Ryan Park
San Francisco, California, United States
1K followers
500+ connections
View mutual connections with Ryan
Welcome back
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
or
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
View mutual connections with Ryan
Welcome back
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
or
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
About
Welcome back
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
Experience & Education
-
ReadMe
************** *********** *******
-
******
*********** *******
-
***** *********
********* ********
-
******** **********
*.*. ******** *******
-
-
*** ****** ********** **********
*.*.*. *********** *******
-
View Ryan’s full experience
See their title, tenure and more.
Welcome back
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
or
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
View Ryan’s full profile
Sign in
Stay updated on your professional world
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
Other similar profiles
-
Trisha Le
San Francisco Bay AreaConnect -
Rafe Goldberg
Los Angeles, CAConnect -
Emily Kuo
San Francisco Bay AreaConnect -
Taryn King
Dallas-Fort Worth MetroplexConnect -
Brendan Luna
San Francisco Bay AreaConnect -
Aaron Hedges
Grand Rapids Metropolitan AreaConnect -
Bill Mill
Portland, MEConnect -
Darren Yong
San Francisco Bay AreaConnect -
Lyli N.
Product Experience Manager
Philadelphia, PAConnect -
Kenny Hoxworth
Pleasanton, CAConnect -
Kevin Ports
Madison, WIConnect -
Dominic Harrington
United KingdomConnect -
Derek Smith
Operations Engineer at Slack Technologies, Inc
San Francisco, CAConnect -
Nathan Shelby
Everett, WAConnect -
Nick Gerner
Seattle, WAConnect -
Xiaoyuan (Vivian) XU
SingaporeConnect -
Yuan Liu
Seattle, WAConnect -
Jorge Ortiz
San Francisco, CAConnect -
Zach Tratar
San Francisco Bay AreaConnect -
Danny Miller
Atlanta Metropolitan AreaConnect
Explore more posts
-
Shreyas Doshi
The biggest mindset shift most senior PMs / Designers / Eng Mgrs / TLs who are building customer-facing products in midsized & large companies must make: Your main job is to make your product win. While it may seem like this Job # 1 should be obvious to all, it really isn’t. Here are some other leading contenders for Job # 1: - Main job is to make my manager happy - Main job is to make execs happy - Main job is to keep stakeholders happy - Main job is to keep team members happy - Main job is to build excellent systems - Main job is to get promoted - Main job is to launch as promised - Main job is to create user delight - Main job is to create customer value (some people LOVE saying this one) Now, I understand that we live in the real world and that there are “good reasons” why the above contenders are at least worthy of consideration. But I am saying what I am saying precisely because we live in the real world and because I think you should do your best to improve your odds of *long-term career success*. You see, as a passionate & ambitious product person who builds the mindset of making your product win as your Job # 1, you will do things & learn things that most of your other peers are not doing & learning. And by doing that over the long arc of your career, you will position yourself to reach closer to whatever is your optimal success potential. This is clearly not the only possible path and it may not be the right path for some / many (no single path can be). But it is at least worth considering if it seems to feel right to you. Most people spend years / decades in mid-sized & large companies and yet are never even told that this is an option they should consider for their long-term career success. If that is you, I want you to view this post just as a possibly helpful pointer. If it doesn’t resonate, that’s totally fine. But if it does resonate, you might over the long-term see yourself becoming a more competent, a more effective, and possibly even a more happy product person.
927
54 Comments -
Anton Kropp
After a year of work my book Building A Startup - A Primer For The Individual Contributor is finally available! https://lnkd.in/erThxvpP If you’re working in or around startups as an IC or technical leader this book is for you. It’s based on 20 years of startup work and will help set you up for success to do more with less, move faster and more correct, and spend more time building features and product people love and less time banging your head at roadblocks and bottlenecks.
