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AI Jobs and Career
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- Full Stack Engineer [$150K-$220K]
- Software Engineer, Tooling & AI Workflow, Contract [$90/hour]
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- More AI Jobs Opportunitieshere
| Job Title | Status | Pay |
|---|---|---|
| Full-Stack Engineer | Strong match, Full-time | $150K - $220K / year |
| Developer Experience and Productivity Engineer | Pre-qualified, Full-time | $160K - $300K / year |
| Software Engineer - Tooling & AI Workflows (Contract) | Contract | $90 / hour |
| DevOps Engineer (India) | Full-time | $20K - $50K / year |
| Senior Full-Stack Engineer | Full-time | $2.8K - $4K / week |
| Enterprise IT & Cloud Domain Expert - India | Contract | $20 - $30 / hour |
| Senior Software Engineer | Contract | $100 - $200 / hour |
| Senior Software Engineer | Pre-qualified, Full-time | $150K - $300K / year |
| Senior Full-Stack Engineer: Latin America | Full-time | $1.6K - $2.1K / week |
| Software Engineering Expert | Contract | $50 - $150 / hour |
| Generalist Video Annotators | Contract | $45 / hour |
| Generalist Writing Expert | Contract | $45 / hour |
| Editors, Fact Checkers, & Data Quality Reviewers | Contract | $50 - $60 / hour |
| Multilingual Expert | Contract | $54 / hour |
| Mathematics Expert (PhD) | Contract | $60 - $80 / hour |
| Software Engineer - India | Contract | $20 - $45 / hour |
| Physics Expert (PhD) | Contract | $60 - $80 / hour |
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Is Google’s Carbon Programming language the Right Successor to C++?
For years, C++ has been the go-to language for high-performance systems programming. But with the rise of multicore processors and GPUs, the need for a language that can take advantage of parallelism has never been greater. Enter Carbon, Google’s answer to the problem. But is it the right successor to C++?
Google has been in the news a lot lately for their new programming language, Carbon. It’s being billed as the successor to C++, but is it really? Let’s take a closer look.
On the surface, Carbon and C++ have a lot in common. They’re both statically typed, object-oriented languages with a focus on performance. They both have a learning curve, but once you know them, you can write code that is both readable and maintainable. However, there are some key differences that make Carbon a more attractive option for modern programmers.
For one, Carbon is garbage collected. This means that you don’t have to worry about manually managing memory, which can be a pain in C++. Carbon also has better support for concurrency than C++. With the rise of multicore processors, this is an important consideration. Finally, Carbon has a more modern standard library than C++. This includes features like string interpolation and pattern matching that make common tasks easier to accomplish.
According to Terry Lambert, Carbon Programming language is probably not the successor of C++. His reason are:
“Single inheritance is a deal-breaker for me, even though the eC++ utilized by IOKit in macOS and iOS has the same restrictions.
Although it specifies stronger type enforcement, which would — in theory — also eliminate RTTI and the reflection, which eC++ has historically eliminated as well, it’s doing it via expression-defined typing, rather than explicitly eliminating it. I expect that it would also prevent use of dynamic_cast, although that’s not explicitly called out.
Let’s see if Linus approves of someone compiling the Linux kernel with Carbon, and then starting to add Carbon syntax code, into that port of Linux.”
On the surface, Carbon seems like a great choice to replace C++. It is designed to be more reliable and easier to use than C++. In addition, it is faster and can be used for a variety of applications. However, there are some drawbacks to using Carbon. First, it is not compatible with all operating systems. Second, it does not have all of the features of C++. Third, it is not as widely used as C++. Finally, it is still in development and has not been released yet.
These drawbacks may seem like deal breakers, but they don’t necessarily mean that Carbon is not the right successor to C++. First, while Carbon is not compatible with all operating systems, it is compatible with the most popular ones. Second, while it does not have all of the features of C++, it has the most important ones. Third, while it is not as widely used as C++, it is gaining popularity rapidly. Finally, while it is still in development, it is expected to be released soon.
