Behind the product: Replit | Amjad Masad (co-founder and CEO)

Introduction to Amjad Masad and Replit (0s)

• Replit is a platform that aims to make software development easier, with the idea that making software today is very difficult and the company wants to change that (0s).
• The platform is viewed as a "developer in their pocket" and has 34 million users globally, with people using it to learn to code, build startups, and create personal software and tools (10s).
• The platform's goal is to remove the bottleneck of turning ideas into reality, making it easier for people to bring their ideas to life quickly (27s).
• With Replit, the limitation is no longer the ability to make things, but rather the speed at which users can generate ideas (41s).
• Amjad Masad is the co-founder of Replit, an AI-powered software development and deployment platform that is one of the fastest-growing developer communities and AI products in the world (1m7s).
• The platform is changing the way products are built, and how product teams operate, with some functions becoming more or less valuable over time (1m23s).
• The conversation with Amjad Masad will cover the implications of Replit on the future of product development, product management, and startups, and how it will change the way people work (2m1s).
• The goal of the conversation is to make people aware of what is possible today and where things are going, so they can thrive in the future (2m16s).

The vision and challenges of Replit (2m41s)

• Replit is a platform that aims to make software development easier by providing a single, learnable environment for coding, deployment, and sharing. (2m48s)
• The current process of software development is difficult and fragmented, requiring users to download an IDE, runtime, and package manager, configure Open Source packages, and figure out deployment and sharing. (2m56s)
• This cumbersome process can discourage people from learning how to code, and Replit's vision is to make software development more accessible and fun. (3m40s)
• Replit provides an easier IDE environment and deployment environment on the internet, making it easy for people to jump in and start coding, even without prior experience. (4m0s)
• The platform has recently introduced new AI products that further simplify the coding process. (4m15s)
• Replit's goal is to make software development easier, more learnable, and more accessible to a wider range of people. (3m52s)

Replit’s growth and user stories (6m50s)

• Replit has 34 million users globally, with a large global presence, and people are using it to learn to code, build startups, and create personal software and tools. (6m54s)
• The platform has recently expanded to companies, releasing a B2B package in July, which has been growing rapidly and allowing people to bring Replit to work. (7m14s)
• A viral tweet showcased an 11-year-old girl who built an app on Replit, highlighting the platform's ability to abstract away the complexities of hosting, database building, and deployment. (7m36s)
• The platform's ability to simplify the development process is particularly useful for non-technical users, such as product managers, designers, and operations people, who can use Replit to build software. (10m31s)
• Replit differentiates itself from other tools by providing an end-to-end platform for making software, from writing code to deploying and monetizing it. (9m6s)
• The platform is often compared to other tools like Cursor, a fork of VS Code with AI tools, but Replit simplifies the runtime and deployment environment, making it a more comprehensive solution. (9m20s)
• Replit's opinionated approach to software development can make it harder for large companies to adopt, but the platform is willing to make this trade-off to empower everyone to build software. (10m10s)
• The platform is democratizing the field of software engineering, with users from various backgrounds, including lawyers, using Replit to build software. (10m39s)

Demo of Replit’s capabilities (10m49s)