115
12 Comments -
Eugene Shih
"Your main job is to make your product win." I think this should apply to any product that your company makes. I also like what he says following this statement about what is NOT your main job. I will summarize here: "Your main job is not to make your manager happy, it is not to make execs happy." Also, note, this main job doesn't only apply to PMs, but also to senior Engineering Managers, Tech Leads, and Designers. #makeyourproductwin #leadership
5
1 Comment -
Rick Boone
Question for engineering leaders (managers, directors, VP's, etc): I'm curious about the current landscape of developer productivity analysis + management tools - things like LinearB and Jellyfish. Which tool, if any, are you using? Any opinions/pros/cons on the tool you're using (or the entire domain overall)?
11
-
Sagar Batchu
At Speakeasy we love working with devex leaders like Michael Heap to continuously raise the bar for what is "best in class" 🔥 We've been super lucky to work with him on what makes a great developer experience for iac and terraform. Come hear him and Thomas Rooney talk through how you can leverage OpenAPI and your API supply chain to build a provider and unlock the Terraform ecosystem. Link to the livestream in the comments 👇 #terraform #codegeneration #openapi
36
3 Comments -
Vinicius Dallacqua
Two articles about CMPs and their impact on performance. One excellent breakdown by Cliff Crocker shared by Tammy Everts! And one mentioning the collaboration of Google and CMPs to help reduce their impact on INP by Search Engine Journal: https://lnkd.in/dcQr9b6s. Some of the work I've done with our teams at Volvo Cars has shown simillar findings. But for our specific case it related the critical rendering path and how loading synchronously CMPs can delay critical resources discovery and loading. Even when those tags are injected at the <body>. Also the 'opted-in' experience is now on my radar to help establish these scenarios onto our performance governance and ensure that tags are properly managed.
3
-
Noah Greenberg
Polls can be a cheat code for earned media, and a great way to build authority. But there are levels to this. Here's how one of the best I've seen - Capital One - does it. (And what I'd do differently to increase earned coverage). Led by Shena Ashley, PhD, Capital One's Insights Center is a masterclass in leveraging polls to create unique insights that would do incredibly well via earned syndication. Here’s what they do great: ✅ Content that sticks: Crucial issues > fleeting trends. Focusing on topics like financial stability, mobility, and entrepreneurship, it's easier to rationalize investment on topics with a longer shelf life. Their insights + stories can drive coverage for months to come. ✅ Visual storytelling: Data doesn’t have to be dry, and Capital One presents original insights through clear and eye-pleasing visuals that are easy to understand. Publishers like charts, they love colorful charts, and they LOVE colorful charts that are easy to understand. Check, check, check. ✅ Strong methodologies and extensive polling numbers: Capital One frequently involves 7k+ participants in their studies - they are not half a**ing it. Well explained methodologies are table stakes to get your polls covered, and Capital One does a great job outlining their data collection process, sample size, and research methodologies. ✅ Easy to steal: Each report has multiple easy to take stories/soundbites, and are also written as full pieces of content, which can be taken as whole. Finally --- if I could change one thing... Add a byline. Brand publishing NEEDS a byline - no news outlet wants to cover a story that can't be credited back to a human. All in all, polls can be incredibly valuable for driving earned syndication - check out Capital One's Insights Center in comments for killer examples.
