Rethinking GraphQL Frontends with Robert Balicki
A challenge in modern frontend application design is efficiently fetching and managing GraphQL data while keeping UI components responsive and maintainable. Developers often face issues like over-fetching, under-fetching, and handling complex query dependencies, which can lead to performance bottlenecks and increased development effort.
Relay is a JavaScript framework developed by Meta for managing GraphQL data in React applications. It’s designed to optimize data fetching by colocating queries with components, ensuring that each part of the UI declares its own data dependencies.
Robert Balicki was on the Relay team at Meta and is now a Staff Software Engineer at Pinterest. He is currently developing Isograph, which provides a declarative and type-safe approach to data fetching.
Robert joins the show to talk about challenges and solutions for managing data in frontend applications.
Gregor Vand is a security-focused technologist, having previously been a CTO across cybersecurity, cyber insurance and general software engineering companies. He is based in Singapore and can be found via his profile at vand.hk or on LinkedIn.
Please click here to see the transcript of this episode.
Sponsorship inquiries: sponsor@softwareengineeringdaily.com
The post Rethinking GraphQL Frontends with Robert Balicki appeared first on Software Engineering Daily.
Summer Replay - Breaking Down Productivity Engineering with Micheal Benedict
In this Summer Replay, we revisit our 2021 conversation Micheal Benedict. At the time, he was the Head of Engineering Productivity at Pinterest, and today, he’s Head of Infrastructure Engineering at Airtable. Micheal tells us what exactly it means to lead engineering productivity and divulges more details on productivity engineering. He traces the history of productivity engineering at Pinterest and offers some distinct observations on building out internal teams. Micheal talks about what it is like in his day-to-day complexities of working in AWS. Tune in for Micheal’s take on the specific details of productivity and the cloud.
Show Highlights:
(0:00) Intro
(0:55) Panoptica sponsor read
(1:36) What is product engineering?
(2:44) The effectiveness of internal platforms
(7:46) Solving AMI problems
(10:23) Building foundations and learning woes
(13:06) Micheal’s day-to-day at Pinterest
(15:31) When engineering productivity starts to make sense
(18:58) Changes Micheal would've made at Pinterest
(20:56) Panoptica sponsor read
(21:19) Biggest mistakes at Pinterest
(23:46) Navigating outages in the cloud
(30:51) Corey’s personal experiences with Pinterest
(36:20) The legacy of code
(40:31) Where you can find more from Micheal
About Micheal Benedict:
Micheal Benedict is an engineering leader with a decade of experience in building and scaling infrastructure for consumer and enterprise companies.
He currently heads Infrastructure Engineering at Airtable. Previously, he led teams at Databricks, Pinterest, and Twitter, enhancing developer productivity, scaling infrastructure, and driving efficient use of multi-million $ cloud budgets.
Micheal holds a Master’s degree in Computer Science from the University at Buffalo.
Links:
Pinterest: https://www.pinterest.com
Twitter: https://twitter.com/micheal
LinkedIn: https://www.linkedin.com/in/michealb/
Original Episode:
https://www.lastweekinaws.com/podcast/screaming-in-the-cloud/breaking-down-productivity-engineering-with-micheal-benedict/
Sponsor
Panoptica: https://www.panoptica.app/
Images and Inspiration With AI: Pinterest’s Jeremy King
Jeremy King leads a team of 1,400 passionate engineers working on the continuous improvement of Pinterest’s image-driven platform. With a background that includes heading up a translation team at eBay and overseeing the technology behind Walmart’s U.S. retail stores and e-commerce business, Jeremy is now responsible for technology operations at Pinterest. To support the company’s mission to inspire people to “create a life that they love,” he and his team rely on advanced AI, machine learning, and a graph database to index and build a network of images so users can find inspiration — particularly when they aren’t completely sure what they’re looking for.
On this episode, Jeremy joins Sam and Shervin to talk about some recent advances Pinterest has made in the image-recognition space and shares his views on how generative AI will transform image-based content like Pinterest’s. Read the episode transcript here.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
Guest bio:
Jeremy King is senior vice president of technology at Pinterest, where he leads the company’s technical vision and the engineering organization responsible for building and scaling a visual discovery engine.
Before joining Pinterest, he was CTO and senior vice president at Walmart, where he led the team responsible for the technology behind U.S. retail stores and e-commerce for Walmart and Jet, and oversaw customer, merchant, and supply chain technologies across cloud and data platforms. King has also held executive-level technology roles at Walmart Labs, LiveOps, and eBay.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.
