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Can You Be a Tech Leader Without Knowing How to Code?

Can You Be a Tech Leader Without Knowing How to Code?

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In this episode of the Engineering Leadership Series, host Tracy Lee interviews Sriram Venkateswaran, the CTPO of Root Pay. Sriram shares insights into his extensive engineering leadership journey and the projects he's been involved in throughout his career.

Sriram discusses his current role as the CTPO at Root Pay, a FinTech SaaS platform. Before his role at Root Pay, Sriram was heading engineering at Polygon and app engineering at Flipkart. He also had a brief stint at Coinbase before moving to the US.

During his five years at the Flipkart group, Sriram played a pivotal role in introducing 3D commerce and augmented reality capabilities within Flipkart, transforming it into a global leader in these technologies.

Sriram emphasizes the importance of maintaining technical skills as an engineering leader. He draws a comparison between a chef who can handle every aspect of cooking and an engineering leader who can still code and debug. He believes this helps leaders stay connected with their team, understand ground-level challenges, prioritize effectively, and earn the respect of their developers.

He recommends that senior leaders take time to code, even if it's only for a few days every quarter or so. This hands-on approach keeps them in touch with the technical aspects of their projects and helps them understand their team's challenges better.

Tracy and Sriram also discuss the difficulties non-technical leaders may face when making technical decisions. Sriram advises using metrics and data to build a strong case and support decision-making. He also stresses the importance of empathy and effective communication when dealing with stakeholders from non-technical backgrounds.

Sriram shares how he introduced 3D commerce and augmented reality at Flipkart to address customer pain points related to online furniture shopping. He emphasized the role of prototypes and aligning with stakeholders in overcoming challenges and making impactful decisions.

His dedication to maintaining his technical skills, even in senior leadership roles, underscored the importance of staying connected with ground-level challenges. His practical advice on decision-making, backed by metrics and prototypes, speaks to the nuanced process of making effective technical choices.

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“ChatGPT knows me pretty well… but it drew me as a white man with a man bun.” – Angie Jones on AI Bias, DevRel, and Block’s new open source AI agent “goose” cover image

“ChatGPT knows me pretty well… but it drew me as a white man with a man bun.” – Angie Jones on AI Bias, DevRel, and Block’s new open source AI agent “goose”

Angie Jones is a veteran innovator, educator, and inventor with over twenty years of industry experience and twenty-seven digital technology patents both domestically and internationally. As the VP of Developer Relations at Block, she facilitates developer training and enablement, delivering tools for developer users and open source contributors. However, her educational work doesn’t end with her day job. She is also a contributor to multiple books examining the intersection of technology and career, including *DevOps: Implementing Cultural Change*, and *97 Things Every Java Programmer Should Know*, and is an active speaker in the global developer conference circuit. With the release of Block’s new open source AI agent “goose”, Angie drives conversations around AI’s role in developer productivity, ethical practices, and the application of intelligent tooling. 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There’s no single answer, but its cross-functional nature makes it a crucial bridge between technical teams and the developers they serve. Leadership Is Not an Extension of Engineering Excellence Most engineers assume that excelling as an IC is enough to prepare them for leadership, but Angie warns that this is a common misconception. She’s seen firsthand how technical skills don’t always equate to strong leadership abilities—we’ve all worked under leaders who made us wonder *how they got there*. When she was promoted into leadership, Angie was determined not to become one of those leaders: > “This required humility. Acknowledging that while I was an expert in one area, I was a novice in another.” Instead of assuming leadership would come naturally, she took a deliberate approach to learning—taking courses, reading books, and working with executive coaches to build leadership skills the right way. Goose: An Open Source AI Assistant That Works for You At Block, Angie is working on a tool called goose, an open-source AI agent that runs locally on your machine. Unlike many AI assistants that are locked into specific platforms, goose is designed to be fully customizable: > “You can use your LLM of choice and integrate it with any API through the Model Context Protocol (MCP).” That flexibility means goose can be tailored to fit developers’ workflows. Angie gives an example of what this looks like in action: > “Goose, take this Figma file and build out all of the components for it. Check them into a new GitHub repo called @org/design-components and send a message to the #design channel in Slack informing them of the changes.” And just like that, it’s done— no manual intervention required. The Future of Data Governance As AI adoption accelerates, data governance has become a top priority for companies. Strong governance requires clear policies, security measures, and accountability. Angie points out that organizations are already making moves in this space: > “Cisco recently launched a product called AI Defense to help organizations enhance their data governance frameworks and ensure that AI deployments align with established data policies and compliance requirements.” According to Angie, in the next five years, we can expect more structured frameworks around AI data usage, especially as businesses navigate privacy concerns and regulatory compliance. Bias in AI Career Tools: Helping or Hurting? AI-powered resume screeners and promotion predictors are becoming more common in hiring, but are they helping or hurting underrepresented groups? Angie’s own experience with AI bias was eye-opening: > “I use ChatGPT every day. It knows me pretty well. I asked it to draw a picture of what it thinks my current life looks like, and it drew me as a white male (with a man bun).” When she called it out, the AI responded: > “No, I don’t picture you that way at all, but it sounds like the illustration might’ve leaned into the tech stereotype aesthetic a little too much.” This illustrates a bigger problem— AI often reflects human biases at scale. However, there are emerging solutions, such as identity masking, which removes names, race, and gender markers so that only skills are evaluated. > “In scenarios like this, minorities are given a fairer shot.” It’s a step toward a more equitable hiring process, but it also surfaces the need for constant vigilance in AI development to prevent harmful biases. Women at the Forefront of AI Innovation While AI is reshaping nearly every industry, women are playing a leading role in its development. Angie highlights several technologists: > “I’m so proud to see women are already at the forefront of AI innovation. I see amazing women leading AI research, training, and development such as Mira Murati, Timnit Gebru, Joelle Pineau, Meredith Whittaker, and even Block’s own VP of Data & AI, Jackie Brosamer.” These women are influencing not just the technical advancements in AI but also the ethical considerations that come with it. Connect with Angie Angie Jones is an undeniable pillar of the online JavaScript community, and it isn’t hard to connect with her! You can find Angie on X (Twitter), Linkedin, or on her personal site (where you can also access her free Linkedin Courses). Learn more about goose by Block. Sticker Illustration by Jacob Ashley...