What Is Carbon?
Carbon is a statically typed systems programming language developed by Google. It is based on C++ and shares a similar syntax. However, Carbon introduces several new features that make it better suited for parallelism. For example, Carbon provides first-class support for threads and synchronization primitives. It also offers a number of built-in data structures that are designed for concurrent access. Finally, Carbon comes with a toolchain that makes it easy to build and debug parallel programs.
Why Was Carbon Created?
Google’s primary motivation for developing Carbon was to improve the performance of its search engine. To do this, they needed a language that could take advantage of multicore processors and GPUs. C++ was not well suited for this purpose because it lacked support for threading and synchronization. As a result, Google decided to create their own language that would be purpose-built for parallelism.
Is Carbon The Right Successor To C++?
In many ways, yes. Carbon addresses many of the shortcomings of C++ when it comes to parallelism. However, there are some drawbacks. First, Carbon is still in its infancy and lacks many of the features and libraries that have made C++ so popular over the years. Second, because it is designed specifically for parallelism, it may be less suitable for other purposes such as embedded systems programming or network programming. Overall, though, Carbon looks like a promising successor to C++ and is worth keeping an eye on in the future.
Conclusion:
So, is Google’s new Carbon programming language the right successor to C++? We think that Google’s Carbon programming language has the potential to be a great successor to C++.
With its garbage collection, better support for concurrency, and modern standard library, Carbon has everything that today’s programmer needs.
It is designed to be more reliable and easier to use than its predecessor. In addition, it is faster and can be used for a variety of applications. However, there are some drawbacks to using Carbon that should be considered before making the switch from C++.
So if you’re looking for a new language to learn, we recommend giving Carbon a try.
Programming paradigms 2022-2023
Programming paradigms are a way to classify programming languages based on their features. Languages can be classified into multiple paradigms.
Some paradigms are concerned mainly with implications for the execution model of the language, such as allowing side effects, or whether the sequence of operations is defined by the execution model. Other paradigms are concerned mainly with the way that code is organized, such as grouping a code into units along with the state that is modified by the code. Yet others are concerned mainly with the style of syntax and grammar.
Common programming paradigms include:
- imperative in which the programmer instructs the machine how to change its state,
- procedural which groups instructions into procedures,
- object-oriented which groups instructions with the part of the state they operate on,
- declarative in which the programmer merely declares properties of the desired result, but not how to compute it
- functional in which the desired result is declared as the value of a series of function applications,
- logic in which the desired result is declared as the answer to a question about a system of facts and rules,
- mathematical in which the desired result is declared as the solution of an optimization problem
- reactive in which the desired result is declared with data streams and the propagation of change
Six programming paradigms that will change how you think about coding
Practice Carbon Programming Language at Hackerrank or LeetCode or FreeCodeCamp
Leetcode and HackerRank coding tests don’t work in developer interviews.
Here’s the proof:
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Research has shown that work sample tests are VERY effective at determining if someone will we a good fit for a job. But here’s the problem: Work sample tests require applicants to perform tasks or work activities that mirror the tasks employees perform on the job.
When was the last time you had to “reverse an integer” or “find the longest substring without repeating characters”. These types of tests don’t mirror the tasks that software developers perform on the job.
AI- Powered Jobs Interview Warmup For Job Seekers
⚽️Comparative Analysis: Top Calgary Amateur Soccer Clubs – Outdoor 2025 Season (Kids' Programs by Age Group)
It’s like testing an architect by having them build a house out of playing cards. Leetcode problems are just brain teasers.
If you want to administer a work sample test, have them do a code review, build a tiny feature in your product, or read and explain some part of your product code. (Every developer knows 90% of your time is spent reading code.)