SaaS Product-Market Fit: 5 Founders Share What Worked
What if the fastest way to SaaS product-market fit was to walk into a train station and start asking strangers questions? That is exactly what Jeremy King did before building Attest into an eight-figure ARR business.
Five SaaS founders share hard-won lessons on customer discovery, product quality, monetization, and finding product-market fit - including Rahul Vora's product-market fit engine that helped Superhuman grow after two years of coding with no launch. Learn how to achieve SaaS product-market fit whether you are validating a new idea or measuring traction in an existing product.
Featured founders: Jeremy King (Attest, $1M ARR in 8 months), Melissa Kwan (eWebinar, $750K ARR bootstrapped), Christian Owens (Paddle, nearly $100M ARR), Trevor Kaufman (Piano, $80M ARR), and Rahul Vora (Superhuman, $125M+ raised).
Key Lessons
🎯 Validate by going to customers physically: Jeremy King interviewed 200 consumers at Waterloo Station before building Attest, proving demand existed beyond corporate research departments.
🛠️ Deep product experience beats surface research for SaaS product-market fit: Melissa Kwan did 1,000+ webinars before building eWebinar, knowing exactly what the product needed.
💰 Monetize from day one to compound growth: Christian Owens built every business to make money immediately, using revenue to reinvest rather than chasing distribution first.
📉 Conviction under pressure is not failure: Trevor Kaufman sold his house to keep Piano alive through years of market rejection before reaching $80M ARR.
🔄 Use the 40% benchmark for SaaS product-market fit: Rahul Vora's product-market fit engine asks users "How would you feel if you could no longer use the product?" and targets 40% answering "very disappointed."
Chapters
Introduction and episode overview
Preview of the five founder clips
Jeremy King - Attest: Zero to $1M ARR in 8 months
How Jeremy validated demand through customer discovery
Why Jeremy did the research for free
Overcoming skepticism from store managers
Melissa Kwan - eWebinar: Two years of building in silence
Why Melissa refused to launch before the product was ready
The cost of a bad first impression on early adopters
How 1,000+ webinars gave Melissa deep problem understanding
Managing competition anxiety while bootstrapped
Financial projections as the real urgency driver
Christian Owens - Paddle: Pragmatism and monetizing from day one
How Christian approaches SaaS product-market fit incrementally
Every business must be a real business from day one
Trevor Kaufman - Piano: Selling his house to survive
The belief that kept Trevor going through market rejection
Rahul Vora - Superhuman: The Product Market Fit Engine
How Sean Ellis's research inspired the PMF Engine
The four steps of the Product Market Fit Engine
Closing thoughts
Resources
Full show notes: https://saasclub.io/357
Join 5,000+ SaaS founders: https://saasclub.io/email
How Pinterest delivers software at scale
Nishant Roy, Engineering Manager at Pinterest Ads, joins Johnny & Jon to detail how they’ve managed to continue shipping quality software from startup through hypergrowth all the way to IPO. Prepare to learn a lot about Pinterest’s integration and deployment pipeline, observability stack, Go-based services and more.
Join the discussion
Changelog++ members save 4 minutes on this episode because they made the ads disappear. Join today!
Sponsors:
Square – Develop on the platform that sellers trust. There is a massive opportunity for developers to support Square sellers by building apps for today’s business needs. Learn more at changelog.com/square to dive into the docs, APIs, SDKs and to create your Square Developer account — tell them Changelog sent you.
FireHydrant – The reliability platform for every developer. Incidents impact everyone, not just SREs. FireHydrant gives teams the tools to maintain service catalogs, respond to incidents, communicate through status pages, and learn with retrospectives. Small teams up to 10 people can get started for free with all FireHydrant features included. No credit card required to sign up. Learn more at firehydrant.com/
Calhoun Black Friday – Go Time co-host Jon Calhoun is having a Black Friday sale on November 21st-29th. All paid courses will be 50% OFF. Learn more about Jon’s courses at calhoun.io/courses
Featuring:
Nishant Roy – GitHub, LinkedIn, X
Johnny Boursiquot – Website, GitHub, X
Jon Calhoun – Website, GitHub, X
Show Notes:
Something missing or broken? PRs welcome!
Startup Funding: He Got Customers to Call VCs For Him
Jeremy King had no product, no revenue, and a six-month deadline from his wife. Instead of pitching VCs the usual way, he convinced 15 potential customers to call investors and ask them to fund Attest so they could buy the product. That startup funding hack compressed two years of struggle into four months.
In this episode, Jeremy reveals how he used Series B investors to create warm intros to seed funds for his SaaS fundraising, why he interviewed 200 people at Waterloo train station to validate his idea, and how a subscription flip took Attest from pay-as-you-go users to $1M ARR in just 7.5 months. You will learn the specific startup traction tactics that helped Attest reach eight figures in ARR and $104 million in total early traction funding.