Are Engineering Leaders Hiding Behind the Data? cover image

Are Engineering Leaders Hiding Behind the Data?

Many engineering leaders when they start out find themselves just wanting to please everyone around them. Figuring out how to “own” the role is quite difficult for many. Rob Ocel, Engineering Lead and Tracy Lee, CEO at This Dot explore this topic on this episode. They discuss the idea of hiding behind the data. When decisions are made, it’s easy to ask for data, but then make decisions solely based on that data and not form or “own” an opinion around that decision so you can’t get blamed for an opinion you had. Rob encourages leaders to have opinions and be willing to fight for them. Another topic covered was making people unhappy in a deliberate way. Are you able to succeed doing so, and do you have the ability to “own” that? Rob also emphasizes the need for self-awareness and self-introspection, and to have mentors and accountability partners to help guide decision-making. Listen to the full podcast here: https://engineeringleadership.podbean.com/e/are-engineering-leaders-hiding-behind-the-data-with-robocel-tracy-lee/...

The simplicity of deploying an MCP server on Vercel cover image

The simplicity of deploying an MCP server on Vercel

The current Model Context Protocol (MCP) spec is shifting developers toward lightweight, stateless servers that serve as tool providers for LLM agents. These MCP servers communicate over HTTP, with OAuth handled clientside. Vercel’s infrastructure makes it easy to iterate quickly and ship agentic AI tools without overhead. Example of Lightweight MCP Server Design At This Dot Labs, we built an MCP server that leverages the DocuSign Navigator API. The tools, like `get_agreements`, make a request to the DocuSign API to fetch data and then respond in an LLM-friendly way. ` Before the MCP can request anything, it needs to guide the client on how to kick off OAuth. This involves providing some MCP spec metadata API endpoints that include necessary information about where to obtain authorization tokens and what resources it can access. By understanding these details, the client can seamlessly initiate the OAuth process, ensuring secure and efficient data access. The Oauth flow begins when the user's LLM client makes a request without a valid auth token. In this case they’ll get a 401 response from our server with a WWW-Authenticate header, and then the client will leverage the metadata we exposed to discover the authorization server. Next, the OAuth flow kicks off directly with Docusign as directed by the metadata. Once the client has the token, it passes it in the Authorization header for tool requests to the API. ` This minimal set of API routes enables me to fetch Docusign Navigator data using natural language in my agent chat interface. Deployment Options I deployed this MCP server two different ways: as a Fastify backend and then by Vercel functions. Seeing how simple my Fastify MCP server was, and not really having a plan for deployment yet, I was eager to rewrite it for Vercel. The case for Vercel: * My own familiarity with Next.js API deployment * Fit for architecture * The extremely simple deployment process * Deploy previews (the eternal Vercel customer conversion feature, IMO) Previews of unfamiliar territory Did you know that the MCP spec doesn’t “just work” for use as ChatGPT tooling? Neither did I, and I had to experiment to prove out requirements that I was unfamiliar with. Part of moving fast for me was just deploying Vercel previews right out of the CLI so I could test my API as a Connector in ChatGPT. This was a great workflow for me, and invaluable for the team in code review. Stuff I’m Not Worried About Vercel’s mcp-handler package made setup effortless by abstracting away some of the complexity of implementing the MCP server. It gives you a drop-in way to define tools, setup https-streaming, and handle Oauth. By building on Vercel’s ecosystem, I can focus entirely on shipping my product without worrying about deployment, scaling, or