
I asked AI to take a random photo with an iPhone 6 flash
Prompt: create an image of a random scence taken by i phone 6 with flash on chaotic and uncanny

Prompt: create an image of a random scence taken by i phone 6 with flash on chaotic and uncanny
Is Codex/ChatGPT Down for anyone else ?
What Codex Plugins are actually improving your workflow
Hey guys,
Currently on ChatGPT Plus mostly for coding.
I just got a promo code for ChatGPT Business that gives 50% off for 48 months, so I can get 2 seats for $20 total instead of the usual price.
For anyone who has used both plans for heavy coding/codex stuff:
Since the price is the exact same as my single Plus account right now, is there any reason not to switch?
Thankss!
GPT-5.6 spotted in Codex backend logs.
Codex v0.136-alpha pushed hours ago.
Today is Friday.
New model or just another Codex bump?
We find out in a few hours.
i have been thinking about something that feels obvious once you actually look at the hiring data lately: the cost of applying to jobs has basically collapsed to zero.
ai writes the resume, rewrites the cover letter, and browser extensions auto-fill the forms. candidates are applying to dozens of roles before they even understand what the company does. i read recently that a huge chunk of applicants apply to 20+ roles a day, and greenhouse has been openly talking about how application volume is turning into a massive trust problem, not just a workflow issue.
the active inbound pipeline is completely changing shape. it used to mean high intent. now it just means cheap distribution.
i feel like most hiring teams haven't adjusted to this reality yet. if a legit senior engineer applies to your role, that is obviously still useful. but if 400 people apply in 24 hours and half of them just spammed an ai apply button, the resume pile stops being a talent pool and just becomes a massive, exhausting verification workload.
the workflow i keep coming back to is almost the exact reverse of what we do now. define the role clearly, find people who have actual public evidence of their work (github, stackoverflow, open web), rank them by actual fit, and then just write outreach based on the real code they have pushed.
in other words, we need to stop starting with the pdf and start with actual proof of work.
for people hiring engineers right now, are you guys still actually trusting inbound applications as your main pipeline, or have you moved most of your serious hiring into outbound and passive sourcing?
i was ordering groceries on instamart today and was short by 20 rupees to get free delivery. usually, this is the part where i either scroll around trying to find some random pack of chips i don't need, or i just get annoyed and close the app.
but they popped up a new option: "add 20 to your swiggy money wallet to get free delivery".
i clicked it, paid the extra 20, and got free delivery instantly. that 20 rupees is now just sitting in my wallet to use on my next order.
as a product decision, this is brilliant. they basically solved three things at once:
it is a tiny tweak but solves drop off today and drives retention tomorrow.
has anyone seen other startups doing this? feels like a pattern that a lot of D2C checkout pages should copy
is anyone else building micro saas feeling weird about the AI hype lately? every day there's a new post or video showing how AI can write your entire codebase or launch an app in a weekend. sure, building is faster now, but if anyone can spin up a micro saas in two days, then the actual coding isn't the bottleneck anymore. it's judgment. knowing what to actually build, what feature to ignore, and what customer pain is actually real is suddenly the only thing that matters. you can use AI to write 10,000 lines of perfect code, but if your product direction is off, you just built a faster path to zero users. are you guys using AI to just pump out more raw features, or are you spending more time on the judgment side trying to figure out what actually needs to exist??
I’m currently paying $20 a month for Codex and accessing it mostly through the codex app, which has been pretty solid so far. I use it for about 1 to 2 hours a day, 5/d a week, mostly splitting my time between working on large codebases and writing content
Lately though, I feel like I might be hitting a wall with context limits. I’m thinking about upgrading or switching my setup next month but not sure
For those of you dealing with massive codebases, how are the $20 plans holding up on Cursor (especially with Composer) or Claude Code ? I’m worried about burning through my monthly premium requests within the first week if I switch over
Does anyone have experience using Codex side-by-side with Cursor or Claude for both heavy coding and content work? Would love to know if the switch is actually worth it or if I should just stay put
Hey everyone,
We are deciding on how to roll out Codex across our team for a large production codebase.
For those using it daily: Are you finding the Codex Mac App or the Codex CLI better for handling massive, multi-file codebases?
Specifically looking at how they compare for background agent tasks, context management, and remote dev (SSH/containers). Appreciate any insights!
Hey everyone,
We are deciding on how to roll out Codex across our team for a large production codebase.
For those using it daily: Are you finding the Codex Mac App or the Codex CLI better for handling massive, multi-file codebases?
Specifically looking at how they compare for background agent tasks, context management, and remote dev (SSH/containers). Appreciate any insights!
On May 12, Google hosted “The Android Show: I/O Edition” before the main Google I/O keynote and honestly this may end up being one of Google’s biggest ecosystem shifts in years
Android 17 is no longer being treated like just a phone update
Google is turning Android into an “agentic” operating system where Gemini can actually interact with apps and complete tasks across the system
For example:
Gemini can reportedly find a photo, crop it, and send it through another app automatically through multi step workflows
Google also announced deeper on device screen awareness so Android can understand what is happening on screen and suggest actions without constantly sending data to the cloud
Android 17 is also getting:
• floating app bubbles for every app
• native app lock with biometrics
• theft detection lock if your phone gets snatched
• session only location permissions
• blur protection for recent apps
• Hub Mode for tablets and docked Pixels
Google also showed major ecosystem changes
Quick Share is getting compatibility with Apple’s ecosystem later this year with QR based sharing for iPhone users
Chrome on Android is getting “Auto Browse” where Gemini can complete repetitive web tasks for you after approval
Android Auto now supports “Cast to Car” so passengers can cast videos directly to the car display
Then came the app partnerships
Instagram on Android is getting exclusive AI camera features for Pixel and Samsung devices including media upscaling and voice isolation tools
Adobe Premiere is officially coming to Android with AI templates optimized for Tensor and Snapdragon chips
Google also teased:
• Android XR smart glasses with Samsung
• Wear OS 5 with massive battery improvements
• smarter Gemini integrations across the ecosystem
The biggest thing I noticed?
