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AI Jobs and Career
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- Full Stack Engineer [$150K-$220K]
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- More AI Jobs Opportunitieshere
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|---|---|---|
| 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 |
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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.
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⚽️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
- The context window problem nobody talks about - how do you persist learning across AI sessions?
by /u/Main_Payment_6430 (programming) on January 15, 2026 at 2:30 pmWorking on a side project and hit an interesting architectural question. Every AI chat is stateless. You start fresh, explain your codebase, your conventions, your preferences, then 2 hours later you start a new session and do it all over again. The model learned nothing permanent. ChatGPT added memory but its capped and global. Claude has something similar with the same limits. Neither lets you scope context to specific projects. From a technical standpoint the obvious solutions are either stuffing relevant context into the system prompt every request, or doing RAG with embeddings to pull relevant memories dynamically. System prompt stuffing is simple but doesnt scale. RAG adds latency and complexity for what might be overkill in most cases. Anyone building tools that interact with LLMs regularly - how are you handling persistent context? Is there a middle ground between dumb prompt injection and full vector search that actually works well in practice? Curious what patterns people have landed on. submitted by /u/Main_Payment_6430 [link] [comments]
- Where do you fall on the Agentic Coder Spectrum? I mapped out 5 levels of AI adoption among developers!by /u/PuzzleheadedAd7828 (programming) on January 15, 2026 at 2:23 pm
I've been noticing a huge gap between what you see on social media (everyone apparently orchestrating multi-agent workflows) and what most developers I talk to actually do. So I tried to map out the different levels of AI adoption I'm seeing: Conversationalists — ask ChatGPT/Claude questions, copy-paste code, workflow unchanged Copilots — use Cursor/Copilot/Windsurf for autocomplete, still write most code Prompt Engineers — describe what they want, run single agents, review generated code, occasionally write manually Orchestrators — run multiple agents in parallel, rarely write code themselves Systems Designers — design processes and feedback loops, agents do all implementation Would love to know from all of you where you are seeing yourself! submitted by /u/PuzzleheadedAd7828 [link] [comments]
- Pythons certification & fosters Career Advancement:
by Selinemir (Programming on Medium) on January 15, 2026 at 2:10 pmAdvance your career with a Python designed for development and leadership, offering financial aid, scholarship programs, & flexible…Continue reading on Medium »
- Components vs Directives and Their Practical Usage
by Smart Tech Circuit (Programming on Medium) on January 15, 2026 at 2:10 pmI still remember the first time I confidently said, “We should make this a component.”Continue reading on Medium »
- Angular Framework Architecture and Core Building Blocks
by Smart Tech Circuit (Programming on Medium) on January 15, 2026 at 2:06 pmThe first time I thought I understood Angular, my app still froze on a simple button click. No errors. No warnings. Just silence. That’s…Continue reading on Medium »
- B-Trees vs. LSM-Trees: Why Your Choice of DB is Failing
by Tech&Talk (Programming on Medium) on January 15, 2026 at 2:02 pmYou picked PostgreSQL because it’s “battle-tested.” Now your write workload is melting your disk budget.Continue reading on Medium »
- The Real Difference Between npm, npx, and pnpm
by Asanka Dilshan (Programming on Medium) on January 15, 2026 at 1:58 pmFor a long time, I used npm, npx, and pnpm almost every day.Continue reading on Medium »
- Short-Link Chaining as a Traceability Failureby 3gi3 (Programming on Medium) on January 15, 2026 at 1:56 pm
A Structural Analysis of Redirect Chains and Abuse PotentialContinue reading on Medium »
- Mastering Cairo Iterators
by Eric Nordelo (Programming on Medium) on January 15, 2026 at 1:50 pmCleaner code. Lower gas. Here’s how.Continue reading on Medium »
- Data Pipelines Explained: From Raw Data to Real-Time Insights (The Ultimate Guide) ⚙️
by Lakhveer Singh Rajput (Programming on Medium) on January 15, 2026 at 1:49 pmIn today’s data-driven world, data is the new oil — but raw data is useless unless refined. That refinement process is done through Data…Continue reading on Medium »