• A demo of Replit is being conducted to showcase the product's capabilities, especially in utilizing AI, and its potential impact on the future of product management and product teams (10m50s).
• Replit allows users to create a project, known as a Repl, in various programming languages, with the option to describe the desired project in a text box for the AI to build (11m35s).
• The AI can decide on the tech stack or the user can specify it, and the project can be built in a specific language, such as Node.js (12m31s).
• A sample prompt is used to build a web application for product managers to track feature requests on a public dashboard, including features like feature request submission, voting system, status tracking, and user-friendly design (12m29s).
• The prompt also includes requirements for admin controls for product managers to manage the community and build internal tools (13m34s).
• The AI responds to the prompt by building an initial prototype, which can then be reviewed and refined (14m26s).
• Different styles of using Replit's AI are possible, including minimalist prompts or more descriptive ones, similar to writing PRDs (13m59s).
• The AI's capabilities allow for the creation of complex projects, such as a web application with multiple features, in a relatively short amount of time (13m58s).
• Replit is a platform that allows users to build full-stack applications, and it has various services such as storage and database, making it a comprehensive tool for development (15m6s).
• The platform has a feature where users can watch the AI build and code their application in real-time, providing a transparent process and allowing users to learn how to structure web apps (15m27s).
• If the AI encounters a problem, users can help debug and understand what's going on, but it's not necessary to care about the code to build things on the platform (15m42s).
• Replit aims to make the process transparent, showing users exactly what the agent is doing, similar to sitting behind an engineer and watching them code (15m58s).
• The platform has a multiplayer system, allowing real-time collaboration, and this system was reused to build the agent, which is structured as another user of the platform (16m12s).
• Users can go into the files and edit them themselves or ask the AI for an explanation, making Replit a full IDE that combines the benefits of chat interfaces with the functionality of a traditional coding environment (16m44s).
• The agent is designed to assist users in building their applications, and users can select from various suggestions, such as adding common threads, implementing email notifications, and more (14m34s).
• The platform allows users to start with a prototype and then assess and improve from there, making it a flexible and iterative development process (14m47s).

Building and iterating with Replit (16m51s)

• Replit has limitations in its current state, particularly when it comes to large iterations of a product, such as database migrations, which can cause errors that are difficult to recover from, especially for users without coding experience (16m53s).
• Despite these limitations, Replit can be used to build minimum viable products (MVPs) and even attract initial users, but further development and iteration may require additional coding knowledge or hiring human coders (17m6s).
• The platform is not yet capable of handling complex database changes, which can lead to unrecoverable errors, but the team is working to address this issue (17m25s).
• Users who encounter problems can seek help from online communities, such as GitHub and Stack Overflow, or use Replit's "bounties" feature to hire human coders to assist with their project (17m56s).
• The long-term goal is to develop the agent to the point where it can automatically seek help from human coders when it encounters a problem it cannot solve on its own (19m19s).
• The agent is capable of proactive problem-solving, such as identifying and fixing errors, and can even perform quality assurance checks to ensure the application is running correctly (19m41s).
• The time it takes to build an application using Replit can be significantly shorter than traditional coding methods, with some tasks taking only a few minutes compared to several days or weeks (20m15s).
• The product in question is Replit, and it has an agent that can assist with various tasks, including deploying and testing products, and even creating admin accounts, all through simple conversations (21m2s).
• The agent can perform complex tasks such as SQL queries, and it's not just limited to building things, but also maintaining them (22m44s).
• The product has the potential to empower non-technical users to build and manage their own products, with the agent acting as a virtual developer in their pocket (24m2s).
• The implications of this technology on product development and management are significant, as it could enable people to build and launch products much faster and with less technical expertise (22m51s).
• The company's goal is to make everyone a developer, and they believe that by making programming easier, people will be able to build more ideas and products than they would have otherwise (23m46s).
• The technology has the potential to disrupt the traditional model of hiring developers, as people can now use the agent to build and manage their own products, with lower activation energy (24m12s).
• The company is seeing customers use the product to build and launch ideas that they wouldn't have otherwise, and they believe that this is due to the lower cost and barrier to entry (24m19s).
• The concept is related to the idea of the "Javelin's Paradox", which states that when the cost of things goes down, the total amount of activity increases (24m27s).
• The concept of a paradox is mentioned, where the consumption of a resource increases as its cost decreases, and the total spend on that resource also goes up, despite the lower cost per unit, with the example given being electricity (24m34s).
• This phenomenon is expected to apply to software as well, where lower costs will lead to increased consumption and creation of more software to improve lives, work, and potentially start more startups (24m52s).