Google is slowly changing Android from an operating system into an intelligence layer across every screen you own
Phone
Laptop
Browser
Car
Watch
Glasses
Everything now seems to revolve around Gemini sitting underneath the experience
this article kinda broke my brain a little ngl bcz we went thru the exact same thing earlier this yr posting on naukri and linkedin and getting flooded w hundreds of cvs/resume that looked copy pasted and going nowhere for weeks and i genuinely thought it was us doing smth wrong but turns out 80% of senior tech hires in india dont even come from job posts at all (which like makes so much sense in hindsight) the guy who actually worked out for us we found by literally going thru github commits not a single job board involved and at the time i thought we just got lucky but apparently thats just how it actually works for senior devs bcz the good ones are not refreshing naukri they're just building stuff and leaving trails elsewhere anyway worth a read if ur hiring rn specially the part abt passive candidates it hit diff for me imo
ok so i need to talk abt this bcz i genuinely felt like i was loosing my mind smwhere around week 3 of hiring for my (tiny 4 personn) startup and nobody warned me how absolutely soul destroying the process is like i posted one role on linkedin and indeed and within few (i think 4 maybe 5 hrs honestly) i had like 300 plus applications sitting in my inbox and i remember just staring at my screen at 1am thinking there is no way any human being is supposed to do this alone hahha i was spending literally six seven hrs a day just reading cvs and half of them were so clearly copy pasted or just wildly off base for wat i asked and imo the worst part wasnt even the volume it was that i kept second guessing myself like wat if the best candidate is buried smwhere in page 8 and i already burned out by page 3 and missed them entirely and that fear alone kept me going for weeks (which was prolly the unhealthiest thing i ever did tbh as a founder) anyway after way too long of doing this the dumb painful manual way i kinda stumbled into a completely diff approach to screening and shortlisting that i genuinely cant believe i didnt knw abt earlier and im not gonna pretend i invented anything new but the shift from me reading every single word of every cv to actually only spending real focused time on candidates who already matched wat i needed on a deeper level (not just keywords u knw) changed everything like my time to hire dropped insanely fast my quality of convos went up bcz i wasnt already exhausted b4 the interview even started and i made 3 hires in the nxt 2 weeks that all passed probation which b4 that felt like pure luck so idk if anyone else here is at that stage where hiring feels like it might actually kill u b4 scaling does but genuinely just rethink the first 60% of ur process (thats where all the invisible time is going fr) and most founders i talk to have no idea how much its costing them not just in hrs but in the candidates they never even got to
the guy i finally hired (after all that chaos) is now one of the best decisions i made for the co and he was literally on pg 6 of my applicants list which terrifies me everytime i think abt it
if i had kept doing it the old way i wud have never even seen his cv imo
imo most teams calc a bad hire way too simply like salary paid + agency fee + rehire time nd thats it. but after talking to one Series B startup that made a bad senior backend hire at 24 LPA, i realized the real cost is way bigger bcz almost none of the invisible damage gets tracked. recruiter spent ~80 hrs on the original search, they paid around 14L salary during the 7 month tenure, senior engs spent ~120 hrs reviewing/fixing their code, then after they left another strong eng lost almost 3 weeks rewriting parts of the system bcz of architecture decisions that didnt scale properly. product timelines slipped by a full sprint tooo. then came another 6 week hiring cycle + another 2.5L agency fee to replace them. nd honestly the worst part wasnt even money, 2 engs literally told their manager they were reconsidering their own positions after dealing with the mess. when they added everything together the estimated damage was somewhere between 35L to 45L for a 24 LPA hire. feels like the line items nobody puts in spreadsheets are the ones that hurt the most. curious how other teams think abt this, do you guys actually track a real cost per bad hire number or does most of it stay invisible???
(all numbers in INR, nd obviously these numbers can vary a lot based on company size, role, team structure, product stage, etc.)
most teams i talk to calculate a bad hire as: salary paid + agency fee + the time to re-hire
that math is missing almost everything
what we actually found when we broke it down for a Series B team that made one bad senior backend hire at ₹24 LPA
recruiter time on the original search: ~80 hours
salary paid during the 7 month tenure: ₹14 lakh
senior engineer review time on their code: ~120 hours over 7 months
code rework after they left: 3 weeks of a strong engineers time
product delay caused by the bad architecture decisions: one full sprint cycle
the re hire search after they exited: another 6 weeks, another ₹2.5 lakh agency fee
team morale cost: 2 engineers told their manager they were reconsidering their own positions
total visible + invisible cost: somewhere between ₹35 and ₹45 lakh
for a ₹24 LPA hire
the line items nobody puts in the spreadsheet are the ones that actually hurt
curious what other teams are actually tracking - do you have a real cost-per-bad-hire number or is it mostly invisible????