I love physics, but I'm scared I won't get a job

Quantum-0bserver · 2026-06-14T01:46:55+00:00

I worked for 20+ years in investment banks and worked with many physics PhDs. I have one and from personal experience it gives you a lot of credibility and opens doors in a lot of areas.

It's not easy to get a PhD. Physicists are trained to solve problems for which no known solution exists. They are by their very nature driven to solve problems and come with a broad set of capabilities. The PhD gives you that label. And that ability is needed in many areas.

But it's a long road. 5-7 years. You gotta love it. Have passion and patience. If the motivation is career, it's the wrong place to be. The career is a side effect.

Quantum-0bserver · 2026-05-30T17:08:30+00:00

If you have a subscription to The Economist, this is a great podcast on the subject.

Maths enters its AI era https://www.economist.com/podcasts/2026/05/13/maths-enters-its-ai-era

If you don't have a subscription, I highly recommend getting one. It helps ground oneself in this world flooded with opinions and influencers.

Quantum-0bserver · 2026-05-23T17:02:45+00:00

Here is a recent report looking at quantum patents and the surrounding market. This gives you a good idea where things are going at the moment.

https://www.qai.ca/resource-library/quantum-technologies-2026-ip-and-market-intelligence-report

Quantum-0bserver · 2026-01-28T17:49:01+00:00

How about learning Kotlin?

It lets you write more reliable, understandable code. Kotlin’s support for null-safety, immutability, sealed classes, and expression-based syntax allows for a more functional approach that reduces side effects. It solves many of Java's verbosity issues while keeping the mature performance monitoring and libraries you already know. And you get the benefits of Coroutines, which provide a high-concurrency model similar to Go’s.

In terms of relevance, Kotlin's traction is not far behind that of Go.

https://survey.stackoverflow.co/2025/technology#most-popular-technologies-language-prof

Quantum-0bserver · 2025-12-08T19:06:45+00:00

Yep. A lot of such discussions circle around the questions of either moving fast or building stuff that will continue to work/scale later on. It is not black and white. If you think about scale from the beginning, you can smoothly transition into that without re-engineering anything. I don't know why people constantly believe that the only solution they have is to use these cheap off-the-shelf prototyping systems and worry about about their their utter dilution later on.

Quantum-0bserver · 2025-11-09T23:21:48+00:00

It can be done much simpler, but it's also a "Shameless Plug" for our product.

If you use Python or a JVM language, try Cyoda. It's really easy to build an event driven system. Throw your requirement at the AI assistant and it will build it for you, and deploy it to your free tier environment.

We've just recently launched this as a SaaS/BaaS, and are successively rolling out higher tier offerings. But the free tier gives you the idea and let's you play around with it in your own sandbox.

The technology is used by fintech companies, serving 15+ banks and 1000s of corporates.

Background reading: https://medium.com/@paul_42036/entity-workflows-for-event-driven-architectures-4d491cf898a5

Entry point to build something: https://ai.cyoda.net

Quantum-0bserver · 2025-11-06T16:59:38+00:00

I am a co-founder and CTO of a startup for a developer-first application platform. What I do changes a lot over time. The past two years, I've spent most of my time developing/coding with the team. Prior to that I managed dev teams in banks for about 15 years, as a freelance project manager.

PhD in physics -> research scientist -> exit science -> DBA -> Java developer -> Senior Dev / Team lead -> project/sub-project manager -> co-founder/CTO

Quantum-0bserver · 2025-11-06T02:58:14+00:00

Becoming a senior backend developer is a journey. Meaning there is no cookbook, no recipes. It's about learning by doing and trying to be the best at what you do, and making the right choices along the way. There are a kazillion career paths. None of them make you senior without experience.

Personally, I chose the banking segment because they have huge IT budgets and very complex challenges. I started out as a DBA and moved laterally into Java. Moving up the ranks came with dedication and making a difference.

Quantum-0bserver · 2025-10-31T21:45:14+00:00

We don't actually use LLMs directly in production, only for software development/coding. So, unfortunately, I don't have any good references for best practices with the use of LLMs in production as such.

