ORMs: A Solution Looking for a Problem?
I used to wonder the same. But working on real projects changed my perspective.
Here’s the journey — the confusion, the pain, and the payoff.
#hashnode#java#nodejs#orm#hibernate#sequelize#mongoose
https://t.co/xaEQW0YA9X
I haven't allowed a production deployment after 4:30 PM in over a year.
Engineering thinks this is a security policy.
It is not.
I just like going home.
The rule started after a developer pushed a “small configuration change” at 5:17 PM on a Friday.
At 5:24, customer login stopped working.
At 5:31, twelve people were on a Zoom call.
At 7:40, someone ordered pizza.
At 10:16, we discovered the configuration change contained a typo.
I spent the entire evening staring at logs because another adult misplaced one character.
The following Monday, I created a production change-control policy.
Deployments after 4:30 PM now require an “Extended Operational Coverage Plan.”
The plan requires an incident owner.
Rollback procedure.
Monitoring confirmation.
Two approvers.
And named personnel available for four hours after deployment.
Suddenly every “urgent” Friday release became perfectly capable of waiting until Monday.
Engineering complained that the process slowed velocity.
I showed leadership our reduction in after-hours incidents.
Leadership loved it.
The CTO called it disciplined operational maturity.
Last Friday, he asked me to approve a 5:00 PM release for his pet project.
I sent him the form.
Deployment moved to Monday.
Had conversations with multiple senior folks across the industry last month.
The word is “AI is making everyone faster, but it’s not replacing good engineers anytime soon.”
- Has hiring slowed down?
Yes. Companies are hiring, but much more carefully than before. Previously almost every big company was bloated, and that contributes to the current layoffs as well.
- Teams gone leaner?
Yes. One person can now do more with AI on the sides. But you still need good people to take decisions.
- What about freshers?
Tougher than before. Supply > demand, so the bar has definitely gone up.
- What about salaries?
Top talent is still expensive. Average talent is feeling the pressure.
- How easy is it to get talent?
Still difficult. Good people are hard to find, and many aren’t switching because of layoff fear.
imo, the most exciting time to be around if you are in tech. If you are below average, time to push yourself. Will be difficult otherwise in the long run. Luck will be a factor, but also depends on how many doors you knock.
Introducing Epic’s version control system: Lore! Built from scratch and open-sourced, we made scalability and performance core tenets from day one.
We’re releasing Lore as open source today.All source code, along with documentation of data formats and protocols are released under an MIT license and free to use. Help shape it into something even more powerful, together: https://t.co/zplVMjkRof
usually the index exists but the query quietly is not using it, a function on the column, an implicit cast, or low selectivity makes the planner skip it. under load you also pay for it on every write and hit lock contention, so a read fix becomes a write tax. and an index that fits in memory at 10k rows starts hitting disk at 10 million. rarely just add index and done
@SidJain_80 Before initiating payment, we just check if the order status is pending. And before reverting status to pending, we must check if it is success already (in case of concurrent attempts)
In front end, the button should be temporary disabled on click (to prevent fast retries)
@SidJain_80 I believe this needs to be handled at multiple levels.
There must be an order entity and a payment entity.
When we initiate the payment, we update order status to mark payment-initiated. And move the order status to success after payment completes. Or back to pending if it fails.
@code_bytein While most people are citing DB issue. And I agree that it CAN be the issue.
IMHO it is more likely an external dependency issue.
If your API is able to perform at 1k req/s in normal case, I'd assume you've DB optimizations in place.
Locks don't normally generate out of thin air
@code_bytein No code was deployed. Soo no recent bugs created.
No alerts fired. Soo server load is normal.
I'd suspect there is some external API call or dependency that is causing the delay.
Could be that external API is taking too long, we've not configured timeout, network issues, etc
'Never use double for money' is dogma, not engineering.
@stefanofago breaks down when double, BigDecimal, or fixed-point is the right call, and the production traps that quietly undo each one.
https://t.co/1GE0yha8xp
#java#deepdive
This is so significant for us here in India.
The US government just told Anthropic to cut off its two most powerful models from foreign nationals, inside or outside America.
Anthropic could not cleanly fence off foreigners from Americans, so it pulled Fable 5 and Mythos 5 for everyone.
Let me walk you through what happened & explain what this means for us.