What You Will Learn
How Jeremy used customer demand as a startup funding proxy for revenue
Why pitching Series B investors shaped his seed-stage strategy
How flipping to annual subscriptions converted nearly all existing users
Why Attest's freemium experiment bombed despite strong user adoption
🔑 Key Lessons
💰 Use customer demand as a startup funding proxy for revenue: Jeremy got 15 potential customers to call VCs directly, replacing traction metrics with firsthand demand.
🧠 Pitch later-stage VCs to shape your startup funding strategy: Jeremy pitched Series B/C investors who gave milestone feedback and warm referrals to their preferred seed funds.
⚡ Compress timelines by engineering social proof loops: Customers, Series B investors, and seed VCs all reinforced confidence in Attest, compressing two years of SaaS fundraising validation into four months.
🔄 Force a subscription flip when usage proves recurring value: Attest moved all users to annual contracts, converting nearly everyone because the product had proven regular utility.
📉 High-ACV products can backfire with freemium: Giving away a $45,000-ACV product made users question data quality and reduced urgency for startup traction.
Chapters
Introduction
Jacques Cousteau quote and the science of curiosity
What Attest does and who it serves
From McKinsey consultant to SaaS founder
Desktop research and validating the TAM
Interviewing 200 people at Waterloo Station
Proving demand exists beyond corporate research teams
The Links of London area manager surprise
Zero to $1M ARR in 7.5 months
Compressing two years of startup into four months
Raising 650K pounds in seed funding
Meeting co-founder Tony Hunter at a startup event
Building the product for international scale
The November 2017 subscription flip
29-day sales cycle and $45K average contract value
Growing to 170 people and eight figures ARR
Why Attest's freemium experiment bombed
Competing against guesswork, not incumbents
Never hearing the term SDR until 18 months in
Lightning round
Resources
Full show notes: https://saasclub.io/331
Join 5,000+ SaaS founders: https://saasclub.io/email
S21:E6 - What it looks like to be an apprentice engineer at Pinterest (Alison Quaglia)
In this episode we talk about what being an apprentice engineer is like with Alison Quaglia, software engineer at Pinterest. Alison talks about switching careers into tech, landing an apprentice engineer role at Pinterest, what that apprenticeship looked like, and leveling up at Pinterest to software engineer.
Show Links
Partner with Dev & CodeNewbie! (sponsor)
Pinterest
Free Code Camp
HTML
CSS
Ruby
Rails
JavaScript
React
Redux
SQL
You Don't Know JS Yet
Into the Unknown: Advice for Breaking into the Tech Industry
Franken Mutt
Alison Quaglia
Alison Quaglia is a full stack engineer with a passion for UX/UI, currently helping to bridge the gap between development and design at Pinterest. Prior to transitioning into tech, she earned a BA in Anthropology from NYU and spent over 10 years working in various creative industries in NYC including fashion magazines, photo shoots, product development, brand consulting and special events for clients like Showtime, Hulu and Wu-Tang Clan.
Breaking Down Productivity Engineering with Micheal Benedict
About Micheal Benedict
Micheal Benedict leads Engineering Productivity at Pinterest. He and his team focus on developer experience, building tools and platforms for over a thousand engineers to effectively code, build, deploy and operate workloads on the cloud. Mr. Benedict has also built Infrastructure and Cloud Governance programs at Pinterest and previously, at Twitter -- focussed on managing cloud vendor relationships, infrastructure budget management, cloud migration, capacity forecasting and planning and cloud cost attribution (chargeback).
Links:
Pinterest: https://www.pinterest.com
Twitter: https://twitter.com/micheal
LinkedIn: https://www.linkedin.com/in/michealb/
Building a Partnership with Your Cloud Provider with Micheal Benedict
About Micheal
Micheal Benedict leads Engineering Productivity at Pinterest. He and his team focus on developer experience, building tools and platforms for over a thousand engineers to effectively code, build, deploy and operate workloads on the cloud. Mr. Benedict has also built Infrastructure and Cloud Governance programs at Pinterest and previously, at Twitter -- focussed on managing cloud vendor relationships, infrastructure budget management, cloud migration, capacity forecasting and planning and cloud cost attribution (chargeback).