- How to Make Architecture Decisions: RFCs, ADRs, and Getting Everyone Alignedby /u/trolleid (programming) on January 15, 2026 at 1:45 pm
submitted by /u/trolleid [link] [comments]
- A Beginner’s Honest Guide to Ethical Hacking With Python
by Vignesh Selvaraj (Programming on Medium) on January 15, 2026 at 1:41 pmA Practical, Beginner-Friendly Approach to Ethical HackingContinue reading on Activated Thinker »
- Factory Functions: A Simple and Practical Guideby Yousaf Maaz (Programming on Medium) on January 15, 2026 at 1:41 pm
When building software, one of the most common tasks is creating objects. In JavaScript and many backend systems, there are multiple ways…Continue reading on Medium »
- Why forcing a developer to take time off actually helpedby /u/dymissy (programming) on January 15, 2026 at 1:12 pm
submitted by /u/dymissy [link] [comments]
- Spring Then & Now: What’s Next? • Rod Johnson, Arjen Poutsma & Trisha Geeby /u/goto-con (programming) on January 15, 2026 at 1:05 pm
submitted by /u/goto-con [link] [comments]
- BOPLA: Why Protecting the Object ID Isn't Enough (Broken Object Property Level Authorization)by /u/JadeLuxe (programming) on January 15, 2026 at 11:48 am
submitted by /u/JadeLuxe [link] [comments]
- Nature vs Golang: Performance Benchmarkingby /u/hualaka (programming) on January 15, 2026 at 11:43 am
I am the author of the nature programming language and you can ask me questions. submitted by /u/hualaka [link] [comments]
- Programmer in Wonderlandby /u/BinaryIgor (programming) on January 15, 2026 at 11:00 am
Hey Devs, Do not become The Lost Programmer in the bottomless ocean of software abstractions, especially with the recent advent of AI-driven hype; instead, focus on the fundamentals, make the magic go away and become A Great One! submitted by /u/BinaryIgor [link] [comments]
- Responsible disclosure of a Claude Cowork vulnerability that lets hidden prompt injections exfiltrate local files by uploading them to an attacker’s Anthropic accountby /u/sean-adapt (programming) on January 15, 2026 at 10:37 am
From the article: Two days ago, Anthropic released the Claude Cowork research preview (a general-purpose AI agent to help anyone with their day-to-day work). In this article, we demonstrate how attackers can exfiltrate user files from Cowork by exploiting an unremediated vulnerability in Claude’s coding environment, which now extends to Cowork. The vulnerability was first identified in Claude.ai chat before Cowork existed by Johann Rehberger, who disclosed the vulnerability — it was acknowledged but not remediated by Anthropic. submitted by /u/sean-adapt [link] [comments]
- Multi-Claude for claude-coding in parallelby /u/Money_Warthog6133 (programming) on January 15, 2026 at 10:36 am
Hey everyone, I've been using Claude Code a lot lately and kept running into the same problem: I wanted to work on multiple features simultaneously, each with its own Claude instance, but switching branches and contexts was a pain. So I built Multi-Claude - a desktop app that combines git worktrees with multiple terminal sessions. And yes, the entire thing was built using Claude Code itself. The problem it solves: When you're deep into a feature with Claude and suddenly need to fix a bug on another branch, you either have to stash everything, switch branches, lose your Claude context... or just wait. With worktrees, each branch lives in its own directory, so you can run multiple Claude sessions in parallel without any conflicts. What it does: - Opens any git repo and lists all your worktrees - Create new worktrees directly from the UI - Multiple terminals per worktree with split panes (horizontal/vertical) - Drag & drop to rearrange terminal layouts - Automatically detects when a terminal is running Claude Code - Full terminal emulation (not just a basic shell) Tech stack: Electron + React + TypeScript + xterm.js + node-pty GitHub: https://github.com/LaurentMnr95/multi-claude It's pretty bare-bones right now but functional. Here's what's on the roadmap: - Recent repos memory (reopen where you left off) - Color themes - Delete worktrees from the UI - Remote status (ahead/behind indicators) - Notifications when Claude finishes a task - Open in external editor (VS Code, Cursor, etc.) - Keyboard shortcuts Refactoring to styled components Would love feedback on what features to prioritize. submitted by /u/Money_Warthog6133 [link] [comments]
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How do we know that the Top 3 Voice Recognition Devices like Siri Alexa and Ok Google are not spying on us?
What are popular hobbies among Software Engineers?
