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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]
- DevOps Engineer, India, Contract [$90/hour]
- 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 |
| Finance Expert | Contract | $150 / hour |
| Designers | Contract | $50 - $70 / hour |
| Chemistry Expert (PhD) | Contract | $60 - $80 / hour |
What is the single most influential book every Programmers should read
There are a lot of books that can be influential to programmers. But, what is the one book that every programmer should read? This is a question that has been asked by many, and it is still up for debate. However, there are some great contenders for this title. In this blog post, we will discuss three possible books that could be called the most influential book for programmers. So, what are you waiting for? Keep reading to find out more!
- Bjarne Stroustrup – The C++ Programming Language,
- Brian W. Kernighan, Rob Pike – The Practice of Programming,
- Donald Knuth – The Art of Computer Programming,
- Ellen Ullman – Close to the Machine,
- Ellis Horowitz – Fundamentals of Computer Algorithms,
- Eric Raymond – The Art of Unix Programming,
- Gerald M. Weinberg – The Psychology of Computer Programming,
- James Gosling – The Java Programming Language,
- Joel Spolsky – The Best Software Writing I,
- Keith Curtis – After the Software Wars,
- Richard M. Stallman – Free Software, Free Society,
- Richard P. Gabriel – Patterns of Software,
- Richard P. Gabriel – Innovation Happens Elsewhere,
- Code Complete (2nd edition) by Steve McConnell,
- The Pragmatic Programmer,
- Structure and Interpretation of Computer Programs,
- The C Programming Language by Kernighan and Ritchie,
- Introduction to Algorithms by Cormen, Leiserson, Rivest & Stein,
- Design Patterns by the Gang of Four,
- Refactoring: Improving the Design of Existing Code,
- The Mythical Man Month,
- The Art of Computer Programming by Donald Knuth,
- Compilers: Principles, Techniques and Tools by Alfred V. Aho, Ravi Sethi and Jeffrey D. Ullman,
- Gödel, Escher, Bach by Douglas Hofstadter,
- Clean Code: A Handbook of Agile Software Craftsmanship by Robert C. Martin,
- Effective C++,
- More Effective C++,
- CODE by Charles Petzold,
- Programming Pearls by Jon Bentley,
- Working Effectively with Legacy Code by Michael C. Feathers,
- Peopleware by Demarco and Lister
- Coders at Work by Peter Seibel,
- Surely You’re Joking, Mr. Feynman!,
- Effective Java 2nd edition,
- Patterns of Enterprise Application Architecture by Martin Fowler,
- The Little Schemer,
- The Seasoned Schemer,
- Why’s (Poignant) Guide to Ruby,
- The Inmates Are Running The Asylum: Why High Tech Products Drive Us Crazy and How to Restore the Sanity,
- The Art of Unix Programming,
- Test-Driven Development: By Example by Kent Beck,
- Practices of an Agile Developer,
- Don’t Make Me Think,
- Agile Software Development, Principles, Patterns, and Practices by Robert C. Martin,
- Domain Driven Designs by Eric Evans,
- The Design of Everyday Things by Donald Norman,
- Modern C++ Design by Andrei Alexandrescu,
- Best Software Writing I by Joel Spolsky,
- The Practice of Programming by Kernighan and Pike,
- Pragmatic Thinking and Learning: Refactor Your Wetware by Andy Hunt,
- Software Estimation: Demystifying the Black Art by Steve McConnel,
- The Passionate Programmer (My Job Went To India) by Chad Fowler,
- Hackers: Heroes of the Computer Revolution,
- Algorithms + Data Structures = Programs,
- Writing Solid Code,
- JavaScript – The Good Parts,
- Getting Real by 37 Signals,
- Foundations of Programming by Karl Seguin,
- Computer Graphics: Principles and Practice in C (2nd Edition),
- Thinking in Java by Bruce Eckel,
- The Elements of Computing Systems,
- Refactoring to Patterns by Joshua Kerievsky,