Links:
Pinterest: https://www.pinterest.com
Teletraan: https://github.com/pinterest/teletraan
Twitter: https://twitter.com/micheal
Pinterestcareers.com: https://pinterestcareers.com
Build Your Analytics With A Collaborative And Expressive SQL IDE Using Querybook
Summary
SQL is the most widely used language for working with data, and yet the tools available for writing and collaborating on it are still clunky and inefficient. Frustrated with the lack of a modern IDE and collaborative workflow for managing the SQL queries and analysis of their big data environments, the team at Pinterest created Querybook. In this episode Justin Mejorada-Pier and Charlie Gu share the story of how the initial prototype for a data catalog ended up as one of their most widely used interfaces to their analytical data. They also discuss the unique combination of features that it offers, how it is implemented, and the path to releasing it as open source. Querybook is an impressive and unique piece of technology that is well worth exploring, so listen and try it out today.
Announcements
Hello and welcome to the Data Engineering Podcast, the show about modern data management
When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their managed Kubernetes platform it’s now even easier to deploy and scale your workflows, or try out the latest Helm charts from tools like Pulsar and Pachyderm. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform. Go to dataengineeringpodcast.com/linode today and get a $100 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show!
Firebolt is the fastest cloud data warehouse. Visit dataengineeringpodcast.com/firebolt to get started. The first 25 visitors will receive a Firebolt t-shirt.
Atlan is a collaborative workspace for data-driven teams, like Github for engineering or Figma for design teams. By acting as a virtual hub for data assets ranging from tables and dashboards to SQL snippets & code, Atlan enables teams to create a single source of truth for all their data assets, and collaborate across the modern data stack through deep integrations with tools like Snowflake, Slack, Looker and more. Go to dataengineeringpodcast.com/atlan today and sign up for a free trial. If you’re a data engineering podcast listener, you get credits worth $3000 on an annual subscription
Your host is Tobias Macey and today I’m interviewing Justin Mejorada-Pier and Charlie Gu about Querybook, an open source IDE for your big data projects
Interview
Introduction
How did you get involved in the area of data management?
Can you describe what Querybook is and the story behind it?
What are the main use cases or workflows that Querybook is designed for?
What are the shortcomings of dashboarding/BI tools that make something like Querybook necessary?
The tag line calls out the fact that Querybook is an IDE for "big data". What are the manifestations of that focus in the feature set and user experience?
Who are the target users of Querybook and how does that inform the feature priorities and user experience?
Can you describe how Querybook is architected?
How have the goals and design changed or evolved since you first began working on it?
What were some of the assumptions or design choices that you had to unwind in the process of open sourcing it?
What is the workflow for someone building a DataDoc with Querybook?
What is the experience of working as a collaborator on an analysis?
How do you handle lifecycle management of query results?
What are your thoughts on the potential for extending Querybook beyond SQL-oriented analysis and integrating something like Jupyter kernels?
What are the most interesting, innovative, or unexpected ways that you have seen Querybook used?
What are the most interesting, unexpected, or challenging lessons that you have learned while working on Querybook?
When is Querybook the wrong choice?
What do you have planned for the future of Querybook?
Contact Info
Justin
LinkedIn
Website
Charlie
czgu on GitHub
Parting Question
From your perspective, what is the biggest gap in the tooling or technology for data management today?
Closing Announcements
Thank you for listening! Don’t forget to check out our other show, Podcast.__init__ to learn about the Python language, its community, and the innovative ways it is being used.
Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.
If you’ve learned something or tried out a project from the show then tell us about it! Email hosts@dataengineeringpodcast.com) with your story.
To help other people find the show please leave a review on iTunes and tell your friends and co-workers
Join the community in the new Zulip chat workspace at dataengineeringpodcast.com/chat
Links
Querybook
Announcing Querybook as Open Source
Pinterest
University of Waterloo
Superset
Podcast Episode
Podcast.__init__ Episode
Sequel Pro
Presto
Trino
Podcast Episode
Flask
uWSGI
Podcast.__init__ Episode
Celery
Redis
SocketIO
Elasticsearch
Podcast Episode
Amundsen
Podcast Episode
Apache Atlas
DataHub
Podcast Episode
Okta
LDAP (Lightweight Directory Access Protocol)
Grand Rounds
The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA
Support Data Engineering Podcast
Blocking the haters as a service
Chou, a Stanford educated computer scientist and electrical engineer, cut her teeth in Silicon Valley with stints at Facebook, Quora, and Pinterest, where she advocated for a stronger focus on diversity.
Block Party describes its mission as building "anti-harassment tools against online abuse, but more fundamentally we are building solutions for user control, protection, and safety."
As CEO and lead engineer, Chou gets to choose the company's tools. Block Party is built with technologies like Render, Flask, and Jinja. Paul is very jealous of this stack.
