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As a self-described "gainfully unemployed data person", Josh Wills is an angel investor and has worked on and led data teams at Slack, Cloudera, WeaveGrid and Google. We discuss:
How to get started with angel investing without a ton of $$
Attributes that define great engineering managers
What's it like transitioning from management back to IC
Challenges in Climate Tech from a software perspective
And more
Segments:
[0:01:35] Transitioning from management to individual contributor (IC).
[0:10:19] Emotional intelligence and its role in engineering management.
[0:25:21] Contrasting the hard power of management with the soft power of senior individual contributors.
[0:37:18] Addressing challenges in climate technology.
[0:51:34] The importance of practicality and how to assess it in interviews.
[0:56:01] Josh's journey into angel investing.
[1:12:59] Criteria used by Josh to evaluate whether to invest in a startup.
Show Notes:
Josh on Twitter: https://twitter.com/josh_wills
The "Touchy Feely" course at Stanford: https://www.gsb.stanford.edu/experience/learning/leadership/interpersonal-dynamics
Jason Calacanis's book on angel investing: https://www.amazon.com/Angel-Invest-Technology-Startups-Timeless-Investor/dp/0062560700
Stay in touch:
π Make Ronak's day by leaving us a review and let us know who we should talk to next! [email protected]
Known for coining the term "Data Scientist", DJ is a renowned technologist with a diverse background spanning academia, industry, and government. Having led product teams at companies like RelateIQ and LinkedIn, DJ was appointed by President Obama to be the first U.S. Chief Data Scientist where his efforts led to the establishment of nearly 40 Chief Data Officer roles across the Federal government, new health care programs as well as new criminal justice reforms. We discuss:
"Dream in years, plan in months, evaluate in weeks, ship daily"
High school misadventures that shaped DJ's world view
Under-hyped opportunities in AI
Building with the customer vs. "if you build it, they will come"
Do we need more regulations on AI?
Much more.
Segments:
[0:01:48] Picking locks in high school.
[0:07:15] How can we make it easier for others to take a risk on us?
[0:11:29] How do you decide whom to take a chance on?
[0:14:24] The 70-20-10 framework for choosing what to work on.
[0:17:49] "No rules, only guidelines."
[0:24:09] Developing personal ethics.
[0:30:52] Building with the customer versus "if you build it, they will come."
[0:34:51] "Dream in years, plan in months, evaluate in weeks, ship daily."
[0:43:56] Ideas should be considered in terms of momentum.
[0:46:11] Under-hyped trends in AI?
[0:51:53] How does AI need to evolve to operate in fields that require very low margins of error?
[0:56:09] Concerning advances that lack sufficient guardrails?
[0:58:55] Do we need more regulations on AI?
[1:02:48] "Failure is the only option."
Show Notes:
DJ Patil on Linkedin: https://www.linkedin.com/in/dpatil/
The card that DJ carried in his notebook: https://twitter.com/DJ44/status/819316928623902720
DJ's interview series with thought leaders in Data Science: https://www.linkedin.com/learning/data-impact-with-dj-patil/data-science-how-did-we-get-here
Stay in touch:
π Make Ronak's day by leaving us a review and let us know who we should talk to next! [email protected]
Erica is a former VP of Engineering at LinkedIn. Having almost dropped out of college, Erica's journey in tech is a testament to her perseverance and dedication. In addition to leading engineering teams at LinkedIn, Erica founded WIT (Women In Tech) to empower women within the company as well as the broader tech community. We discuss:
How to create incentives for diversity-building work.
Building your personal "board of directors".
Balancing mentoring work vs sprint tickets.
Structuring a community for long-term success.
Much more.
Segments:
[0:18:04] building women-in-tech and the importance of leading by example
[0:21:17] creating incentives for diversity-building work
[0:23:30] examples of building better products with more diverse stakeholders
[0:29:48] how to spot red flags during the interview process
[0:32:51] do men and women bring different skill sets to the problem or it's all individual based?
[0:35:34] building your personal "board of directors"
[0:40:21] how to ask people for mentorship if I'm shy?
[0:44:21] exploring new projects
[0:53:32] how to hold yourself accountable when there's no structure?