This week Anthropic launched two new models, Fable 5 and Mythos 5.
Both sit on the same very capable base. Mythos is the heavy one. It is so good at finding software security holes that Anthropic kept it limited to a small set of trusted partners under a program called Glasswing.
Mozilla said it fixed hundreds of security bugs using an early version of it. That cyber skill is exactly what makes the model valuable, and exactly what makes a government nervous.
On Friday, US Commerce Secretary Howard Lutnick sent a letter to Anthropic's CEO putting both models under export control.
By one account, the trigger was another company claiming it had jailbroken Mythos. The government had also tried earlier to get Anthropic to delay the launch and failed. The letter came right after that.
Anthropic complied within hours but pushed back hard in public.
It says the so-called jailbreak is narrow. Other public models like GPT-5.5 already do this, and security defenders use it every single day.
Anthropic's argument is simple. If a minor finding like this can yank a model used by hundreds of millions of people, then no frontier model from anyone could ever stay online.
The company also built Fable with extra guardrails and a 30-day data retention rule specifically to catch and shut down misuse fast, so being recalled over this stings even more for them.
Now, what does this mean for you and me, building on these tools from Bengaluru or Pune.
Day to day, almost nothing changes right now. Fable 5 and Mythos 5 are gone for everyone, but Claude Opus 4.8, Sonnet and Haiku all still work. Your normal Claude usage is fine. ChatGPT and Gemini are fine.
But the deeper story is that the most powerful AI is now being treated like advanced chips. A controlled export.
The same way the US decides which Nvidia chips India is allowed to buy, it can now decide which AI models India is allowed to use.
And the word "foreign national" puts all of us in one bucket, friend of America or not.
Remember that Anthropic's own CEO was in New Delhi in February, talking up AI for India. That closeness did not stop the tap from being turned off.
So this can lead to interesting ramifications.
One. A two-tier AI world.
US persons get the top tier, the cyber-capable frontier. The rest of us get the model one notch below, and even that can vanish overnight. This order landed at 5:21 PM with zero warning and the model was gone the same evening.
Two. A massive reason for India to build its own.
Every minister and founder talking about sovereign AI just got handed proof. If a tool can be switched off from a foreign capital you do not vote in, you cannot put anything critical on top of it.
Not a bank, not a hospital system, not a government service, nothing.
Three. A lesson for builders.
Do not wire your product to a single model from a single country and assume it stays.
Keep a fallback model ready to swap in. Abstract your prompts so you are not married to one provider. Treat model access like a supply chain with risk.
Four. Slower, messier launches ahead.
If governments can pull a model over a narrow finding, every lab will get more cautious about what it ships and where.
Expect more launches that are geo-gated from day one, where India is simply not on the list at the start.
I use these tools all day and I am not about to stop. I am not panicking and neither should you. None of this breaks your workflow tonight.
But if you are building on American AI from India, treat today as the day to plan for access being pausable.
Keep a backup. Read the sovereign AI conversation a lot more seriously than you did last week.
Gen Z realizing one of the biggest shocks after college is that life no longer happens around you.
In school, friends, events, relationships, and opportunities are built into your environment.
As an adult, if you don't actively create a social life, weeks can turn into months surprisingly fast.
Every dev has typed this:
Authorization: Bearer <token>
But nobody stops to ask —
Why "Bearer"?
Why not just send the token directly?
What's your answer? 👀
You're designing a new service architecture for a scaling team.
Do you start with a monolith that you can refactor into services later?
Or build microservices from day one with distributed systems complexity?
Which approach and why?
@swapnakpanda Because in India, they set the deadline first. And plan the work later. So when the plan requires each person to work 15 hours/day, having a personal life is simply out of the question.
Very practical list! I work with a solution architect who constantly gets rebuked by leadership in meetings simply because he lacks clarity of thought and understanding. This is very important.
#SoftSkills#Communication#ProfessionalDevelopment
How to avoid looking inexperienced at work
1. Don’t rush to answer everything.
2. Think before you speak.
3. Ask structured questions.
4. Avoid emotional reactions.
5. Stay composed in feedback.
6. Don’t overshare uncertainty.
7. Focus on clarity in communication.
8. Deliver clean, complete work.
9. Observe before acting.
10.Learn quickly from mistakes.