Real-world applications and use cases (25m4s)

• Many people are using Replit to build back-office tools, such as real estate agents who need to manage data and other aspects of their business, as a replacement for traditional Software as a Service (SaaS) solutions that often don't exactly meet their needs (25m28s).
• In larger companies, Replit is used for prototyping, production apps, and tools, with product managers building and testing the first version of an app before handing it over to engineers for further development (26m2s).
• This approach empowers product managers to build the initial version of a product without needing engineers, allowing them to test and refine their ideas more efficiently (26m53s).
• Marketing departments are also using Replit, such as SpotHero's head of marketing, who built a competitive analysis application to track competitors' pricing and ensure their company is benchmarked correctly (27m9s).
• Sales engineers use Replit to quickly spin up prototypes, such as an employee at X (formerly Twitter) who uses Replit to create applications and prototypes for customers to demonstrate how to use an API (27m42s).
• Replit allows users to deploy their applications to cloud providers, such as Google Cloud, without needing to manage the underlying infrastructure (28m42s).

The technology stack (30m13s)

• The technology stack that enables Replit's functionality is based on abstractions, with the bottom layer being the runtime, which includes the operating system, package manager, and language runtimes, allowing for the installation of packages in any language, including native packages (30m38s).
• The AI has access to all packages across all languages, including Linux, and can take screenshots to check if the homepage is rendering correctly (31m3s).
• The layer on top of the runtime is the editor and the infrastructure that runs the editor, including the multiplier editor, which is exposed to the AI (31m27s).
• A new discipline called AI computer interfaces (ACI) has emerged, which is different from human-computer interfaces (HCI), and Replit provides the AI with text representations of the shell, package installation, and editing tools (31m39s).
• The AI computer interface provides the AI with feedback on errors, similar to what a human sees, but in a text format (32m26s).
• The technology stack is built on top of foundation models, with the Sonnet model from Claude being the most important model used for coding, and models from Open AI are also used in the multi-agent system (32m40s).
• Different models have different powers, and some models, such as the embedding model for search, are trained internally (33m17s).
• The use of multiple models in the technology stack is a heavy engineering project, and it is expected that products will be made of a society of models (33m37s).

The evolution of Replit and its capabilities (33m48s)

• The concept of Replit was first built in 2009, and the initial idea was a deployed app that allowed users to register, upload, and log in as admin to move things around and see what's in progress or completed (33m52s).
• The current version of Replit allows users to create a new feature or start a new session, and it builds from the existing code base, understanding what the user has built and what they want to add (34m43s).
• Replit generates git commit messages for every action, allowing users to roll back changes and maintain a history of their work (35m7s).
• The goal of Replit is to make it accessible to everyone, but also to provide a deep product that power users can master over time, with a learning curve that can take a couple of years (35m31s).
• A key aspect of Replit is that it's built around a computer specifically designed for an AI agent to use, which is optimized for how AI interacts with computers (35m46s).
• This computer is equipped with a set of tools and services, including a package installer, code editor, SQL query tool, and various external services like databases and object stores, all of which interface with the foundational model (37m2s).
• The development of Replit involves experimentation with AI computer interfaces and interactions, as large language models have different behaviors and requirements than humans (36m2s).
• The goal is to create a system that allows users to effectively work with AI, despite its alien nature and different behaviors, and to make the process more scientific than artistic (36m51s).
• The concept of living in a simulation is not as far-fetched as it may seem, and current advancements in technology feel like the beginnings of what a simulation computer would be (37m45s).
• A feature is being developed where an agent will test an application instead of a human, allowing for autonomous interaction and enabling the agent to interface with the application entirely through a platform like Slack (38m19s).
• This feature will enable users to give commands to the agent, such as getting Taylor Swift tickets the moment they become available, and the agent will build an app to continuously monitor the web and make the purchase when possible (38m38s).
• The agent will be able to use the app and make purchases using a wallet or credit card, demonstrating a high level of autonomy and competence (39m5s).
• The development of software agents that can create and interact with software is a key step in achieving more general AI, as software runs many aspects of modern life, including the internet and businesses (39m14s).
• As AI becomes more competent in software, it will become more general in terms of its capabilities and what it can do (39m28s).