[1:03:17] how to structure a community for long-term success
[1:10:22] how to balance mentoring work vs sprint tickets
[1:14:57] journey to being on the advisory board for SJU
Show Notes:
Erica on Linkedin: https://www.linkedin.com/in/ericalockheimer/
Stay in touch:
π Make Ronak's day by leaving us a review and let us know who we should talk to next! [email protected]
Mitchell co-founded HashiCorp in 2012 and created many important infrastructure tools, such as Terraform, Vagrant, Packer, and Consul. In addition to being a prolific engineer, Mitchell grew HashiCorp into a multi-billion-dollar public company. We discuss:
How to structure large projects to avoid demotivation or burnout
The "A.P.P.L.E" framework for diffusing tense situations and handling trolls
How to decide what to work on
Mitchell's unconventional transitions from CEO to CTO and then back to an individual contributor (IC)
The quality that Mitchell values the most in an engineering team.
[0:14:19] Impactful lessons from working at the Apple Store in college
[0:22:26] Origin story of HashiCorp
[0:26:08] College side project that turned into Mitchell's first financial success
[0:31:25] Why infrastructure?
[0:39:50] How individual products came about
[0:44:17] Challenges of fundraising as a company with an umbrella of products
[0:48:20] Balancing being the CTO and writing code: "I didn't want to be that CTO that just produced technical debt"
[0:53:09] Transitioning from CEO to co-CTO
[0:57:26] From CTO to Individual Contributor
[1:06:03] What's next?
Show Notes:
Mitchell's blog: https://mitchellh.com/writing
The "APPLE" principle that has guided Mitchell throughout his career: https://mitchellh.com/writing/apple-the-key-to-my-success
Mitchell's Startup Banking Story π: https://mitchellh.com/writing/my-startup-banking-story
Stay in touch:
π Make Ronak's day by leaving us a review and let us know who we should talk to next! [email protected]
After 17 years building SRE teams at Google and serving as the Site Lead for Engineering in Dublin, Dave joined Elastic as the Sr Director of Engineering and later VP of Engineering at Twilio. Following a recent career break, Dave now divides his time between coaching engineering leaders and consulting to help busy teams be more effective. In the heart of our conversation, Dave shares the frameworks and practical tips he's amassed for making the most of the mentorship experience.
Segments:
[00:01:45] Growing remote SRE team as the Google Dublin Site Lead
[00:19:49] Company Culture vs Company Values
[00:23:47] How to find companies that are serious about remote work
[00:34:26] Coaching vs Mentoring at Big vs Small companies
[00:38:35] How Google does coaching & mentoring
[00:41:38] What makes a good 1-1
[00:46:56] Considerations for seeking out a mentor
[01:03:27] Getting external mentorship while working at a small company
[1:08:20] How to set specific goals for mentorship
[1:20:13] The "CIA" Method for career decision making
[1:31:08] How to sunset mentorship 1-1s
[1:35:20] Venturing into consulting to help busy teams be more effective
[1:42:13] How to get started with consulting
Show Notes:
Dave on LinkedIn: https://www.linkedin.com/in/gerrowadat/
Dave's personal website: https://log.andvari.net/pages/about.html
Dave's coaching website: https://www.strategichopes.co/
Service Level Objectives by Alex Hidalgo: https://www.oreilly.com/library/view/implementing-service-level/9781492076803/
The Staff Engineer's Path by Tanya Reilly: https://www.oreilly.com/library/view/the-staff-engineers/9781098118723/
Stay in touch:
π Let us know who we should talk to next! [email protected]
At the personal request of Reid Hoffman to emerge from early retirement, David joined LinkedIn in 2009 during a period of rapid growth to help stabilize the chaos, cultivating a much-needed culture of "Site Up and Secure." Before this, David served as SVP of Engineering and Operations at Yahoo!, overseeing their Search Marketing organization and the Production Operations infrastructure for the entire company. Throughout his career, David has held multiple leadership positions and is recognized as one of the top operations executives. David's intensity, passion, courage and commitment to work have always been deeply admired by his colleagues and his wisdom, well captured in one line axioms, better known as Henkeisms, are still echoed at LinkedIn.
This episode was first published almost 3 years ago and we are sharing it again because it's been one of our favorites :) Hope you like it too!
Segments:[00:01:37] "This is my freaking site" poster
[00:04:10] David's first 2 retirements and starting at LinkedIn
[00:09:41] IC to Management
[00:17:20] Site-Up Culture
[00:21:58] Re-architecting LinkedIn's release process
[00:27:23] War stories from Yahoo: The 10G Massacre
[00:32:06] "Go to work every day willing to be fired": Project Panama at Yahoo
[00:43:33] The power of Individual Contributors
Show Notes:David Henke on LinkedIn
Learning to Lead - David Henke's talk on leadership which he delivered at his alma mater - UCSB
Project Inversion at LinkedIn
π Let us know who we should talk to next! [email protected]
Before joining CueIn last year as a Founding Data Scientist, Melissa was a Lead Data Scientist at Salesforce working on the Einstein Platform that focused on automating Data Science workflows. In this conversation we dive into Melissa's unique journey, what to do in the face of increasing job automation and explore the latest developments in practical AI.
