“Remember “What got you here won’t get you there”. When you move to a lead developer role you need to develop from “maker” mode into “multiplier” mode. Become more of a gardener” @patkua#LeadDevBerlin
“People are not computers. People cannot be programmed. Blurry is the new binary in your new role as a lead developer. There is no single right answer. You’ll never know what all people want, but you can be certain it’ll be different” @patkua#LeadDevBerlin
“Different models of decisions making:
- autocratic
- consultative (consult but reserve right to decide)
- democratic or consensus-driven.
Even democratic isn’t binary - eg Roman Voting people vote either in favour, opposed, or happy to go w majority” @patkua#LeadDevBerlin
Excellent opening talk at #LeadDevBerlin from @patkua on The Way of the Lead Developer:
- Maker to Multiplier
- Blurry is the new Binary
- Motivate over Moan
👏🏽👏🏽👏🏽
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Latest in the “moving into tech leadership and/or management” subtheme here today at #LeadDevSanFrancisco is “Becoming a Manager Somewhere Else” from @mybluewristband
“Not all the advice provided in this talk will definitely work for you, as it’s my own story”
Jenn’s Career Trajectory:
- civil engineer
- mechanical engineer
- structural engineer
- customer support (to get foot in the door of tech)
- web developer (~5 years)
- software engineer (again. Another 3 yrs)
- moving towards management
“Three Things to Look for in the Person:
[0) Care about people (non-neg) ] 1) Doubts (filter out power hungry) 2) Growth mindset (highly competent at engineering —> highly incompetent at managing) 3) Courage to be disliked (recognition changes)
“Inclusion is a foundation for setting and creating a level playing field for people to be given opportunities to succeed. Inclusion has to presume competence.”
I love the @TheLeadDev crowd so much. They just gave @carlaprvieira applause and whooping for explaining it’s her first time in the US and her first international conference talk here at #LeadDevSanFrancisco 🥰🥰🥰💖💖💖
“Bias is like a virus that travels and is replicated by machine learning models.”
Potential Harms Caused by AI Systems: 1) Bias & discrimination 2) Denial of individual autonomic rights 3) Non-transparent, unexplainable or unjustifiable outcomes 4) Invasions of privacy 5) Unreliable, unsafe or poor quality outcomes