Forem: Gary Sieling

How to Give Talks to Developers w/ Ben Orenstein

Gary Sieling — Fri, 01 Sep 2017 12:49:22 +0000

This is a great talk on how to give engaging tech talks. Ben Orenstein demonstrates how to engage your audience through a series of lightning talks.

Main Argument

It is more important to be entertaining than informative. You want people to enjoy and remember your talk.

He gives tons of tips-

Hit people with the thesis right away
Throw something weird at them
Good default language for talks (hold your hands out, rather than crossing your arms)
To reduce anxiety in advance, practice "power poses" in advance - acting confident makes you feel confident.
To work with anxiety during the delivery, scan for a "nodder" in the audience and make eye contact periodically - pretend you're giving the talk to this person
Good information with unenthusiastic delivery bores people - pick topics you care about
Avoid - "Sorry you can't see this from the back" - check the slides from the back of the room in advance
Don't apologize in advance to set expectations low
Don't be afraid of dead sound - if you ask for questions, people need a few seconds to think
Take a listening pose while waiting for questions
Speaking in a small, but packed room is high energy compared, but a big room that is half full will feel low energy

Discussion Questions

Have you found any tips that improved your talks?

Want to watch more talks? I built a search engine for talks -www.findlectures.com. I also send personalized recommendations by email.

What the Hacker News Front Page did for my app

Gary Sieling — Tue, 06 Jun 2017 13:22:23 +0000

On Sunday night, I posted a "Show HN", for a side project https://www.findlectures.com:

Luckily, I made it to the front page before WWDC coverage started. While the site was on the front page, I had roughly 50 concurrent users at any point.

Previously the site was featured on TNW and Lifehacker, roughly concurrently, which was about double the traffic from HN:

Side projects by their nature tend not to be polished - during this event, the folks on HN reported roughly fifteen issues, including a critical CSS issue on mobile, and an out of memory error on my Solr server.

During the previous traffic spike, I gained an appreciation for being able to quickly deploy changes (basically, use Heroku), so I was able to fix these quickly.

Since the last spike I have been instrumenting the site to get more feedback, which really paid off.

I have an email list of my "best of" talks, and on sign-up, it asks people if they have favorite speakers, or topics of interest.

Of email signups, 50% fill out the feedback form, which is about 100 times higher than I expected. From Hacker News, I got about 75 messages recommending speakers I should index.

Most of these notes were positive. A few were less so, and it's important to remember that is difficult for commenters to be empathetic through a screen, so a few people will forget that there are real people behind a project.

In the emails I send out, I also request feedback on the individual emails. On average 1% of recipients use this each week. I got an 3-4 notes from Hacker News readers who signed up, which is higher than normal (if you want to replicate this, use this awesome demo from codepen).

I recently added an functionality to get feedback on individual videos. There was no way to know if anyone would use this, but during this traffic spike, I was pleased to see several people make it through the different paths.

I'm also logging how far people get into videos, in Google Analytics, hoping that I can eventually train a machine learning model to improve the ranking:

In the end, the effect of the HN Front Page is over a hundred pieces of qualitative feedback, as well as several bits of data that I can use to improve the site for the future.

Side Projects Invigorate Software Engineering Culture

Gary Sieling — Tue, 30 May 2017 12:22:00 +0000

Dreaming up, planning, designing and building side projects often fosters a fresh, rejuvenated atmosphere of creativity, curiosity and possibility around a team. As a senior engineer, demonstrating that you value exploring ideas outside the domain of your direct focus encourages others on your team to do the same, to the benefit of all.

Software teams that restrict themselves to thinking only about their current project are apt to stagnate, fall behind and burn out. Teams that are lead to invest even a small fraction of their time investigating new tools, fresh concepts and emerging practices are much more likely to find a sustainable balance between productivity and fun.

This is especially true if you work on problems with a short information half-life, like web development. Even if your current technology choices are ideal, browsers and web protocols are changing rapidly around you, so you’re eventually forced into architectural changes.