AI Jobs and Career
And before we wrap up today's AI news, I wanted to share an exciting opportunity for those of you looking to advance your careers in the AI space. You know how rapidly the landscape is evolving, and finding the right fit can be a challenge. That's why I'm excited about Mercor – they're a platform specifically designed to connect top-tier AI talent with leading companies. Whether you're a data scientist, machine learning engineer, or something else entirely, Mercor can help you find your next big role. If you're ready to take the next step in your AI career, check them out through my referral link: https://work.mercor.com/?referralCode=82d5f4e3-e1a3-4064-963f-c197bb2c8db1. It's a fantastic resource, and I encourage you to explore the opportunities they have available.
Developers are tired of Leetcode interviews. It’s time to stop wasting everyone’s time.
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Malbolge 2022 2023
RegEx is just Malbolge for Strings:
What is the hardest programming language? For me, I say C++, C, and Malbolge. Out of all of these, Malbolge is the hardest
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Z-Library. The world’s largest ebook library
Top 50 Programming Languages Ranked by the Number of Influenced Languages
Programming Breaking News and Quiz
- Love and Hate and Agents
by /u/More-Literature-1053 (programming) on March 7, 2026 at 8:18 pmA bloody-knuckles account of AI-adoption from an experienced Rust developer. submitted by /u/More-Literature-1053 [link] [comments]
- He Wrote 200 Lines of Code and Walked Away (What happened Next will blow your Mind)
by Ship X/ TechX (Programming on Medium) on March 7, 2026 at 8:08 pmNo human input. Zero manual commits. Just a script waking up every 8 hours, reading its own source code, and evolving.Continue reading on Techx_official »
- Why Your Containers Die Silently (And How Health Checks Save Them)by Teguhwin (Programming on Medium) on March 7, 2026 at 8:02 pm
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by STARYLX (Programming on Medium) on March 7, 2026 at 7:43 pmThe Expression And Embodiment Of DivinityContinue reading on Medium »
- Why developers using AI are working longer hoursby /u/Inner-Chemistry8971 (programming) on March 7, 2026 at 7:42 pm
I find this interesting. The articles states that, "AI tools don’t automatically shorten the workday. In some workplaces, studies suggest, AI has intensified pressure to move faster than ever." submitted by /u/Inner-Chemistry8971 [link] [comments]
- How I Won the MTD Marathon 2026 — Building a Personal Diary App in Just 4 Hours
by M B GIRISH (Programming on Medium) on March 7, 2026 at 7:39 pmIntroduction :Continue reading on Medium »
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- Building a Powerful AI Coding Environment Without Enterprise Infrastructure
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- Cooperative super(): Writing Python Methods That Chain Across Unrelated Classes
by Tihomir Manushev (Programming on Medium) on March 7, 2026 at 7:29 pmNot every method in a class needs to call super() — and the ones that don’t, reshape the entire activation sequenceContinue reading on Medium »
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by Smitasubudhi (Programming on Medium) on March 7, 2026 at 7:29 pmImagine an office where every employee has a different role. Some employees handle calculations, some assign tasks, some compare reports…Continue reading on Medium »
- Every Feature Needs One Thing Before Release: Alerts
by Nitin Agrawal (Programming on Medium) on March 7, 2026 at 7:21 pmImagine shipping a feature you’re proud of — polished UI, solid unit tests, code reviewed twice — only to find out three days later that…Continue reading on Medium »
- Stop Lying to Your Tests: Real Infrastructure Testing with Testcontainers in Spring Bootby /u/kharamdau (programming) on March 7, 2026 at 6:33 pm
An article about why integration tests that run against H2 often miss production issues and how running tests against real infrastructure with Testcontainers can improve reliability in Spring Boot services. submitted by /u/kharamdau [link] [comments]
- How to Decode a VIN in JavaScriptby /u/Kitchen-Suit9362 (programming) on March 7, 2026 at 5:34 pm
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- I couldn't find a benchmark testing WebFlux + R2DBC vs Virtual Threads on a real auth workload, so I benchmarked itby /u/Lightforce_ (programming) on March 7, 2026 at 3:50 pm