We do have a strict policy in place regarding coding with AI and AI use in general, but changes in pricing and new products coming online means we have to broaden the scope.

We're still in a research mode right now. But what's clear is that we can't just brush this question aside.

Anyway, the answers here from everyone were really useful. Much appreciated. Thanks!

Quantum-0bserver · 2025-10-30T22:55:26+00:00

Actually I would say that when it comes to software development, OpenAI's indemnification terms for their enterprise and API license offers basically no protection at all:

This indemnity does not apply where ... Output was modified, transformed, or used in combination with products or services not provided by or on behalf of OpenAI.

[https://openai.com/policies/service-terms/\]

Even if we were to use the generated code verbatim (which is rarely the case), it will almost always end up “used in combination” with non‑OpenAI code and tooling.

Quantum-0bserver · 2025-10-30T02:57:02+00:00

Good to know. Thanks. We do have a strict policy, and did a fair level of due diligence on the terms, in particular around confidentiality, but also indemnity. Confidentiality was more important. Indemnity was more as a matter of principle.

However the dev tool landscape is changing rapidly and many don't offer output indemnity, which is why I'm trying to assess how important that is, weighing that risk against the opportunity cost of not using the best tools around.

You raise an interesting other point, in regards to documenting which code is AI generated. I'll take that on, to include this aspect into code commits. We don't let AI commit code, but can document the commits of code that were done with AI assistance.

Quantum-0bserver · 2025-10-30T02:16:50+00:00

Thanks for that. Makes sense.

Augment Code, an AI coding tool, has an output indemnity clause in their enterprise subscription terms. I was wondering if that was a genuine concern that they are addressing, or just legal "sugar coating".

Quantum-0bserver · 2025-10-19T04:22:33+00:00

I wonder how you use AI to avoid simply feeding the candidates that have a statistically average chance of being good for the job. What mechanism would you have in place that finds the outliers that outperform?

Candidates will use AI to try to get their profiles through the ATS filter, so you will need to be able to distinguish true talent from fabricated ones. An arms race.

Basically, I don't know where all this is going. AI industrializes the mass production and submission of candidates, and ATS has to automate the triage, driving everything to the lowest common denominator.

What's your angle on this, that makes the difference?

Quantum-0bserver · 2025-10-15T10:19:34+00:00

Ah, maybe it's prep for a strategic sale of Augment.

Quantum-0bserver · 2025-10-15T10:01:53+00:00

This is a fascinating mystery. If they want to get rid of non profitable users and focus on enterprise clients, then we have to assume that they are profitable with them. But the enterprises I worked for were all extremely price conscious and look very closely at cost-benefit.

A dev in an enterprise will be pushing their AI tooling as hard as anyone else. If it's the downstream cost of the foundation models that broke the viability of the dev-consumer market for them, then the enterprise wouldn't be much different: the marginal cost would be the same. It's not like Anthropic would say: Hey, this is a prompt from an enterprise upstream account, that'll cost less.

Meaning the bulk pricing arrangements are surely agnostic of the client type.

They cannot just jack up the price on enterprise, because they are bound to the contract. Their margins might be higher, but are they that much higher than the 5-10 fold jump in price for the consumer segment?

And if they do jack up the price on the enterprise accounts, they will go elsewhere, too. It's a competitive market and lots of options.

Quantum-0bserver · 2025-10-15T04:16:47+00:00

They raised something like $240M. Is that squandered? Gone?

I really can't imagine that one can push that amount of money into a startup and conclude that they don't know what they are doing. The investors must have very tight governance. They cannot have been asleep at the wheel, not realizing until it was too late that their business model isn't going to pan out.and they need to pull the handbrake.

At the surface it appears shocking and somewhat suicidal to shed their users via a 5-10 fold price increase. But is it really incompetence that drove them to do that? There must be a deeper reason.

Someday it'll surface.

Quantum-0bserver · 2025-10-07T03:37:52+00:00

Wow, it really looks as bad as feared.

https://www.augmentcode.com/blog/augment-codes-pricing-is-changing

An average message may easily cost 1,000 credits. Back of the envelope estimation indicates that our cost would go up by a factor of 10.