Our lifeboat badge winner of the week is Bryan Oakley, who answered the question: How to redirect print statements to Tkinter text widget?
See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Recode Decode: Ben Silbermann
Pinterest CEO Ben Silbermann talks with Recode's Kara Swisher about deliberately engineering happiness into the site, expanding into commerce, and competing with larger social and commerce tech companies. This interview was recorded in front of a live audience at the National Retail Federation's annual conference, the Big Show, in New York City.
Featuring:
Ben Silbermann (@8en), CEO, Pinterest
Host:
Kara Swisher (@karaswisher), Recode co-founder and editor-at-large
More to explore:
Subscribe for free to Reset, Recode's new podcast that explores why — and how — tech is changing everything.
About Recode by Vox:
Recode by Vox helps you understand how tech is changing the world — and changing us.
Follow Us:
Newsletter: Recode Daily
Twitter: @Recode and @voxdotcom
Learn more about your ad choices. Visit podcastchoices.com/adchoices
Diversification in Recommender Systems with Ahsan Ashraf - TWiML Talk #187
In this episode of our Strata Data conference series, we’re joined by Ahsan Ashraf, data scientist at Pinterest. We discuss his presentation, “Diversification in recommender systems: Using topical variety to increase user satisfaction,” covering the experiments his team ran to explore the impact of diversification in user’s boards, the methodology his team used to incorporate variety into the Pinterest recommendation system and much more!
The show notes can be found at https://twimlai.com/talk/18
Episode 46: Tracy Chou
Tracy Chou has been a super early employee at Pinterest and Quora and has become one of the most respected voices in the diversity in tech conversation, both in terms of gender and in terms of race, We talk about 1) her experiences being both a women in tech and asian in tech, 2) what’s it meant for Tracy to become a public figure, 3) how she evaluates who she spends her time with and why, 4) having a social impact beyond tech and more. Edited by @Alexkontis Praise to @triketora Criticism to @eriktorenberg
Product Hunt Radio: Episode 10 w/ Zack Shapiro, Erik Torenberg, & Connor Montgomery
I know I say this all the time but this may be one of my favorite PHR episodes yet. Zack Shapiro (Co-Founded Luna, hacking on Product Hunt), Erik Torenberg (CEO of Rapt.fm, hustling on Product Hunt), and Connor Montgomery (Builder at Pinterest) join me, Ryan Hoover, on my windy rooftop. We chat about tinder for the elderly, our favorite easter eggs, and Erik raps about Product Hunt. No joke. Listen. Products mentioned: - Swift (http://www.producthunt.com/posts/swift) - Apple's innovative new programming language - Stitch (http://www.producthunt.com/posts/stitch) - Tinder for older adults - BarkBuddy (http://www.producthunt.com/posts/barkbuddy) - Tinder for dogs. Adopt cute pups that need a home - Kittyo (http://www.producthunt.com/posts/kittyo) - Play With Your Cat. Even When You're Not Home via Phone - Electric Objects (http://www.electricobjects.com/) - Put the Internet on your wall - Domainr (http://www.producthunt.com/posts/domainr) - Worldwide domain search - Oyster (https://www.oysterbooks.com/) - Netflix for books - EPIC! (http://www.producthunt.com/posts/epic) - Netflix for kids books - Pocket (https://getpocket.com/) - When you find something you want to view later, put it in Pocket - ClickHole by The Onion](http://www.producthunt.com/posts/clickhole-by-the-onion) - The most irresistibly shareable content on the internet - InstaNerd (http://www.producthunt.com/posts/instanerd) - Be smart, instantly - 5iler (http://www.producthunt.com/posts/5iler) - A notepad for the rhythm of your mind - OneTab (http://www.producthunt.com/posts/onetab) - Manage Your Tab-Hoarding - to.be Camera (http://www.producthunt.com/posts/to-be-camera) - The Augmented Reality Camera - "Hook" Product Hunt API](http://www.producthunt.com/posts/hook-producthunt-api) - Unofficial Product Hunt API for retrieving today's hunts - Notifyr (http://www.producthunt.com/posts/notifyr) - Receive iOS notifications on your Mac - Alfred (http://www.producthunt.com/posts/alfred) - Never use your mouse again - Shuddle (http://www.producthunt.com/posts/shuddle) - Uber for Families - Rhymer's Block (http://www.producthunt.com/posts/rhymers-block) - In-line rhyming dictionary for hip hop & poetry lyrics - Yo (http://www.producthunt.com/posts/yo) - A simple app to say "yo" to friends - bttn (http://www.producthunt.com/posts/bttn) - Press the bttn & Magic Happens™ (internet connected button)