The future of AI in software development (39m36s)

• The future of AI in software development will significantly impact the roles of product managers and founders, changing the required skill sets and potentially putting some functions at risk, requiring professionals to consider alternative career paths (39m38s).
• A notable persona emerging in this context is the CEO of a startup, often a creative who cannot code, but has a bottleneck of ideas that need to be translated through others, which AI can help unlock and unblock (40m0s).
• This technology can enable CEOs to build future concepts, products, and companies, unlocking their creativity and allowing them to touch and feel their ideas, which can then be improved upon by engineers (40m57s).
• The current silos between designers, product managers, and engineers in tech companies can lead to frustration and misinterpretation, but a common language of working prototypes and applications can help bridge these gaps (41m50s).
• The use of working prototypes and applications as a common language can make communication around product development more concrete, allowing for more effective collaboration and a radical reimagining of how tech companies and other organizations operate (43m30s).
• The potential for everyone to make software, regardless of their role, could lead to a more generalist approach, where individuals can take on a wider range of responsibilities and contribute to the development process in new ways (43m48s).
• The integration of design tools, such as Figma, with development platforms, can facilitate this process, enabling designers to create working prototypes that can be easily translated into code, streamlining the development process (42m57s).
• This shift could ultimately change the way companies operate, making them more agile and responsive to changing needs, and enabling a more collaborative and effective approach to product development (43m54s).

Skills for the future: generative thinking and coding (44m4s)

• For engineers and designers working on Replit, it is suggested to focus on developing skills such as generative thinking, which involves generating new ideas quickly, as this skill is harder to develop but worth working on (44m6s).
• Being generative is important because it can help open up the bottleneck in the idea production process, where ideas are generated but not made quickly enough, and with the help of tools, making things is becoming easier (44m30s).
• Training the generative muscle is a good thing, and it can be done by learning a little bit of coding, but not in the traditional way, such as through a coding boot camp (45m54s).
• Traditional coding boot camps may focus too much on tooling, such as Git, which may not be immediately relevant to the problem at hand, and can be inverted by giving the tool before the actual problem (46m11s).
• As a product manager, designer, or someone who is not in their code editor every day, it is not necessary to worry about all the tooling, and learning a little bit of coding can be done through interacting with AI, debugging, and building something with Replit (47m1s).
• Learning to code can be done through practical experience, such as talking to an AI, doing a little bit of debugging, building something with Replit, running into a problem, and trying to fix it using AI (47m11s).

Amjad’s law (47m26s)

• Amjad's Law states that the return on investment for learning to code is doubling every six months, particularly when it comes to learning how to prompt AI, read code, and debug it (47m31s).
• As a result, learning a little bit of this skill every six months can net more power and enable the creation of more complete things (47m50s).
• This concept suggests that specific engineering skills are becoming increasingly valuable, doubling in value every six months, and will continue to be essential in the future (48m37s).
• These valuable skills include understanding the basic components of how things are built, unblocking AI agents, and comprehending the mental model behind the technology (48m55s).
• The idea is not to know everything, but rather to have a deep understanding of specific skills that can help move projects forward quickly (48m45s).
• There is a need for new engineering schools that teach these specific skills, focusing on AI-native coding rather than traditional coding methods (49m3s).
• AI-native coding is a distinct approach that differs from traditional coding, and it requires a different set of skills and knowledge (49m22s).
• A school teaching AI-native coding would likely skip some computer science basics and focus on teaching how to structure an app, prompting, and debugging (50m2s).
• Debugging is considered a valuable skill to learn, and it requires a deep understanding of how things work, including servers, APIs, and other underlying technologies (50m16s).