- Modern Operating Systems by Andrew S. Tanenbaum,
- The Annotated Turing,
- Things That Make Us Smart by Donald Norman,
- The Timeless Way of Building by Christopher Alexander,
- The Deadline: A Novel About Project Management by Tom DeMarco,
- The C++ Programming Language (3rd edition) by Stroustrup,
- Patterns of Enterprise Application Architecture,
- Computer Systems – A Programmer’s Perspective,
- Agile Principles, Patterns, and Practices in C# by Robert C. Martin,
- Growing Object-Oriented Software, Guided by Tests,
- Framework Design Guidelines by Brad Abrams,
- Object Thinking by Dr. David West,
- Advanced Programming in the UNIX Environment by W. Richard Stevens,
- Hackers and Painters: Big Ideas from the Computer Age,
- The Soul of a New Machine by Tracy Kidder,
- CLR via C# by Jeffrey Richter,
- The Timeless Way of Building by Christopher Alexander,
- Design Patterns in C# by Steve Metsker,
- Alice in Wonderland by Lewis Carol,
- Zen and the Art of Motorcycle Maintenance by Robert M. Pirsig,
- About Face – The Essentials of Interaction Design,
- Here Comes Everybody: The Power of Organizing Without Organizations by Clay Shirky,
- The Tao of Programming,
- Computational Beauty of Nature,
- Writing Solid Code by Steve Maguire,
- Philip and Alex’s Guide to Web Publishing,
- Object-Oriented Analysis and Design with Applications by Grady Booch,
- Effective Java by Joshua Bloch,
- Computability by N. J. Cutland,
- Masterminds of Programming,
- The Tao Te Ching,
- The Productive Programmer,
- The Art of Deception by Kevin Mitnick,
- The Career Programmer: Guerilla Tactics for an Imperfect World by Christopher Duncan,
- Paradigms of Artificial Intelligence Programming: Case studies in Common Lisp,
- Masters of Doom,
- Pragmatic Unit Testing in C# with NUnit by Andy Hunt and Dave Thomas with Matt Hargett,
- How To Solve It by George Polya,
- The Alchemist by Paulo Coelho,
- Smalltalk-80: The Language and its Implementation,
- Writing Secure Code (2nd Edition) by Michael Howard,
- Introduction to Functional Programming by Philip Wadler and Richard Bird,
- No Bugs! by David Thielen,
- Rework by Jason Freid and DHH,
- JUnit in Action
Source: Wikipedia

What are the concepts every Java C# C++ Python Rust programmer must know?
Ok…I think this is one of the most important questions to answer. According to the my personal experience as a Programmer, I would say you must learn following 5 universal core concepts of programming to become a successful Java programmer.
(1) Mastering the fundamentals of Java programming Language – This is the most important skill that you must learn to become successful java programmer. You must master the fundamentals of the language, specially the areas like OOP, Collections, Generics, Concurrency, I/O, Stings, Exception handling, Inner Classes and JVM architecture.
Recommended readings are OCA Java SE 8 Programmer by by Kathy Sierra and Bert Bates (First read Head First Java if you are a new comer ) and Effective Java by Joshua Bloch.
(2) Data Structures and Algorithms – Programming languages are basically just a tool to solve problems. Problems generally has data to process on to make some decisions and we have to build a procedure to solve that specific problem domain. In any real life complexity of the problem domain and the data we have to handle would be very large. That’s why it is essential to knowing basic data structures like Arrays, Linked Lists, Stacks, Queues, Trees, Heap, Dictionaries ,Hash Tables and Graphs and also basic algorithms like Searching, Sorting, Hashing, Graph algorithms, Greedy algorithms and Dynamic Programming.
Recommended readings are Data Structures & Algorithms in Java by Robert Lafore (Beginner) , Algorithms Robert Sedgewick (intermediate) and Introduction to Algorithms-MIT press by CLRS (Advanced).