Side projects are a great place to explore interesting problems with little risk. Unlike a work environment, you can abandon a project part way through, as there is no expectation of finishing. I store a lot of my projects in Bitbucket, because they have free, private git hosting, so I can choose if and when I want to reveal the work to the rest of the world.

Some companies like seeing job applicants have side projects, but these are typically hard to evaluate directly (does that project on your github even run?) The real value comes from the knowledge you acquire during the effort.

Once you get far enough with a project to write or speak on the subject, you can demonstrate thought leadership. If you’re in technology leadership this may increase the number of people applying for positions on your team, but more importantly, it makes joining your team much more desirable for people who are looking to grow.

Not all side projects are code - configuring and hardening a virtual machine with Wordpress is a fantastic learning experience. If you set up a blog, writing essays on your findings is a good personal growth exercise. I know a couple people who work for AWeber, and use the email marketing software to explore new ways for businesses to interact with customers (e.g. "100 words" and "Weekly Coffee" ). If you prefer to explore open source to “give back”, there are many small libraries with burned-out creators who’d like a reprieve.

In writing this piece, I consulted my peers and discussed lessons they’ve learned:

Building a project from scratch forces you to think through architectural decisions that are typically made for you. You will likely find that you can spend a lot of time on problems unrelated what you really want to solve (e.g. build tooling, user account management). Each of these problem has a seemingly infinite number of solutions. This has forced me think through the trade-offs inherent in architectural decisions, and improved my time management skills.

If you write code for exploratory purposes, your coding style will likely be a moving target, and you’ll find that you periodically step away from a project, and later return, likely forgetting parts of what you did. After a few months, this is a pretty accurate simulation of what it’s like to work on a real project - varied coding styles and potentially unfamiliar functionality.

I found that documenting problems as a I go helps me later - my blog provides me with auxiliary memory, which I consult regularly to refresh my memory on certain tasks.

Should you wish to write, there are many “weekly” email newsletters (JavaScript Weekly, and so on) - these always need high quality content and have large readerships, so if you want to work on essays for talks, these are good target audiences. There are also syndication sites that are friendly to software developers writing about their work - e.g. DZone, Dev.to, or the sideproject subreddit. If your friends or peers are also subscribed to any of these, it looks really good when your work shows up.

In some industries it is difficult or impossible to having public facing projects, because of security or IP concerns. If you choose to work on side projects, it’s important to give some thought to what you want to achieve, and how you will work within the constraints and opportunities at your disposal. Done well, these can be a great boost both to your career, and to the culture of your team.

Gary Sieling is a Software Architect at Wingspan Technology, and built a side project that lets you search over 150,000 lectures: https://www.findlectures.com, and an email list with curated talk recommendations.

5 Talks to Learn About AI

Gary Sieling — Tue, 31 Jan 2017 17:50:04 +0000

From building a search engine for lectures, I've found that there is more interest in artificial intelligence, as it the discipline migrates from research applications to highly visible commercial products. It can be difficult to find good introductory material, especially for people who are interested but non-technical.

Much of the research is very math-heavy, and productizing it can require software engineering and operational expertise. Further, the discipline is fragmenting around use cases and data formats - for instance, there are products that focus on working with images, sounds, or text, and many AI-based products are actually intended to be building blocks, rather than complete solutions.

In this post, I've collected several talks I've found that have helped me understand the connections between business and technical problems.

AI: A Return to Meaning - David Ferrucci - 65 minutes

I saw this talk by David Ferucci at Philly ETE. He led the team that created IBM's Jeopardy-winning Watson software. In this talk he covers how computer scientists have teach computers to grapple with natural language problems. Early attempts tended to be rule oriented (e.g. building databases of grammatical structures), but with time have moved to probability models. One of the compelling parts of this talk is a discussion of how Watson deals with ambiguity in Jeopardy games.

