Vivek Sharma

Passionate about software quality, automation and outdoor sports

[JER @lifeof_jer]

https://t.co/ofucbVgkLV

[Boris Cherny @bcherny]

I'm Boris and I created Claude Code. Lots of people have asked how I use Claude Code, so I wanted to show off my setup a bit.

My setup might be surprisingly vanilla! Claude Code works great out of the box, so I personally don't customize it much. There is no one correct way to use Claude Code: we intentionally build it in a way that you can use it, customize it, and hack it however you like. Each person on the Claude Code team uses it very differently.

So, here goes.

[Christian H. Cooper @christiancooper]

@karpathy Teachers should lean into it. Use tools like this to create better learning environments. Testing itself likely changes too.

https://t.co/K6KXaCtPQ5

[Andrej Karpathy @karpathy]

A number of people are talking about implications of AI to schools. I spoke about some of my thoughts to a school board earlier, some highlights:

1. You will never be able to detect the use of AI in homework. Full stop. All "detectors" of AI imo don't really work, can be defeated in various ways, and are in principle doomed to fail. You have to assume that any work done outside classroom has used AI.
2. Therefore, the majority of grading has to shift to in-class work (instead of at-home assignments), in settings where teachers can physically monitor students. The students remain motivated to learn how to solve problems without AI because they know they will be evaluated without it in class later.
3. We want students to be able to use AI, it is here to stay and it is extremely powerful, but we also don't want students to be naked in the world without it. Using the calculator as an example of a historically disruptive technology, school teaches you how to do all the basic math & arithmetic so that you can in principle do it by hand, even if calculators are pervasive and greatly speed up work in practical settings. In addition, you understand what it's doing for you, so should it give you a wrong answer (e.g. you mistyped "prompt"), you should be able to notice it, gut check it, verify it in some other way, etc. The verification ability is especially important in the case of AI, which is presently a lot more fallible in a great variety of ways compared to calculators.
4. A lot of the evaluation settings remain at teacher's discretion and involve a creative design space of no tools, cheatsheets, open book, provided AI responses, direct internet/AI access, etc.

TLDR the goal is that the students are proficient in the use of AI, but can also exist without it, and imo the only way to get there is to flip classes around and move the majority of testing to in class settings.

[Venkat Subramaniam @venkat_s]

If your job is mostly typing code that part of the job will disappear.

If it’s mostly problem solving, decision making, inferring context, leveraging proper tools to accomplish those, then delivering results will be further enriching moving forward.

Skill up, don’t fear down.

[anand mahindra @anandmahindra]

If I was his opponent, I would cry foul & file a suit claiming that I was confronted by an unnatural opponent who possessed three arms…

😳

👍🏽💪🏽🇮🇳

https://t.co/4p5EsPNxyV

[Johns. @CricCrazyJohns]

Cartwheel celebration by Kevin Sinclair after taking his first Test wicket. 🔥🤯

[Andrej Karpathy @karpathy]

New YouTube video: 1hr general-audience introduction to Large Language Models
https://t.co/Bl4WNuNyFJ

Based on a 30min talk I gave recently; It tries to be non-technical intro, covers mental models for LLM inference, training, finetuning, the emerging LLM OS and LLM Security.

[Rowan Cheung @rowancheung]

OpenAI's custom GPTs are taking over.

I built a directory to find the best GPTs and got OVER 500+ submissions in 24 hrs.

The top 10 community favorites so far:

[Java Guides @GuidesJava]

Java Versions:

[Dr Milan Milanović @milan_milanovic]

𝗕𝗼𝗼𝗸𝘀 𝗘𝘃𝗲𝗿𝘆 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝗠𝘂𝘀𝘁 𝗥𝗲𝗮𝗱 𝗶𝗻 𝟮𝟬𝟮𝟯.

You probably already noticed that I'm a big fan of reading. I usually read 3-4 books per month. You can learn from knowledgeable people in two ways: to work directly with them or to read what they have written. The first is the best option, yet it is often impossible. We have books written by people who are probably the best at this in the world at the time of writing.