Been going back and forth on this for a while. The common wisdom these days is "just use Virtual Threads, reactive is dead", and honestly it's hard to argue against the DX argument. But I kept having this nagging feeling that for workloads mixing I/O and heavy CPU (think: DB query -> BCrypt verify -> JWT sign), the non-blocking model might still have an edge that wasn't showing up in the benchmarks I could find. The usual suspects all had blind spots for my use case: TechEmpower is great but it's raw CRUD throughput, chrisgleissner's loom-webflux-benchmarks (probably the most rigorous comparison out there) simulates DB latency with artificial delays rather than real BCrypt, and the Baeldung article on the topic is purely theoretical. None of them tested "what happens when your event-loop is free during the DB wait, but then has to chew through 100ms of BCrypt right after". So I built two identical implementations of a Spring Boot account service and hammered them with k6. The setup Stack A: Spring WebFlux + R2DBC + Netty Stack B: Spring MVC + Virtual Threads + JDBC + Tomcat i9-13900KF, 64GB DDR5, OpenJDK 25.0.2 (Temurin), PostgreSQL local with Docker 50 VUs, 2-minute steady state, runs sequential (no resource sharing between the two) 50/50 deterministic VU split between two scenarios Scenario 1 - Pure CPU: BCrypt hash (cost=10), zero I/O WebFlux offloads to Schedulers.boundedElastic() so it doesn't block the event-loop. VT just runs directly on the virtual thread. WebFlux VT median 62ms 55ms p(95) 69ms 71ms max 88ms 125ms Basically a draw. VT wins slightly on median because there's no dispatch overhead. WebFlux wins on max because boundedElastic() has a larger pool to absorb spikes when 50 threads are all doing BCrypt simultaneously. Nothing surprising here, BCrypt monopolizes a full thread in both models, no preemption possible in Java. Scenario 2 - Real login: SELECT + BCrypt verify + JWT sign WebFlux VT median 80ms 96ms p(90) 89ms 110ms p(95) 94ms 118ms max 221ms 245ms WebFlux wins consistently, −20% on p(95). The gap is stable across all percentiles. My read on why: R2DBC releases the event-loop immediately during the SELECT, so the thread is free for other requests while waiting on Postgres. With JDBC+VT, the virtual thread does get unmounted from its carrier thread during the blocking call, but the remounting + synchronization afterward adds a few ms. BCrypt then runs right after, so that small overhead gets amplified consistently on every single request. Small note: VT actually processed 103 more requests than WebFlux in that scenario (+0.8%) while showing higher latency, which rules out "WebFlux wins because it was under less pressure". The 24ms gap is real. Overall throughput: 123 vs 121 req/s. Zero errors on both sides. Caveats (and I think these matter): Local DB, same machine. With real network latency, R2DBC's advantage would likely be more pronounced since there's more time freed on the event-loop per request Only 50 VUs, at 500+ VUs the HikariCP pool saturation would probably widen the gap further Single run each, no confidence intervals BCrypt is a specific proxy for "heavy CPU", other CPU-bound ops might behave differently Takeaway If your service is doing "I/O wait then heavy CPU" in a tight loop, the reactive model still has a measurable latency advantage at moderate load, even in 2026. If it's pure CPU or light I/O, Virtual Threads are equivalent and the simpler programming model wins hands down. Full report + methodology + raw k6 JSON: https://gitlab.com/RobinTrassard/codenames-microservices/-/blob/account-java-version/load-tests/results/BENCHMARK_REPORT.md submitted by /u/Lightforce_ [link] [comments]
- AMD GAIA 0.16 introduces C++17 agent framework for building AI PC agents in pure C++by /u/Fcking_Chuck (programming) on March 7, 2026 at 3:25 pm
submitted by /u/Fcking_Chuck [link] [comments]
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An amazing resource on the implementation details of one of the very best DBs! submitted by /u/BinaryIgor [link] [comments]
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What are the Greenest or Least Environmentally Friendly Programming Languages?
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What are popular hobbies among Software Engineers?