18
2 Comments -
Tom Leung
Here's a verbatim review from last month's cohort: "Tom's class is the only one on Maven thus far that I wholeheartedly rate a full 10 out of 10. Through fun assignments, we got hands-on practice on dealing with ambiguous, high-stake reviews. Beyond product reviews, Tom's extensive insights have been enormously helpful for a mid-career PM like me." I've got a new cohort starting in a few days for my 5-star rated, interactive, live, small-group workshops. Learn more and enroll here https://lnkd.in/gFFuUYpu #productmanagement
10
-
💾 Alex Martin
🐍 Job opportunity, y'all! Is anyone in my network with senior+ Python & GraphQL chops looking for a new role? Remote-first, good comp range, fun challenges to solve. This role will have some team leadership & support as well, so if you're trying to grow pure technically it may not be the right move for now. No kickback for me here, just trying to help a friend out. A few quick rules: - No contractors, agencies, etc. I'd like to recommend someone I know (or who is close to my personal network) for this one. - Possibly open to nearshore folks with US work authorization. You'll need overlap with US hours (EST-PST). - Please don't say "Interested!" or ask me to contact you in the comments. I know I'm asking for trouble posting this! 😅 I'll be very respectfully blocking anyone who decides this doesn't apply to them. - Feel free to tag folks in a comment if you think they might be a match. If you're interested or know someone who might be, shoot me a DM and I'll connect you/them to the right folks. 💬
18
3 Comments -
Ghazenfer Mansoor
We've all heard the horrifying tales of software projects spiraling out of control - bloated budgets, missed deadlines, lackluster products. What if you could wake up from these nightmares for good? My new guide covers everything you need to know about the key approaches for building software: 💻 Do it yourself (you're a product developer) 💻 Outsource it 💻 Build an in-house team 💻 Use a combination approach I break down the pros and cons of each option, so you can choose the right path for your product vision and avoid common pitfalls. No more sleepless nights wondering if you're on track. No more cold sweats thinking about looming disasters. Read the guide today and ensure your software build is a developer's dream, not a nightmare on Dev Street: https://lnkd.in/ehDG_JsN
8
1 Comment -
Amritpal Singh
Recent layoffs in Big tech might not just impact those directly let go, but also those waiting for employer sponsorship for Green Cards. Companies often have to freeze sponsorships for 6 months after layoffs, causing delays. This, coupled with the surge in applications mentioned in Business Insider article, can be discouraging. But here's the good news! You're not limited to waiting for your employer. Talented tech professionals might qualify for self-sponsored Green Cards through EB-1A (alien of extraordinary ability) or EB-2 NIW (National Interest Waiver). Don't let delays hold you back! Explore your options and take control of your future. I am doing a free webinar on educating fellow immigrants on how to self-sponsor and write your own destiny. Please provide your information here (Link: https://lnkd.in/gw7KmRE6)
26
1 Comment -
Paul Drake
Here's the biggest mistake I see software teams (and businesses) make when they're building something new. Premature optimization. It's a software mortal sin. When you're going from 0-1, there's a strong temptation to jump ahead mentally and try to solve future problems. Or, the allure of "sexier" feature ideas early in the development tends to detract from a disciplined focus on ensuring the core functionality actually satisfies the most important customer needs. Experienced product teams know the truth: building the foundation is difficult and it requires a significant amount of discipline and focus. Gall’s Law states that "all complex systems that work evolved from simpler systems that worked." If you want to build a complex system that works (with sexy features), build a simpler system first, and then improve it over time. How do you apply this principle to software? 1. Understand the problems that are most important to your customers 2. Build minimal set of functionality to address those problems 3. Launch to a group of early adopters and get their feedback 4. Refine + iterate #productmanagement #startups #principles #mvp #ux
3
-
Jason Gorman
As a long-time Line 6 Helix user, I found this interview with its architect Eric Klein really interesting. Much good talk about user experience and usability. "If somebody tells you there's a problem with what you're offering them, they're almost always right. But if someone tries to give you a solution to that problem, they're almost always wrong." Chimes strongly with my experiences over the years. Address needs. Solve problems. Taking feature requests from users is how products can die.