Anthony Levandowski: Google Driverless Cars

This talk covers some history and motivations for the development of driverless cars, including experimentation into driverless motorcycles and tractors. This started with early DARPA research, with a more recent focus on urban driving. This will give you a window into some of the non-technical problems around AI, as the investment into engineering and legal issues around autonomous vehicles is immense and complex.

http://chariotsolutions.com/screencast/philly-ete-keynote-screencast-claudia-perlich-the-big-data-revolution/

This is an older keynote, also from Philly ETE. The speaker works in online advertising - she talks about how internet advertising evolved to a market-based system, and how computer scientists think about buying the best ad space and combatting fraud. I thought this was also a helpful perspective of what researchers do on a day-to-day basis.

Seeing Machines Think

One of the challenging of machine learning is understanding what the computer is actually "learning." This talk focuses on a unique angle - novel visualization techniques to see inside the machine's mind. Some of this assumes a little bit of technical background, but if you stick through, they cover some interesting edge cases for where AI fails.

Amazon Machine Learning: Empowering Developers to Build Smart Applications

This is unfortunately a bit of a sales pitch for an Amazon product. It demonstrates what Amazon feels is useful for people who want to incorporate machine learning into their applications. This seems to be aimed at people who use spreadsheets to make business decisions (e.g. for an e-commerce site) but have a data volume beyond what Excel can handle. Since this is a product demo, it will give you an idea of some practical problems you'll face, like making sure your results are valid and repeatable, and controlling the balance of false negatives/positives.

More Resources
If you're interested in exploring these topics further, I've also found the AlchemyAPI demo site helpful for text analysis, and the PyImageSearch blog for learning about vision / image recognition problems.

Have any good talks you can recommend? Please comment below, and I'll include them in https://www.findlectures.com.

Hi, I'm Gary Sieling

Gary Sieling — Mon, 30 Jan 2017 01:58:40 +0000

I have been coding for 17+ years.

You can find me on GitHub as garysieling

I live in PA.

I work for Wingspan Technology.

I mostly program in these languages: Scala, Javascript, Java, Python, and SQL.

I am currently learning more about machine learning.

Nice to meet you.

6 Conference Talks to Level Up as a Developer

Gary Sieling — Tue, 03 Jan 2017 17:22:55 +0000

Conference talks are a great way to learn from other developers - writing one requires distilling hours of preparation, and the distilliation of potentially years of experience into an hour presentation. If you can find good conferences, you will hear many perspectives on up-and-coming tools, while learning from seasoned veterans.

Over the last year, I've been building a search engine for lectures, which includes thousands of software conference talks. Here are some of the best:

Web Design: The First Hundred Years with Maciej Ceglowski

Maciej CegÅ‚owski's talks blend history, software development, and humor. In this talk he draws lessons on software privacy from the rich history of U.S. / Soviet competition in the development of the aerospace industry.

Rails Conf 2013 How to Talk to Developers by Ben Orenstein

In this talk, Ben Orenstein demonstrates techniques to level up your presenting skills and make your talks memorable, using a creative series of lightning talks.

Google Driverless Cars

Autonomous vehicles are in the news a lot lately. This talk covers the history of the research, some basic mechanics of how they work, and what the future holds.

DEF CON 18 - Barnaby Jack - Jackpotting Automated Teller Machines Redux

Security is a big focus within the software industry, and will only become more important as awareness of security issues grow. In this talk, the presenter shows how he hacked specific model of ATM to spit out money, following the process from what he went through to purchase the ATM to developing and deploying software on a device that is hardened by design.

Alan Kay, 2015: Power of Simplicity

Alan Kay is one of the great figures in computer science - in this keynote talk, he shares his experiences from a career in software development.

Unconscious Bias @ Work | Google Ventures

This is a training video from a team at Google, on how to avoid allowing unconscious bias to affect HR decisions (hiring and performance reviews). While this is geared around preventing discrimination against women, it is intended to be generalized. The strength of this material is that the speaker covers a series of interesting recent psychological experiments, as well as data from Google and specific actions that they have taken to avoid unfair hiring practices.

Know something I've missed? Please send me your favorites!