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(3) Design Patterns – Design patterns are general reusable solution to a commonly occurring problem within a given context in software design and they are absolutely crucial as hard core Java Programmer. If you don’t use design patterns you will write much more code, it will be buggy and hard to understand and refactor, not to mention untestable and they are really great way for communicating your intent very quickly with other programmers.
Recommended readings are Head First Design Patterns Elisabeth Freeman and Kathy Sierra and Design Patterns: Elements of Reusable by Gang of four.
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(4) Programming Best Practices – Programming is not only about learning and writing code. Code readability is a universal subject in the world of computer programming. It helps standardize products and help reduce future maintenance cost. Best practices helps you, as a programmer to think differently and improves problem solving attitude within you. A simple program can be written in many ways if given to multiple developers. Thus the need to best practices come into picture and every programmer must aware about these things.
Recommended readings are Clean Code by Robert Cecil Martin and Code Complete by Steve McConnell.
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.
(5) Testing and Debugging (T&D) – As you know about the writing the code for specific problem domain, you have to learn how to test that code snippet and debug it when it is needed. Some programmers skip their unit testing or other testing methodology part and leave it to QA guys. That will lead to delivering 80% bugs hiding in your code to the QA team and reduce the productivity and risking and pushing your project boundaries to failure. When a miss behavior or bug occurred within your code when the testing phase. It is essential to know about the debugging techniques to identify that bug and its root cause.
Recommended readings are Debugging by David Agans and A Friendly Introduction to Software Testing by Bill Laboon.
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I hope these instructions will help you to become a successful Java Programmer. Here i am explain only the universal core concepts that you must learn as successful programmer. I am not mentioning any technologies that Java programmer must know such as Spring, Hibernate, Micro-Servicers and Build tools, because that can be change according to the problem domain or environment that you are currently working on…..Happy Coding!
Summary: There’s no doubt that books have had a profound influence on society and the advancement of human knowledge. But which book is the most influential for programmers? Some might say it’s The Art of Computer Programming, or The Pragmatic Programmer. But I would argue that the most influential book for programmers is CODE: The Hidden Language of Computer Hardware and Software. In CODE, author Charles Petzold takes you on a journey from the basics of computer hardware to the intricate workings of software. Along the way, you learn how to write code in Assembly language, and gain an understanding of how computers work at a fundamental level. If you’re serious about becoming a programmer, then CODE should be at the top of your reading list!
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submitted by /u/creaturefeature16 [link] [comments]
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I’ve been experimenting with a workflow for making coding-agent runs more observable. Instead of asking an agent to summarize a repo, the system runs the agent in a sandbox against a GitHub repo and records the actual terminal/browser session. The result is a replayable video of what happened: setup, failures, retries, browser state, and final output. The motivation is that text summaries from agents hide a lot. For repo evaluation, the path matters as much as the final answer. High-level flow: GitHub repo → sandbox → agent run → terminal/browser recording → processed replay Demo: https://www.trymyrepo.com Architecture notes: https://www.trymyrepo.com/how-it-works Planning to open source it next week. Curious if people here think this kind of “visual evidence” is useful for agent workflows, or if logs/traces are enough. submitted by /u/delecioushelix [link] [comments]
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OP here. I'm trying out a new interactive way to teach complex concepts. What do you think of the style? How about content, could you follow along okay? submitted by /u/CarbonFire [link] [comments]
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- I built a world record exact solver for the minimum line cover of prime points after watching a Numberphile video. It turned the previous 282-hour record into 22 minutes, then kept going to prove 20 new awkward primes never certified before.by /u/jespergran (programming) on May 12, 2026 at 5:27 pm