6
-
Julius Kabugu
Interesting read from DC Palter. Thoughts? ===== "Every founder thinks they want as much cash as they can get, but if they haven’t found product-market fit (and by definition, a pre-revenue company hasn’t found PMF) they’re going to need to pivot at least three times before they get rolling. The more they spend now on what will turn out to be a dead end, the harder it will be to pivot. Attempting to fly before you can crawl is a recipe for crashing." An Open Letter to VCs: Please Get Out of Pre-Seed Investing https://lnkd.in/gzC7HtZ8
5
-
Shepherd Walker
Alistair Gray gave a great talk at Write The Docs Portland, going into detail about our investment in Internal Docs at Stripe. He breaks down our thoughts about issues of fragmentation, discoverability, and document quality - and how we’ve tried to build great tools to improve the state of internal docs at Stripe across all of these axes. In Q&A, he touches on an important theme which is essentially “how do we convince engineers to use the tooling we build.” The answer really boils down to “ruthlessly build what engineers want” while maintaining our core primitives (eg, ownership, doc quality) that we know are vital to the health of Stripe’s knowledge base all-up. Let me know if y’all have any questions - happy to expand more on these themes! https://lnkd.in/em4QRFmH
26
-
Ankit Jain
I've had the privilege to know Max Kanat-Alexander for the last year through our Hangar DX community, and since then I've learned so much about DevEx him. Max is the author of Code Simplicity, was a TL at Google who defined the code review guidelines and was also the Chief architect of the Bugzilla project. I recently chatted with him about the Developer Productivity and Happiness framework that LinkedIn published last year. There are so many nuggets in that podcast that we may have to do a volume 2. Listen to the full episode on YT, Spotify or Apple podcasts: https://lnkd.in/dtAwVgBy Some takeaways: - There cannot be developer productivity without developer happiness - Iteration time and context switching are key concepts that impact developer productivity. - Understanding and catering to different personas of developers is crucial for effective developer productivity efforts. - It's significantly more important to understand what to measure than how to measure it. Most teams fall into the trap of measuring the wrong metrics. #developerproductivity #developerhappiness Checkout the Hangar DX community at https://dx.community We are hosting a Zoom session with William Howell from Okta this Thursday at 11am PDT!
15
-
Todd McGee
Stop (over-) engineering your prompts Generative AI is really cool. I use several tools in this category every day for writing suggestions, image generation and more. The tools can do amazing things, especially if given the right prompt. But there's a limit to how much prompt engineering one should do, especially if you're trying to generate text for mainstream consumption. This topic is already a bit of a bandwagon but this topic has been bugging me for about a week so I'm going to write about it. Generative AI relies on a class of machine learning applications broadly described as deep learning. Deep learning boils down to feeding a neural network a ton of content that has been classified into groups and then iterating over the content to allow the network to identify patterns in the content. Basically the network builds up statistical relationships between the words or other elements in the content. So it knows, for example, that if a piece of content is a recipe the word tomato is often followed by the words sauce or paste and very rarely by the word stem. But in a document about farming tomato is often followed by the word seed, starter or stem. The deep learning model has developed an elaborate matrix of statistical relationships between words in different types of content. If you described CHatGPT as an elaborate word guesser you wouldn't be wrong, just over-generalizing. Large language models are trained on billions of documents. So how, you might ask, are the documents classified in order to feed them into the neural network? Did someone categorize the web by hand? Of course not. The developers of the LLM leveraged Natural Language Processing (another deep learning application, btw) and other tools to categorize documents before they got fed into the model. Okay, but, again, what does that have to do with prompt engineering? When you ask an LLM to generate a piece of content, say a blog post about cycling in Northern California, you are specifying a category of content. If you later asked for an "image in Rubinesque style of a man and a woman engaged in flower picking while overhead rages a space battle between starships populated by photorealistic blob-like aliens carrying professional immersion blenders done in the style of pointillism" you have specified many categories. You're essentially asking the LLM to extract elements of the content that it was trained on that match your descriptors and which have mathematical relationships to other adjacent content elements and to include those in your generated image or blog post. And ... prompt engineering? The categories in the content were identified with Natural Language processing. Your prompt should be in natural language, not some over-specified, highly engineered artifical style. Don't over-think it, work with the model, don't try to control it too much. That's it.
2
Explore collaborative articles
We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
Explore MoreOthers named Ryan Park in United States
-
Ryan Park
Vice President of Marketing, Brand & Partnerships | Strategic Leader in Innovation & Growth 🚀
San Diego Metropolitan Area -
Ryan Park
New York City Metropolitan Area -
Ryan Park
Coppell, TX -
Ryan Park
Ann Arbor, MI -
Ryan Park
Williston, ND
311 others named Ryan Park in United States are on LinkedIn
See others named Ryan Park