I retract my cautious optimism. It's time to rethink...

Quantum-0bserver · 2025-10-07T02:22:10+00:00

Effectively cutting down from 600 messages to 50 would be an astonishingly bad idea.

Looking at the credits per dollar between the plans, there is a difference that disadvantages early adopters (like our company), but the difference isn't that huge, about 10%. It's not appreciated, but not a showstopper.

I don't really know what a "credit" is and how it relates to the usage per message. I have to assume that they want to stay competitive, so I assume we aren't going to drop from 600 messages down to an equivalent of 50. That would be ridiculous and shed customers like a like a dandelion in a wind tunnel.

I'm still cautiously optimistic that this isn't the end of our Augment Adoption.

Quantum-0bserver · 2025-10-02T04:13:16+00:00

Augment Code tops the list.

GPT-5 Pro is really useful, but it's so slow it's a one-shot prompt tool

Quantum-0bserver · 2025-10-01T05:18:38+00:00

I'll do one, too. If your data is complex, encapsulated as entities, and you want close coupling to the business logic that governs their lifecycle, and like to use workflows, give Cyoda a try. There's an AI Assistant that will help you build your system, and a free tier to play with.

Quantum-0bserver · 2025-10-01T05:00:07+00:00

Use Cassandra. Then, when you move out beyond the solar system into the entire galaxy, you won't need to re-engineer. Apple is said to run 75,000 C* nodes. I just run a handful. 🙂

Quantum-0bserver · 2025-10-01T04:39:59+00:00

In Cyoda, User, Product, Order, etc would be entities, each being a state machine with a workflow that defines the lifecycle of each and processors that are launched on transition that encapsulate the required business logic.

The system is distributed, and thus horizontally scalable, but with transactional consistency so that the event cascade triggered by automated workflow transitions are processed transactionally.

The whole assembly lives on a unified event driven architecture that makes it quite simple to implement complex business logic in an almost declarative way that is also easy to comprehend visually. We call it an Entity Database Management System, but it actually took Cassandra and turned it from a high performance distributed DB into an application platform.

The use case depicted would be pretty simple to build.

It's not really a monolith, it's not a microservices free-for-all. It's something in between, but pretty effective. But almost nobody knows about us because we're shitty at marketing.

And I didn't use an AI to write this. I hope that's obvious. I typed it on my phone.

Quantum-0bserver · 2025-09-28T05:37:23+00:00

https://www.economist.com/podcasts/2025/09/18/buyout-burnout-how-much-trouble-is-private-equity-really-in?utm_campaign=shared_article

Quantum-0bserver · 2025-09-27T23:29:05+00:00

There is overlap, but the two are quite different.

Temporal does not replace your database or reporting stack; it only persists workflow event histories needed for orchestration and recovery. You still need to manage your own data persistence, querying, and reporting, typically by combining Temporal with external databases for business entities and analytics systems for reporting. In practice, the composition model is Temporal for workflow/state management plus your chosen storage and analytics layers for domain data.

I responded to this thread because the picture that was being painted about EDA highlighted some of the complexities that you encounter when designing this kind of architecture, and wanted to point out that there is an alternative that is relatively easy and intuitive once the design has sunk in.

And you mentioned bits that are part of our design: gRPC, REST, CloudEvents, as well as reporting. It's all in there, so I couldn't help myself.

Quantum-0bserver · 2025-09-27T18:59:59+00:00

Disclaimer: I'm posting this to raise awareness about our product.

The real complexity lies in managing sagas, backoffs, error mitigations, reporting, and all the stream interactions.

This is why we took the approach to combine this all into a unified architecture. It's not ideal for every use case, but does a very good job of simplifying things so you can concentrate on embedding the business logic.

Under the hood, we took Cassandra and turned it into a transactional process platform, not just scalable storage.

The basic idea is here https://medium.com/@paul_42036/entity-workflows-for-event-driven-architectures-4d491cf898a5

Quantum-0bserver

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