Segments:[00:02:13] Melissa's background in computational neuroscience
[00:06:08] 7 years at Salesforce vs startup
[00:11:31] Joining CueIn
[00:19:30] Chatbot observability
[00:28:16] Feedback loops
[00:33:10] Use LLM to observe.. LLMs?
[00:39:06] AI automating jobs
[00:43:01] Doing ML in 2017 vs now
[00:50:35] Few shot learning, Hugging Face
Show Notes:Melissa's Linkedin: https://www.linkedin.com/in/melissajanerunfeldt/
π Let us know who we should talk to next! [email protected]
What's it like to open source an internal project at a big tech company like LinkedIn? When should a company open source a project and what are the benefits and challenges that come along with it? If you want to open source an internal project, how should you go about advocating for it?
FΓ©lix is a Principal Staff Engineer at LinkedIn where he works on the data infrastructure team that builds Venice. Venice is a distributed derived data store which LinkedIn open sourced in the fall of 2022.
He joins the show to chat about his experiences leading the open source efforts for Venice, as well as his thoughts on balancing leadership with execution, delegating responsibility and fostering a culture of ownership, and growth within a team.
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Show Notes:
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Stay in Touch:
βοΈ Subscribe to our newsletter: https://softwaremisadventures.com
π Let us know who we should talk to next! [email protected]
---
Segments:
[0:01:36] Introduction
[0:02:32] Career Choices and Job Satisfaction
[0:08:34] Understanding Venice: LinkedIn's Distributed Derived Data Store
[0:22:37] The Journey of Open-Sourcing Venice
[0:26:36] Understanding the Business Perspective of Open Source Systems
[0:30:28] How and when to advocate for open-sourcing an internal project
[0:39:32] Challenges and Strategies in Open Source Project Maintenance
[0:46:40] Balancing Leadership and Execution in Engineering Roles
Should engineers and product managers "stay in their lanes"? What big company habits should you keep vs unlearn when transitioning to working at a start-up? Could an ayahuasca retreat give you more clarity on your career goals? Ilya and Arnab join the show to share their journey quitting big tech to bootstrap a podcasting startup.
Arnab and Ilya are the co-founders of Metacast. Before starting the company, Arnab was a Principal Engineer at AWS while Ilya was a Sr. Product Manager at Google and Principal PM at Amazon before that. While at Amazon, Arnab and Ilya worked together on various projects including AWS Chatbot, which they started from scratch and launched into a successful AWS service.
Show Notes:
Stay in Touch:
βοΈ Subscribe to our newsletter: https://softwaremisadventures.com
π Let us know who we should talk to next! [email protected]
Segments:
[0:00:00] Starting Metacast
[0:05:39] Should engineers and product managers "stay in their lanes"?
[0:11:56] How to decide when to explore options vs committing to a decision
[0:14:46] Do you have to be a specialist to be successful?
[0:18:20] Quitting Amazon & Google
[0:33:52] Spiritual retreat
[0:47:09] Trying therapy
[0:51:33] Orthogonal weaknesses
[0:57:31] Big co habits to keep vs unlearn
[1:04:32] Metacast Milestones
What's "AI in a Box"? Pete Warden joins the show to share a new project he recently launched that encapulates Language Transcription/Translation and Question Answering capabilities into a wallet-sized board running locally without internet, as well as stories and learnings from building his new company, Useful Sensors, after 7 years of leading the tensorflow mobile project at Google.
Pete is the CEO of Useful Sensors. After founding his own company Jetpac and selling it to Google in 2014, he became a staff research engineer at Google, where he led the TensorFlow Mobile team. Pete is also the author of two well-received books: "Public Data Sources" and "Big Data Glossary" and builder of OpenHeatMap.
Show Notes:
Stay in touch:
βοΈ Subscribe to our newsletter: https://softwaremisadventures.com
π Send feedback or say hi: [email protected]
Segments:
[0:00:00] Failing and trying again, experiential learning
[0:03:13] AI-in-a-box demo
[0:07:28] Animatronics?
[0:10:12] Privacy and trust
[0:12:04] Talk to your appliances
[0:15:22] How to fit the LLM into such a small chip?
[0:16:50] Quantization
[0:20:07] Disposable ML frameworks
[0:24:33] Updating model on shipped hardware
[0:28:34] LLMs with specialized domain knowledge
[0:30:08] Founding Useful Sensors
[0:37:07] scaling training vs inference
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