server management. Everything just works. ` A Brief Case for MCP on Next.js Building an API without Next.js on Vercel is straightforward. Though, I’d be happy deploying this as a Next.js app, with the frontend features serving as the documentation, or the tools being a part of your website's agentic capabilities. Overall, this lowers the barrier to building any MCP you want for yourself, and I think that’s cool. Conclusion I'll avoid quoting Vercel documentation in this post. AI tooling is a critical component of this natural language UI, and we just want to ship. I declare Vercel is excellent for stateless MCP servers served over http....

The Future of Dates in JavaScript: Introducing Temporal cover image

The Future of Dates in JavaScript: Introducing Temporal

The Future of Dates in JavaScript: Introducing Temporal What is Temporaal? Temporal is a proposal currently at stage 3 of the TC39 process. It's expected to revolutionize how we handle dates in JavaScript, which has always been a challenging aspect of the language. But what does it mean that it's at stage 3 of the process? * The specification is complete * It has been reviewed * It's unlikely to change significantly at this point Key Features of Temporal Temporal introduces a new global object with a fresh API. Here are some important things to know about Temporal: 1. All Temporal objects are immutable 2. They're represented in local calendar systems, but can be converted 3. Time values use 24-hour clocks 4. Leap seconds aren't represented Why Do We Need Temporal? The current Date object in JavaScript has several limitations: * No support for time zones other than the user's local time and UTC * Date objects can be mutated * Unpredictable behavior * No support for calendars other than Gregorian * Daylight savings time issues While some of these have workarounds, not all can be fixed with the current Date implementation. Let's see some useful examples where Temporal will improve our lives: Some Examples Creating a day without a time zone is impossible using Date, it also adds time beyond the date. Temporal introduces PlainDate to overcome this. ` But what if we want to add timezone information? Then we have ZonedDateTime for this purpose. The timezone must be added in this case, as it also allows a lot of flexibility when creating dates. ` Temporal is very useful when manipulating and displaying the dates in different time zones. ` Let's try some more things that are currently difficult or lead to unexpected behavior using the Date object. Operations like adding days or minutes can lead to inconsistent results. However, Temporal makes these operations easier and consistent. ` Another interesting feature of Temporal is the concept of Duration, which is the difference between two time points. We can use these durations, along with dates, for arithmetic operations involving dates and times. Note that Durations are serialized using the ISO 8601 duration format ` Temporal Objects We've already seen some of the objects that Temporal exposes. Here's a more comprehensive list. * Temporal * Temporal.Duration` * Temporal.Instant * Temporal.Now * Temporal.PlainDate * Temporal.PlainDateTime * Temporal.PlainMonthDay * Temporal.PlainTime * Temporal.PlainYearMonth * Temporal.ZonedDateTime Try Temporal Today If you want to test Temporal now, there's a polyfill available. You can install it using: ` Note that this doesn't install a global Temporal object as expected in the final release, but it provides most of the Temporal implementation for testing purposes. Conclusion Working with dates in JavaScript has always been a bit of a mess. Between weird quirks in the Date object, juggling time zones, and trying to do simple things like “add a day,” it’s way too easy to introduce bugs. Temporal is finally fixing that. It gives us a clear, consistent, and powerful way to work with dates and times. If you’ve ever struggled with JavaScript dates (and who hasn’t?), Temporal is definitely worth checking out....

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