After watching a Numberphile video on "awkward primes" I fell down a rabbit hole that turned into a month of obsessive C++ optimisation. The problem: Plot the first N primes as points on a graph — the 1st prime (2) at position 1, the 2nd prime (3) at position 2, and so on. What is the minimum number of straight lines needed to pass through every point? Proving you've truly found the minimum is the hard part — it's an NP-complete set cover problem, and it gets exponentially harder as N grows. The previous record stood at N=861, certified by Max Alekseyev (GWU) using an industrial MIP solver in 282 hours. The solver replaces the MIP approach with an arithmetic-aware incremental architecture: 12,162 "heavy lines" (through 3+ primes) stored as 1024-bit bitmasks, keeping the full working set L2-resident 60% of steps certified instantly via witness propagation with no search at all Lagrangian relaxation with projected subgradient descent for tight lower bounds Parallel branch-and-bound with an Exclusive Dependency Rule that provably forces required lines without branching The results: N=861 reached in 22 minutes. Full sweep to N=1024 completed in under 40 hours, certifying f(1024)=143 and finding 20 new awkward primes. Full paper, MIT-licensed C++ source, and a live browser demo that runs the actual algorithm in real time are all at the link above. For the OEIS people: https://oeis.org/A373813 submitted by /u/jespergran [link] [comments]
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massive campaign for 170+ packages and 400+ malicious versions published. what we saw that not a single maintainer account compromised. tanStack and Mistral AI these are the names that stand out. submitted by /u/BattleRemote3157 [link] [comments]
- Looking for feedback on AI content in r/programming and the April no-AI trialby /u/ketralnis (programming) on May 5, 2026 at 6:41 pm
Hello fellow programs! In April we tried out a complete ban on LLM-related content. Today we're asking for feedback on how that went, and more generally what we want to do about this kind of content. Please comment below, but if all you're going to say is "I liked/hated it", please also indicate that you've read the nuance below. To be clear we always have and will continue to ban content that's generated by an LLM. If you don't want to write it, we don't want to read it. And we also do and will continue to ban content that's not related to programming but about e.g. philosophy in AI or jailbreaking chatgpt. (Non-programming AI articles account for most of the AI-related content that we see and we remove quite a lot of them. This is not related to the April trial.) So the nuance is that the only additional category of content that we banned in the April trial and are asking about here is programming content that is about AI. This ranges from: mathematical techniques in machine learning ("using transformer techniques for sequence prediction") techniques for using LLMs at runtime within a small codebase production model deployment and testing architectures experience reports or configuration tips with Cursor best practises for prompting how we secure our AI generated codebase hey guise I just discovered vibe coding will AI replace programmers i am surely the first person to ask this how to glue an LLM to your business data synergisting agentic blockchains in a mobile social local world: a tedx talk featuring one line of code on the last slide You can see that we've struggled with what to do about the various categories for a while and have moved around in our approach and we'll probably do that for a while yet. I don't want to go banning every faddy thing that's briefly so popular as to be annoying but we also need to be careful with the content that we allow because it's what drives future submitters, so it can be self feeding. This topic also brings out the rabid fans and detractors alike, so it's easy to get lost in a vocal minority. (For that reason I'm not going to pretend that this is a fully democratic decision where we add up the vote counts or something: people are too willing to brigade on this stuff and we'll keep some subjectivity to avoid that.) At some point I believe these tools will be discussed as simply as we discuss compilers or OOP or GC or VX Modules, but currently the hype and doomerism are so rabidly partisan that it's hard to find honest examples. Note that a confounding influence is that in the last month or so the new mods really got ramped up. I was removing things like that before but on a large delay, whereas now we're better able to enforce the rules we already had. So if what you're annoyed by is "will AI replace programmers?", be aware that this has no effect on that. We already remove it. All of that said, we want to gather ideas and feedback on how we can best handle these categories of content and suggestions for how to draw the lines so we can meet our mission to be the place with the highest quality programming content, where I can go to read something interesting and learn something new every day. submitted by /u/ketralnis [link] [comments]




































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