Tom So

@tomso

Deep into web3 social, bit of a generalist In the crypto rabbit hole (as I should). Also super into startups, everything social and community building. I usually read on product management and career development - I add engineering sprinkles to the mix bc why not

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In this guide, I want to go very deep on all the experiences, resume tips and interview strategies you’ll need to get an Associate Product Manager role.

Substack • The Associate Product Manager Playbook

25/25) I would praise SOL if it pivoted & fixed these flaws The problem is that it would require changing the very attributes that where sold as "features" to investors Human nature tends to double down on such mistakes Especially considering the money involved... See more

Justin Bons twitter.com

blockchain and

High-level insight

Most companies do not operate in ways they realize their vision by continuously aligning business goals with customers' needs and pain points. Product teams need to be aligned on business objectives and be allowed to operate at an initiative level to impact those objectives.

Author describes different processes to set product team... See more

Melissa Perri • Escaping the Build Trap: How Effective Product Management Creates Real Value

A thread about social graphs and how web3 brings a paradigm shift in how social networks will be built in the future: 🧵

nader dabit twitter.com

Web 3.0 and

1/There is a general misconception that DeSoc is intended to make visible your social graph in a public panopticon way. A "God's eye view" is not the goal. In fact, no two people should have the same partial view.

name twitter.com

DeSOC (decentralised Society) and

In the insightful (and accessible) book Design for How People Learn, Julie Dirksen covers five "gaps" that inhibit learning (and applying) something new:Knowledge GapSkills Gap (Knowledge + Practice)Motivation GapHabit GapEnvironment Gap

The Beautiful Mess • TBM 44/52: Making Optional Product Practices Stick

A startup’s data room is key for raising venture capital. But many founders waste time compiling data investors don’t want or need. From @venturetwins, a 🧵 on what founders need to know, including specific data investors want to see, info to leave out, and traps to avoid.👇

name twitter.com

Data and

The size and sophistication of these models make it impossible to fully understand how they make predictions. They have billions of weights that interact in subtle ways to make a final prediction; looking at them is like hoping to understand psychology by examining individual brain cells. Even in academic settings with well-established models, the... See more

future.com • How Recommendation Algorithms Actually Work | Future - https://future.com/forget-open-source-algorithms-focus-on-experiments-instead

The Superhuman Product/Market Fit Engine

coda.io

High Performance Lifestyle and