ZephyrBlu
The "it saves money" mindset is bad for everyone, distorts everything away from valuable work and investments that generate the most revenue.
Astra wasn't even released 3mo ago. It would not be surprising in the slightest that a public model from 3mo would not be capable of solving this problem, but an internal one from current day would be.
I found the Devin reviewer to be very good, and have heard good things about Cursor's Bugbot. I've also found asking an agent with fresh context or subagent to adversarially review locally is good.
I don't think that is what most people colloquially mean by "feature flags" though. Even most teams in Shopify abused "ephemeral" flags for long periods of time.
When they rolled out the mandate it was very annoying for my team because we had a lot of operational flags like you're describing that we needed to get exemptions for.
When someone else flips a flag that impacts your team and they have no idea they even caused a problem, it becomes very difficult to resolve the issue. Usually you can check for recent deploys, instead you have to go and guess at which feature flag which was recently flipped could possibly be affecting your code. I experienced this several times.
Also, it was actually more desirable for most of these things to go straight to production. Test it properly before shipping, then when you ship it soaks on a 5% traffic canary at which point you can monitor and cancel the deploy if you see errors. That is generally safer than a feature flag rollout unless you are doing something very high impact/risk, in large part because it gives any other team affected by your rollout the ability to respond and be able to easily find the source of errors.
In my org it was a fairly common failure mode to ship something and accidentally cause an issue for another team. Usually it was other teams/orgs shipping things that impacted us.
If it's config/customization, it should be in code. If it's experimental it can be a flag until it solidifies, and then it needs to get moved to code.
When I was at Shopify a couple of years ago they mandated that feature flags had to be short-lived (Like 2-4w lifetime tops, some had exceptions) because they would end up getting left in code and never cleaned up, or for extended periods of time like months. Hard to tell if it's genuinely a "feature flag" or actually just a normal part of the system at that point.
Feature flags being flipped in prod was also a major source of incidents, in part because people didn't treat them as experimental and with the associated risk profile of something experimental.
The only exception where having long-lived flags was useful and required was for operational killswitches (E.g. disable Apple Pay because it's having issues), but that is explicitly not application config.
Microsoft's previous model was not linked to tokens at all. Complete anomaly among coding agent providers. It's not representative of token economics at large. Claude Code recently announced increased limits. Codex does regular limit refreshes.
Tokens are pretty damn abundant even though they're not bargain basement cheap yet.
Previously they used "premium requests" which would allow you to make a request to one of the more expensive models. People abused the shit out of this because a request was disconnected from tokens.
You could make one request which used tens of dollars worth of tokens, obviously not the intended usage pattern and obviously unsustainable.
Tokens for a given intelligence level are becoming much cheaper very quickly, but everyone wants to use the smartest frontier models so tokens are not dirt cheap. Even frontier models are a bit cheaper in absolute terms than they previously were, and much cheaper in terms of intelligence.
It's also absurd to think that there is no company which does genuine software "engineering". If you break ads at Google/Meta, streaming at Netflix, etc there are massive consequences. They are heavily incentivized to properly engineer their systems.
The main thing that governs whether time is spent to well-engineer something is if there is incentive to do it. In traditional engineering that incentive is the law (Getting council approval, not getting sued, etc). In software engineering that incentive is revenue.
Seems like it was an insanely profitable product, but a risky business.
Material is not just about quality, but rarity or uniqueness. For example, japanese denim can get very expensive in part because it's very low volume. For dress pants, it might be a particularly interesting fabric.
A lot of more expensive pants also have interesting designs or proportions that are very unique or hard to find elsewhere. There is a lot of cool stuff you can get for under $500 USD though, that is still pretty expensive.
Some examples around that price range:
- https://stoffa.co/collections/trousers/products/lavender-woo...
- https://www.lemaire.fr/products/twisted-belted-pants-bl760-d...
- https://www.blueowl.us/collections/pure-blue-japan/products/...
Coding IC work takes a lot of focus and context that someone who is operating at the company-level should not really be in sole possession of.
To me, the whole point of these positions is to take the hit on random bullshit, planning, people management, etc and give your ICs space to do the kind of work he is taking on.
That doesn't mean you have no technical context or involvement in the development process, but it does mean you should probably be at least one step removed from it.
We were not built with the capacity to handle the sheer amount of stimulation the modern world has. You have to put in a lot of effort to not succumb to natural desires that would have been adaptive behaviours until recent history.
Maybe more about my unfamiliarity with the Korean address format than anything else tbh.
Some things about Naver I kind of miss from Apple/Google maps, but international software in general feels much more user friendly and better UX than Korean software.
I wouldn't expect things to calm down for a while, even if real-life results are worse. You can make excuses for underperformance of these things for a very long time, especially if the CEO or other executives are invested.
> The real problem we should be discussing is, how do we convince students and apprentices to abstain from AI until they learn the ropes for real
I hate to say it but that's never going to happen :/
This is the whole point. The marginal dev will go to the path of least resistance, which is to skip the understanding and churn out a bunch of code. That is why it's a problem.
You are effectively saying "just be a good dev, there's literally nothing about AI which is stopping you from being a good dev" which is completely correct and also missing the point.
The marginal developer is not going to put in the effort to wield AI in a skillful way. They're going to slop their way through. It is a concern for widespread AI coding, even if it's not a concern for you or your skill peers in particular.