If we look at the software engineering world, there are many gems here, but here I will recommend the best books per area of work:

𝟭. 𝗚𝗲𝗻𝗲𝗿𝗮𝗹:
🔹 The Pragmatic Programmer by David Thomas and Andrew Hunt (https://t.co/NCSpr3ZhGb)
🔹 Modern Software Engineering by David Farley (https://t.co/2X5eWCHcni)

𝟮. 𝗖𝗼𝗱𝗶𝗻𝗴 𝗽𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀:

🔹 Clean Code by Uncle Bob Martin (https://t.co/4Ml52XBKKb)
🔹 Head First Design Patterns by Eric Freeman (https://t.co/4jXkPd8vcK)
🔹 Refactoring by Martin Fowler (https://t.co/8fbR93LNy0)

𝟯. 𝗗𝗮𝘁𝗮 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝘀 𝗮𝗻𝗱 𝗮𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺𝘀:

🔹 Grokking Algorithms by Aditya Bhargava (https://t.co/1q2hWfaONO)

𝟰. 𝗗𝗮𝘁𝗮:

🔹 Designing Data-Intensive Applications by Martin Kleppman (https://t.co/2Rtjfs987o)
🔹 Learning SQL by Alan Beaulieu (Free - https://t.co/T6Z4iz3nHN)

𝟱. 𝗧𝗲𝘀𝘁𝗶𝗻𝗴:

🔹 Growing OO Software by Tests by Steve Freeman (https://t.co/joi6Q8nm4W)
🔹 TDD by Example by Kent Beck (https://t.co/IxVGfJymQu)
🔹 Unit Testing Principles, Practices, and Patterns by Vladimir Khorikov (https://t.co/7VyFPkUpZS)
🔹 The Art of Unit Testing by Roy Osherove (https://t.co/rqNoqJH49t).

𝟲. 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲:

🔹 Fundamentals Of Software Architecture by Mark Richards and Neil Ford (https://t.co/LOnF7783bl)
🔹 Clean Architecture by Uncle Bob Martin (https://t.co/fojqHumHo3)
🔹 Software Architecture the Hard Parts (https://t.co/K7AqvDOoSN)
🔹 Domain-Driven Design Distilled by Vaughn Vernon (https://t.co/pT8GZQmrR5)
🔹 A Philosophy of Software Design by John Ousterhout (https://t.co/rBeKHE0w6P)

𝟳. 𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝗱 𝘀𝘆𝘀𝘁𝗲𝗺𝘀:

🔹 Understanding Distributed Systems by Roberto Vitillo (https://t.co/NmApvbFyQj)

𝟴. 𝗗𝗲𝘃𝗢𝗽𝘀:

🔹 DevOps Handbook by Gene Kim (https://t.co/EHmuVxZrKi)
🔹 Continuous Delivery by Jez Humble and David Farley (https://t.co/tePOX3hfs3)
🔹 Accelerate by Nicole Forsgren (https://t.co/HqHfEjAmB4)

𝟵. .𝗡𝗘𝗧/𝗖#:

🔹C# in Depth by Jon Skeet (https://t.co/u4M31XN673)

𝟭𝟬. 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴:

🔹 The Hundred-Page Machine Learning Book (https://t.co/31A2XuGKSR)

𝟭𝟭. 𝗧𝗲𝗮𝗺𝘀:

🔹 The Five Dysfunctions of a Team by Patrick Lencioni (https://t.co/bKS3xhjCQv)
🔹 Drive by Daniel Pink (https://t.co/GVyKMoAkUu)
🔹 Team Topologies by Matthew Skelton and Manuel Pais (https://t.co/KaeDPYurVM).

Should anything else be added to the list?

#technology #softwareengineering #programming #techworldwithmilan #books

[Brij Pandey @brijpandeyji]

✅ Working of Python vs Java
🚀 Java: Bytecode + JIT = Speed ⚡
🐍 Python: Simplicity + Magic
✨ Both titans have their charm! 🔥
.
📌 Don't Forget to save this post for later and follow @brijpandeyji for more such information.

[ANI @ANI]

#WATCH | Haryana: Spiritual jamming by youths outside a cafe in Gurugram.

Youth outside this cafe chant Hanuman Chalisa every Tuesday.

[nixCraft 🐧 @nixcraft]

yes

[RRR Movie @RRRMovie]

And the GOLDEN GLOBE AWARD FOR BEST ORIGINAL SONG Goes to #NaatuNaatu #GoldenGlobes  #GoldenGlobes2023  #RRRMovie

[Programmer Humor @PR0GRAMMERHUM0R]

How inheritance works https://t.co/WmuN9uVIGN

[Alex Xu @alexxubyte]

/1 The CAP theorem is one of the most famous terms in computer science, but I bet different developers have different understandings. Let’s examine what it is and why it can be confusing.

[CCTV_IDIOTS @cctv_idiots]

Engineering masterpiece 👌

[Gianni Cara @giannicara]

Master storytelling and you can print money at will.

Sadly, most people don't know how or where to start.

Here are 5 storytelling frameworks to get you started: