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Mashhood Rastgar

Karachi Wala Developer

A Technology podcast

#46 in Technology · 🇵🇰
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About the show

10 minute weekly ramblings of a software engineer based in Karachi sharing about tech and startups. Recently started a series on Engineering Leaders in Pakistan.

Newest episodes

Software Factories When You're Not an Engineer

2 min

A builder without a technical background asked how to make software factories actually work. My answer is simpler than a better harness: build your understanding as you go. Every instruction is a chance to learn — ask the agent what it did, why, what the alternatives were. Good skills will carry a prototype a long way, but systems that last need you to understand how they're designed. Question: I want to move toward software factories because people talk about them a lot, but I can't seem to use them properly — is it worth it, and how do I build a workflow that makes sense? In this episode: The question: why software factories don't work for a non-technical builder yetStep in with curiosity and a learning mindsetEvery instruction is a chance to learn: what did you do, why, what are the alternatives, pros and cons?Depth comes with time: data models, REST APIs, data storage, encryption, authenticationSkills and a good harness carry a prototype a long way — look at what Matt Pocock and Addy Osmani shareSystems that last need an understanding of system design, and sometimes the codeRelated episodes: The Shifting Role of the Developer: From Writing Code to Writing SpecsFrom Coder to Architect: The Power of the Producer MindsetThe AI Autonomy Paradox: Why Software Engineers Must Unlearn "Control"Agentic Transformation Concept: Progressive DisclosureHave a question? Reach out on LinkedIn or Twitter.

Depth or Breadth? What New Engineers Should Focus On

5 min

A question from a young engineer: should you build depth or breadth in a market nobody can predict? I start with a different question — what kind of work do you actually enjoy? — then walk through where depth still matters (the AI frontier, trillion-dollar systems like Stripe, formal verification) and why breadth roles are becoming outcome-focused. My answer: try both, practise relentlessly, and set outcome-based targets for yourself. Question: Should new software engineers focus on fundamentals or other things — depth or breadth — to succeed in an unpredictable market? In this episode: Start with what kind of work you enjoy — not everyone fits every pathWhy most people will be a better fit for breadth rolesWhere depth lives: model training, security, compute optimisation, and the ML frontierComplex systems at Stripe's scale need domain + technical depth to stay verifiedFormal verification: a new field that will demand depthBreadth = learning new domains fast; roles judged on pure outcomesSales, marketing, product, design — learn them on the go, deploy, get feedbackThe open question: how do juniors build depth when AI does the work?Practice, critical and Socratic thinking, and outcome-based targets apply to both pathsRelated episodes: Are you a T-Shaped Developer?Whats makes a good software engineer?Stop Reviewing Code, Start Reviewing Tests: TDD in the Age of AIThe Shifting Role of the Developer: From Writing Code to Writing SpecsHave a question? Reach out on LinkedIn or Twitter.

What Forward-Deployed Engineering Actually Looks Like

3 min

"Forward-deployed engineer" is the title everyone wants. I share what it actually looked like for me: two weeks sitting in a field office that runs 200 schools, taking phone-call tasks about broken solar panels and missing teachers — and building tools in the afternoons until the coordinator asked to use them. Recorded live at a community session on agentic engineering (Urdu/English). Question: Is forward-deployed engineering a real role — and what does it actually look like? In this episode: FDE is a company engineering role, not a freelance gig — and titles get abusedThe field office story: arrive with a blank slate, do whatever work they hand youBuilding on Replit from 2–6pm, using the tool yourself the next day, gaining your first userTwo intense weeks that ended in a contractRelated episodes: Agentic Transformation: My StoryThe Shifting Role of the Developer: From Writing Code to Writing SpecsHave a question? Reach out on LinkedIn or Twitter.

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All episodes

Software Factories When You're Not an Engineer

2 min

A builder without a technical background asked how to make software factories actually work. My answer is simpler than a better harness: build your understanding as you go. Every instruction is a chance to learn — ask the agent what it did, why, what the alternatives were. Good skills will carry a prototype a long way, but systems that last need you to understand how they're designed. Question: I want to move toward software factories because people talk about them a lot, but I can't seem to use them properly — is it worth it, and how do I build a workflow that makes sense? In this episode: The question: why software factories don't work for a non-technical builder yetStep in with curiosity and a learning mindsetEvery instruction is a chance to learn: what did you do, why, what are the alternatives, pros and cons?Depth comes with time: data models, REST APIs, data storage, encryption, authenticationSkills and a good harness carry a prototype a long way — look at what Matt Pocock and Addy Osmani shareSystems that last need an understanding of system design, and sometimes the codeRelated episodes: The Shifting Role of the Developer: From Writing Code to Writing SpecsFrom Coder to Architect: The Power of the Producer MindsetThe AI Autonomy Paradox: Why Software Engineers Must Unlearn "Control"Agentic Transformation Concept: Progressive DisclosureHave a question? Reach out on LinkedIn or Twitter.

Depth or Breadth? What New Engineers Should Focus On

5 min

A question from a young engineer: should you build depth or breadth in a market nobody can predict? I start with a different question — what kind of work do you actually enjoy? — then walk through where depth still matters (the AI frontier, trillion-dollar systems like Stripe, formal verification) and why breadth roles are becoming outcome-focused. My answer: try both, practise relentlessly, and set outcome-based targets for yourself. Question: Should new software engineers focus on fundamentals or other things — depth or breadth — to succeed in an unpredictable market? In this episode: Start with what kind of work you enjoy — not everyone fits every pathWhy most people will be a better fit for breadth rolesWhere depth lives: model training, security, compute optimisation, and the ML frontierComplex systems at Stripe's scale need domain + technical depth to stay verifiedFormal verification: a new field that will demand depthBreadth = learning new domains fast; roles judged on pure outcomesSales, marketing, product, design — learn them on the go, deploy, get feedbackThe open question: how do juniors build depth when AI does the work?Practice, critical and Socratic thinking, and outcome-based targets apply to both pathsRelated episodes: Are you a T-Shaped Developer?Whats makes a good software engineer?Stop Reviewing Code, Start Reviewing Tests: TDD in the Age of AIThe Shifting Role of the Developer: From Writing Code to Writing SpecsHave a question? Reach out on LinkedIn or Twitter.

What Forward-Deployed Engineering Actually Looks Like

3 min

"Forward-deployed engineer" is the title everyone wants. I share what it actually looked like for me: two weeks sitting in a field office that runs 200 schools, taking phone-call tasks about broken solar panels and missing teachers — and building tools in the afternoons until the coordinator asked to use them. Recorded live at a community session on agentic engineering (Urdu/English). Question: Is forward-deployed engineering a real role — and what does it actually look like? In this episode: FDE is a company engineering role, not a freelance gig — and titles get abusedThe field office story: arrive with a blank slate, do whatever work they hand youBuilding on Replit from 2–6pm, using the tool yourself the next day, gaining your first userTwo intense weeks that ended in a contractRelated episodes: Agentic Transformation: My StoryThe Shifting Role of the Developer: From Writing Code to Writing SpecsHave a question? Reach out on LinkedIn or Twitter.

Is This the Last Era of Software Engineering?

3 min

Every generation of engineers has been told their craft is ending — assembly to C, C to Java, Java to Python. Using the story of photography, I argue AI won't end software engineering; it will turn far more people into builders and change what the job looks like. Recorded live at a community session on agentic engineering (Urdu/English). Question: Do you think this is the last era of software engineering? In this episode: Assembly → C → C++/Java → Python: each shift was called the end of real programmingThe photographer analogy: cameras in every pocket, yet more photographers employed than everBuilders go from ~5% of the world to maybe 40% — imagine how much software that createsThe job changes; it doesn't disappearRelated episodes: LLMs: Are AI Software Engineers ready to take over?The AI Code Revolution: What Developers Need to KnowAgentic Transformation: My StoryThe Shifting Role of the Developer: From Writing Code to Writing SpecsHave a question? Reach out on LinkedIn or Twitter.

The Shifting Role of the Developer: From Writing Code to Writing Specs

16 min

Have you ever asked an AI to build something, only to realize it built the exact wrong thing? AI is incredible at generating code, but it lacks human judgment. In this episode, I share the story of building an internal AI coaching bot called "Jugnu." My first attempt failed completely because I relied on the AI's judgment instead of doing the research myself. I quickly learned that the most successful AI developers spend 90% of their time researching, planning, and writing specs before they ever type a prompt. Join me as we explore how the role of the software engineer is merging with the product manager, the death of "un-used software," and the exact frameworks and tools (like NotebookLM and Superpowers) you can use to master AI-assisted development.

Stop Reviewing Code, Start Reviewing Tests: TDD in the Age of AI

13 min

As AI agents become capable of rewriting entire C compilers and Next.js repositories in days, the value of software is shifting away from the code itself. If LLMs write probabilistic code, how do you guarantee deterministic results? The answer: Tests. In this episode, we argue that developers need to stop agonizing over AI-generated implementation code and instead double down on writing, reviewing, and curating rigorous test suites. Learn why some open-source projects are actually closing their test repos, and how adopting an Architect mindset will unlock true AI autonomy in your workflow.

From Coder to Architect: The Power of the Producer Mindset

9 min

The role of the developer is changing. In this episode, we discuss how to stop being a "consumer" of AI prompts and start becoming a "producer" of AI systems. By shifting your focus from writing code to designing autonomous loops and persistent architectures, you can move up the ladder of value and start steering the future of software development.

The AI Autonomy Paradox: Why Software Engineers Must Unlearn "Control"

8 min

As software engineers, we are trained to control every detail—from code formatting to system architecture. But autonomous AI demands the exact opposite. In this episode, we discuss the "Autonomy Paradox." Learn why enforcing arbitrary rules on AI agents causes them to fail, and how shifting your focus from "how it's built" to "what it achieves" is the key to unlocking next-generation development.

Agentic Transformation Concept: Progressive Disclosure

8 min

If you are dumping your entire codebase into Claude or Gemini and hoping for the best, you are doing it wrong. In today's episode, we tackle Context Engineering. AI agents have short-term memory (the Goldfish Problem) and limited Context Windows. If you fill that window with unnecessary data or heavy MCPs, the AI's performance drops drastically. Tune in to learn how to structure your information using Agent files, Skill files, and Rule files. We also break down advanced strategies like Progressive Disclosure (only giving the AI what it needs, when it needs it) and using Sub-Agents to keep your main context window clean.

Agentic Transformation: My Story

7 min

In this episode, I share a personal story of building an ERP system with AI in the field, and how it forced me to confront the "5 Stages of Grief" as a veteran software developer. The way we have written code for the last 20 years is ending. To survive, we have to unlearn our "deterministic" mindsets and adopt new mental models for a non-deterministic world. Join me as we kick off a brand new series on the foundational literacy required for the future of tech.

GPT-5: Is AGI here?

7 min

Dive into the much-anticipated GPT-5 update. We cut through the hype to analyze OpenAI's latest offering, covering its new unified architecture, efforts to reduce hallucinations, enhanced memory, and the controversial decision to deprecate GPT-4. Is GPT-5 the leap towards AGI we've been promised, or just an incremental step? We compare its capabilities against Gemini, Grok, and Claude, and share our candid thoughts on whether it truly delivers or leaves us more excited for upcoming models like Gemini 3.0.

The AI Code Revolution: What Developers Need to Know

10 min

Dive into the AI coding revolution! This episode explores how AI is transforming software development, from rapid prototyping and coding assistance with tools like GitHub Copilot, to the rise of generative coding. Learn the key trends, essential tools, and practical ways you can leverage AI to build faster and smarter. Perfect for developers and anyone curious about the future of code.

Your AI Just Got Local: Gemini CLI is Automating Your Workflow

10 min

Ever wished your AI could actually do things directly from your terminal, beyond just chatting? Google's new Gemini CLI is here, and it's a game-changer! Unlike previous closed-source tools, this open-source power tool brings the intelligence of Gemini Pro right to your command line. We're talking direct file system access, automated project setups, and a powerful "reason and react" loop that lets AI analyze, plan, and execute tasks on your machine. Perfect for DevOps, developers, and anyone ready to automate their workflow. Is your terminal ready for its new brain?

Beyond Benchmarks: Understanding LLM's Accuracy Collapse in Reasoning

11 min

Are Large Language Models (LLMs) truly intelligent, or just sophisticated pattern matchers? This episode dives deep into a fascinating debate sparked by Apple's recent research paper, which questioned the reasoning capabilities of LLMs. We explore the counter-arguments presented by OpenAI and Anthropic, dissecting the methodologies and the core disagreements about what constitutes genuine intelligence in AI. Join us as we unpack the nuances of LLM evaluation and challenge common perceptions about AI's current limitations.

Your LLM's New Best Friend: Should You Be Using MCP Now?

9 min

Dive deep into the world of AI communication with this episode, focusing on the game-changing MCP (Model Context Protocol). Discover how this protocol, pioneered by Anthropic, acts as a universal translator, enabling AI models to seamlessly interact with external services like Google, Twitter, or even your private databases. Learn why MCP was developed to overcome the limitations of static API documentation, ensuring consistent and accurate information for AI. We'll explore its client-server architecture, how it empowers custom integrations, and why it's becoming the core of connecting LLMs to the vast digital world. Get ready to understand the future of AI interaction!

Navigating the Newest AI Models & Future Insights

10 min

Dive into the rapidly evolving world of Large Language Models! This episode breaks down the latest updates on cutting-edge models like Gemini 2.5 Pro (with its 2 million context window), the ambitious Llama 4, GPT-4o's impressive image generation, and Cloud's Sonnet 3.7. We explore key trends such as expert architectures, the nuances of leaderboard performance (including Llama 4's controversy), the emergence of "deep thinking" AI capable of independent research, and the potential impact of upcoming models like GPT-5. Discover how these advancements are shaping the future of AI.

So is everyone vibe coding now?

9 min

In this episode - I take on the task of explaining what vibe coding is, and if we should keep studing software engineering. I introduce some vibe coding tools, including the latest one Firebase Studio from Google

Does OpenAI O1 change everything?

10 min

Last week OpenAI released a new model called O1 - which has advanced capabilities to reason and does a lot better in maths and coding. How does it do this and what does this change? This and more in this episode.

LLMs: Understanding Google Gemma

10 min

In the world of many open source LLM models, Google Gemma stands out with some unique capabilities. Firstly its made by Google after all - so its implementation is fully optimized and memory efficient. This and more on what is Gemma about and how its better.

AI in Your Pocket - LLMs on Smartphones

7 min

This episode dives into the exciting world of on-device AI, specifically Large Language Models (LLMs) running directly on your smartphone! We'll explore why cramming this powerful tech into your pocket is a game changer, and discuss how LLMs can transform your daily interactions with your phone.

LLMs: Will Lama3 destroy the competition?

7 min

Lama3 is a popular open source model by Meta, the company behind Facebook, Instagram and Whatsapp. They have release the next iteration of the famous Lama2 model, this is a popular open source LLM which is heavily used by developers world wide. Is the new iteration strong enough to take on the best closed source models? We explore in this episode.

LLMs: Finetuning - do you need it?

8 min

As we move to use LLMs more and more for different use cases, we will run into at times issues or limitations with the model. There are many different ways to train the model to do a specific task better, and fine tuning is one of them. What is about, when do we need to use it and how do we do it - all in this episode.

LLMs: Are AI Software Engineers ready to take over?

8 min

In this episode I share my thoughts on the latest additional to AI development called Deven, and where the industry is moving towards. Will software engineering be taken over by AI in the next few years?

LLMs: My thoughts on Gemini Pro 1.5 and OpenAI Sora.

5 min

So this week we had 2 back to back announcements which completely shook up the LLM worlds. Gemini Pro 1.5 with its 10 million token context length makes it super powerful to run on large codebases and a lots of documents. The other big news was the launch of OpenAI Sora - their new text to video generation which can now generate super realistic videos for up to a minute. How will these impact our tool, I share some thoughts here.

LLMs: Welcome Google's Gemini Ultra!

5 min

The all new heavy weight model has just dropped this week. Should you be rushing to try it out? Why is the ultra model better? This and more in his quick episode talking about Gemini Ultra.

LLMs: How to train LLMs on your data using RAG.

6 min

In this episode - we discover the Retrieval Augmented Generation (RAG) process which allows us to train our LLMs using our data. In this short episode we cover what is this about and how can we use it.

LLMs: An Introduction to Prompt Engineering

9 min

If you are using ChatGPT or Bard - you are "prompting" the AI to get some answers. Not all prompts are made equal. The response of the LLM depends heavily on the quality of the prompt and the context given to it. Thus its worth while spending some time understanding prompt engineering and how to do it properly.

LLMs: This Jen, is the internet.

6 min

Referencing the classic episode from IT Crowd - we take our first dive into the world of LLMs by talking about neural nets and how they form the basis of the LLMs we know today. We touch on the famous paper - All you need is attention, and then talk about what LLMs under the hood are really about.

Welcome to the world of GenAI.

9 min

After a year long break - Im back with an update on Gemini and Gen AI taking over. In this episode I talk about the over all impact of Gemini and LLMs and how can we use them better in our daily lives.

EngineeringLeadershipPakistan - Lamak Qaizar @ Bazaar Tech

28 min

I had a great chat with Lamak, who works at one of the startups in Karachi called Bazaar Tech. We discussed several interesting topics including team structures, full stack development, performance reviews and more! Thanks Lamak for taking time out for this episode of EngineeringLeadershipPakistan.

EngineeringLeadershipPakistan - Asadullah Bin Yousuf @ Airlift

31 min

I had a great chat with Asadullah about his time in Airlift where he was an engineering manager leading a specific team. We talked about several management related topics, from the values at Airlift, life there as an engineering leader,  performance management, hiring, engineering productivity and more!  You can also watch this on the KarachiWalaDeveloper Youtube channel.

EngineeringLeadershipPakistan - Hunain Kapadia @ SmartBenefits

16 min

This is the first episode of the all new series where I will be interviewing Engineering Leaders in Pakistan. We will be talking about leadership topics like CTO roles, hiring, performance reviews, feedback and more. In this episode we have Hunain Kapadia from Smart Benefits sharing about this experience building the some awesome tools in the insurance space.

Writing Good User Stories in Product teams

14 min

Software Engineers require instructions in order to build apps and tools. And most of us don't know what these instructions should look like. One of the ways these instructions can be shared is in the form of user stories, and it's not just about writing a bunch of text, but comprehensive check list of how this should be structured so the right information can be given to the builder. Ofcourse its a two way effort Product and Engineering need to work closely to build up such requirements so they make sense from a functionality perspective, and a technical perspective. This session is based on the article linked below: https://martinfowler.com/articles/product-backlog-building-canvas.html

Why I havn't applied to Google as a SE (yet).

8 min

Google, or any of the FAANG companies for that matter, are an awesome place to work. When I started by bachelors - I was thinking of graduating and then getting a job there, or build a pathway to a job there. However by the time I graduated, my mind set had changed. In this episode I explore my thoughts and reasoning on what changed my mind and why I havnt applied since.

Should you join a startup today?

9 min

With startups going bust left right and center, high inflation and a global recession - are startups still the right choice to be at? In this episode I talk about the difference between the companies treating engineering teams as a profit center vs a cost center, to show why startup engineering teams as usually a better choice even if there is a slightly higher risk being there.

How good is your company's Engineering Culture?

30 min

In this episode I break down a good engineering culture using two different culture tests from the web. We take a deep dive into the technical side of the culture first, followed by the work and management culture. How does your company score - what is the one thing you would change in your company to make it a better experience?

Why Should Every Developer Learn Javascript?

15 min

Javascript is one of my favourite languages out there. Im not sure if it just the familiarity with the language (have been using it since age 10) or the fast pace of change in the language space or the fact its being used on space craft - I think its a useful skill to have for anyone working in the software industry. Check out my rant on what makes JS so awesome according to me!

Understanding DORA metrics for Software Delivery Performance

12 min

As programmers we work hard all day to ensure we build the best products in the best technical way possible, and if that work isn't shipped to customers right away, we are unable to generate any value of it for the company / product. DevOps plays a critical role in our organisations today, and ensure we have an efficient production line shipping features to our customers is a part of it. In this episode we review how we can better understand and measure performance of our software delivery and what does it take to compete with the best out there.

Whats makes a good software engineer?

20 min

While mentoring some students with technical interviews, I documented what I find to be most important qualities of a software developer or engineer. While a quick google search online will find mixed reviews, most people feel that technical skills are most important. However I feel a bit differently about this, and in this episode share the things all software engineers should focus on and how they can improve them selves if lacking.

Before joining a startup

10 min

The recent failure of the startup Fast got me thinking of things one needs to be aware of while considering to join a startup and things to observe while working in one. This episode covers some basics to what you can do before and after joining which should help you prepare better for the risks involved while working in a startup. This episode was inspired by the following post: https://newsletter.pragmaticengineer.com/p/the-scoop-fast?s=r

Understanding a Startups Technical Due Diligence...

12 min

Technical Due Diligence (DD) for startups is not something we think about until the time really comes in. When we get the list of questions or get asked those dreaded questions that we always knew would come to haunt us. In this episode I share about what is the process and what to expect from this, so that one can be better prepared when this happens.

Are you a T-Shaped Developer?

10 min

T-Shaped developers are those interested in learning across a breadth of technologies ranging from frontend to backend to devops. In this episode we try to understand why would we want to diversify vs specialise and is there a better option between the two?

Thinking about Engineering Analytics

18 min

Do you feel your team is very sluggish and not moving fast enough? Do you feel there are constant blockers which are stopping the features to get shipped? In this episode I dive into the world of engineering performance and what are some thing of the useful things you can measure, and which ones are not meant to be measured at all.

Understanding how ESOPs or Share Options work

27 min

You might have been reading about one of the dozen multi-million dollar investments made into startup recently. And you might be wondering how do I get a piece of that action. Most companies now offer their shares to employees through whats called an ESOP. This allows you to accrue value over time and if the company wins big - so do you! This and more in this episode.

Demystifying PCI DSS - Do I need it?

15 min

PCI DSS is a security standard certification which a company requires if they have card payment integrations on their websites. However its one of those topics which sounds scary, not talked about enough and is very specific to each company. So understanding even if it is a requirement for your company becomes a pain. In this episode I share my experience going through the certification with Sastaticket and what I learnt during that.

How do I write faster code?

10 min

In order to write faster code you need to understand (or profile) your current code and visually or numerically breakdown the pieces which need improvement. How do you do this? We use code profilers! In this episode we dive into the world of tweaking code performance and getting the most out of the hardware its running on.

Mono Repo vs Multi Repo

11 min

Mono repos is not a new concept - but one often visited by growing organisations to help reduce the overhead of managing thoses dozens of repos in the company. Is it better? Well that depends on the company and how they work. In this episode I go through the differences and reasons why one would consider a mono repo over a multi repo.

Do I need monitoring and observability for my web app?

9 min

Now a days even a simple CRUD based app can have a lot of moving parts - esp if deployed with something like Kubernetes. Our complex applications are growing even faster, interacting with many different libraries and handling greater and more variable loads. How do we get insight into whats really happening on the code level any more? Long gone are the days when a simple CPU usage alert would be enough to monitor most applications - today we need to monitor on different level and metrics to get a better picture of whats going on. This and more in this episode.

See all 73 episodes

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