Replit’s new developments and future plans (50m36s)

• The potential for building a massive business using Replit or other tools that can scale to hundreds of billions of dollars in value is possible, given the compounding effect of the power of AI (50m48s).
• The improvement in AI is happening at a massive scale, and it's hard for humans to grasp the exponential growth, as explained by futurist Rikers (51m24s).
• When building the agent, the team was told to focus on building and optimizing for the future, rather than just for today, as the models were not yet available to support the desired modality (51m46s).
• The right modality for the agent is being able to chat inside the programming environment and create things for the user, which was not possible with the models available a year ago (52m11s).
• The models have improved significantly over the past year, with new models landing every six months, allowing for significant improvements in reasoning and capabilities (52m30s).
• If the current trajectory continues, it's possible that next year, thousands of users will be able to pay for services that are maintained and debugged by AI (52m58s).
• The AI is already capable of doing SQL queries, migrations, and other tasks, but the next bottleneck will be architecting a system that is resilient and scalable (53m9s).
• The AI needs to have access to the entire suite of tools to be able to architect a resilient system, and it needs to become more reliable at doing so (53m38s).
• In the future, it's possible to imagine a billion-dollar company with zero employees, where support and development are handled by AI, and the founder is just building and creating value (54m2s).
• The economics of software development are changing, with the cost of software decreasing significantly, which raises questions about the price that can be charged for software and whether it's possible to build the next Salesforce using generative tools (54m27s).
• Being generative is crucial in staying ahead of the competition, as it allows for quick iteration, improvement, and generation of new ideas (54m49s).
• The concept of "God of the gaps" can be applied to the current state of AI, where humans are filling in the gaps in tools, but over time, AI will fix these gaps itself, shrinking the space where humans are needed (55m13s).
• The current regime of AI, using Transformers, has the potential to scale far, but there may be limitations in data or other areas that could surprise us (55m52s).
• It's essential to let people experiment with these tools and process the changes happening in the industry (56m31s).
• The way we work is going to change rapidly, and it's crucial to be resilient to this change, especially for founders and leaders at companies (56m51s).
• Having roadmaps can be challenging, especially in AI, and it's essential to be able to react quickly to new capabilities and changes in the industry (57m1s).
• Being agile and able to switch priorities quickly is vital, rather than being stuck with roadmaps or silos (57m46s).
• At Replit, there are many people who have transitioned between roles, such as from designer to engineer or product manager, demonstrating the importance of flexibility and adaptability (58m3s).
• Replit has a fluid work environment where designers can code and engineers can design, making it uncomfortable for some people but necessary for the future where everyone is a hybrid person (58m15s).
• The most valuable skill set for engineers will be unblocking AI tools, debugging, and figuring out how to allow them to go further in product management and design land (59m14s).
• The skills that will become more valuable for product managers and designers are generating ideas, finding opportunities, discovery, and articulating problems to be solved as clearly as possible to AI tooling (59m29s).
• Replit is currently in open beta and can be accessed at rep.com, with the core plan subscribers able to access the Agent feature (1h0m8s).
• The company is active on Twitter, with the handle @replit and the CEO's handle @amasad (1h0m36s).
• Replit is working on a new product called Assistant, which is a cousin of Agent but less powerful and more controllable, allowing users to focus on specific features or areas of the code without needing to know how to code (1h1m12s).
• Assistant is faster than Agent, responding in milliseconds and seconds, and is designed to give users more power and autonomy (1h1m44s).
• Replit has two tools: Agent and Assistant, which provide different levels of control and assistance to users. Agent is like having a developer work for you, where you give them the product requirements document (PRD) and they build the thing, while Assistant is like sitting next to the developer and making small increments of changes quickly and reliably. (1h2m0s)
• The mental model for Agent is having a developer work for you, while the mental model for Assistant is collaborating with the developer to make small changes. (1h2m11s)
• Replit is hiring engineers and product managers, and listeners can be useful by coming to work at Replit or referring great people to the company. (1h3m0s)
• The best way to improve Replit's tools is to hire great people, and the company is looking for talented individuals to join their team. (1h3m20s)
• Listeners can subscribe to the show on Apple Podcast, Spotify, or their favorite podcast app, and consider giving a rating or leaving a review to help other listeners find the podcast. (1h3m43s)
• All past episodes and more information about the show can be found at Lenny podcast.com. (1h3m56s)