Free trial

Serial Entrepreneur and Tech Veteran Rob Pinna VP of Product and Engineering at Serenity App., Inc. Shares 5 Essentials For Development Velocity

profiq podcasts

Most of us understand velocity in terms of objects: how fast something can travel in a given direction. But what does this term mean when it comes to engineering teams – and why is understanding this so fundamental to building your team’s velocity?

profiq is one of the founders and organizers for the Moving Fast Tech Podcast and Meetup series, and recently, we had the opportunity to sit down with Rob Pinna, VP of Product and Engineering at Serenity App, Inc., to discuss development velocity – and how to apply this complex concept to your engineering teams. Put simply, according to Pinna, development velocity is the speed of development in the direction of creating ultimate software value and application.

Pinna touches on five areas in the Moving Fast Tech Podcast that are critical to improving and maintaining development velocity:

Time stamp
4:50 – Value orientation: Focus on delivering value is the developer’s highest priority
8:41 – WIP and cycle time: Minimizing work in process
15:16 – People: Culture, career development, skill development, sourcing, and specialization
19:00 – Tech debt: Preventing tech debt in scalable ways
21:39 – DevOps: Continuous integration and continuous delivery; self-detection of errors

In addition to fleshing out each of these areas and explaining how they impact dev velocity, Pinna adds additional insights from his 35-year career as a leader in software development – including helpful tips for troubleshooting specific challenges.

Listen to the full podcast here.

development velocity engineering team podcast startup

Leave a Reply

Related articles


Let’s make LLMs generate JSON!

In this article, we are going to talk about three tools that can, at least in theory, force any local LLM to produce structured output: LM Format Enforcer, Outlines, and Guidance. After a short description of each tool, we will evaluate their performance on a few test cases ranging from book recommendations to extracting information from HTML. And the best for the end, we will show you how forcing LLMs to produce a structured output can be used to solve a very common problem in many businesses: extracting structured records from free-form text.

Notiondipity: What I learned about browser extension development

Me and many of my colleagues at profiq use Notion for note-taking and work organization. Our workspaces contain a lot of knowledge about our work, plans, or the articles or books we read. At some point, a thought came to my mind: couldn’t we use all this knowledge to come up with project ideas suited to our skills and interests?

From ChatGPT to Smart Agents: The Next Frontier in App Integration

It has been over a year since OpenAI introduced ChatGPT and brought the power of AI and large language models (LLMs) to the average consumer. But we could argue that introducing APIs for seamlessly integrating large language models into apps developed by companies and independent hackers all over the world can be the true game changer in the long term. Developers are having heated discussions about how we can utilize this technology to develop truly useful apps that provide real value instead of just copying what OpenAI does. We want to contribute to this discussion by showing you how we think about developing autonomous agents at profiq. But first a bit of background.