but I have senior engineers on my team with a fleet of agents, shipping code they don't fully understand, and... everything is fine. Stuff still breaks, we fix it. Clients ask "How does XYZ work?" and we say, "Not sure, let us get back to you." And they're totally fine with that answer.
Everything within me screams that this is wrong and we should have intimate familiarity with the system, but I cannot find any evidence that the path of "running a team" instead of "building engineering skill" is not going to work out fine in the long-run. (Yes, my comparison between "team" and "engineering skill" is a bit rough but I'm not interested in the semantics.)
All the evidence that I'm seeing in my own business, with senior engineers meeting clients' needs with autonomous agentic teams is that it's all fine, and while there are gaps, it's actually okay. Clients are happy. Software works 80-90% of the team exactly as it should. Bugs are fixed quickly. We ship more in 3 months than we previously could've shipped in a year. I'm baffled and frankly not as advanced as my devs (I still ask questions one by one to my agent, like a Real Caveman!)
It makes me wildly uncomfortable so I'm trying to wrestle with this. I want your statement to be true, but I just don't see evidence of that.
Either you work in a non-standard field, or your standards for software are way too low.
What software gets to fail 80% of the time? If your ecommerce checkout software fails 1 in 5 times, you don't have an ecommerce business at all, you are dead in the water. If your airline booking software fails for 1 in 5 customers, you are out of business.
99.99% reliability still means 1 in 10000 customers are experiencing an error, which at scale can mean thousands to millions per day. That's completely unacceptable for any software I've ever been involved with writing.
There's plenty of ideas, they just don't have them [1]. It's kind of hilarious to watch all of these people copy each other out of fear while pretending they're being original.
[1] https://www.youtube.com/watch?v=nMfHYUFeiJo
I'm looking forward for AI to make it very easy to deploy your own tools and walk away from all this SAAS.
slack, jira, notion, even google suite
AI makes the cost of software development much lower, which means you can have a very good alternative that you can self host.
I'm thinking of companies that has 1000+ employees that pay millions annually in SaaS subscriptions.
SaaS is a tax on b2c business that will be reduced.
Seriously just fuck the whole industry and walk away! Go back to emailing spreadsheets and documents around. Save your shit to your own hard disk. You don't need a todo app - just post-its stuck to your fucking monitor. Call someone on the fucking phone. Crack your software or use OSS. Run it all on recycled PCs. Stop giving everyone money for this shit because it's only normalising your subscription future.
Note: I work for a SaaS company. They are bastards. They all are.
Personally, I'm getting ecosystem fatigue. Who even has the time to set up pilots to feature-test all these different systems?
What are people actually using to manage semi-collaborative agentic coding workflows nowadays? We've moved from on-dev-machine coding to @claude in GitHub, but of course GitHub purposefully weakens the capability of that approach to the point that it's kind of a hack. Github/Linear have somewhat more cohesive experiences but it still feels like tooling for agent teaming is quite lacking and unergonomic.
Im not convinced of any of these cloud or tagging solutions where I get to the point of moving coding away from my dev's machines.
Because models run for a long time autonomously developers need to manage more agents simultaneously. At that point you basically need a tracker for tasks in flux, and compute for each agent. It also means that the interactive monitoring isn’t as helpful anymore.
Regarding visibility, developers now think in high level architecture rather than lines of code, but implementation details are still important to document. We also want to understand when agents are hitting pain points. Both of these basically require archiving agent outputs more deeply than just code changes and commits.
I've been using Claude and other agents in Slack for some code tasks. It's mostly fine for simpler projects and products. Things like docs or specific libraries. But I'm not really convinced this is the ideal interface yet. Reviews are my bottleneck and GitHub has a great UI for this. Plus, token consumption with Slack is out of control.
Maybe in time this will be the way we work, but for now I still find myself using GitHub, a terminal, and slack together.
https://www.youtube.com/watch?v=Z0GFRcFm-aY
Maybe it’s the future. Where I can join to coding/spec driven channels to observe or help.
I would do this - coding/spec driven in public. Hope it will be the future.
It would allow also non devs to join.
Next up - Slack releases a model router. Cloudflare builds an agents platform. OpenAI acquires a dev tools startup.
You can’t just “spin Claude up in slack”; it can’t magically just connect to GitHub and your code.
I presume this feature basically is like… if you’re already using your agents in cloud hosted runtimes, then you can connect to those agents like you already are, but via slack.
…
Did I misunderstand?
This seems like a non feature; if you’re bring to want it, you can’t have it because you have to setup Complicated External System, and if you’re already using cloud hosted agents, you’re already using it (eg. Claude tag or whatever).
So it’s what… a diff viewer in slack? An agents tab so slack becomes like cursor?
The videos seem enormously light on examples of how it actually works, did someone find a more detailed example of usage to show why you want this?
https://buzz.xyz/