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Project Clarity

~5 mins read

QA

current pains vision past learnings good bad ugly

1. Past, present, future for the company, team, person, and lifecycle
   • historical context
   • Present challenges and opportunities
   • Future vision and direction
2. Lifecycle
   • planning,
   • dev,
   • testing,,
   • deployments,
   • monitoring,
   • on-calls what could be better about the life-cycle? what do you like about it?
3. team dynamics
   • which teams are there
   • how do they collaborate
   • who is on this team and for how long
4. Good bad ugly
   • things to improve
   • things they like
   • churn/burn out/hardest parts
5. Growth
   • what have they been learning
   • how the work improved their skills (look if they just focus on tech)

courses

• sociology class
• humanities
• art of animation
• music
• advanced swimming

• econ

• accounting
• probability

• deutsch A2

• entrepreneurship
• IoT
• startup class

• tunga gungor, algorithms

• satellite space

• info retrieval, sentimental analysis project

• CNN lung disease detection
• electromagnetic field theory
• robotics
• microcontrollers, doodle jump, overcomplicated trajectory
• pattern recognition
• modern physics

planned Senior project poorly and did most of the work on the last week

overall, I overloaded myself and caused a lot of unnecessary stress, feel lucky to not get severe burnout

context

real estate analytics for an alumni

yacht market analytics

cosmetics analytics

retail analytics, supermarket products

• Crawl
• Set up a data pipeline
• Implement the business logic
• Sync to ElasticSearch and Metabase
• Create an API
• Create an orchestrator
• Set up monitoring
• Create recovery procedure
• Security review

entropy, manual decision tree > stats > NLP

then tried to create a generic system for all this, but it’s harder than it sounds, also given my overall experience at the time

• negotiation and pricing mistakes
• underestimating the cost to me and the benefit to the customer
• clarification mistakes,
• should only put enough effort to verify an approach
• distractions of a small business, accounting, office space, bills, contracts, …

• slow reporting, measure & debug, found the gitlab was the bottleneck, replaced with gitea

• manager change, guidance through identifying and prioritizing, charting the technical roadmap and communicating through both sessions and docs

• driven monitoring, log collection, telemetry, DevOps collab

• error codes feedback

• inter-team collaboration feedback
• visibility/communication feedback

DP

problems

• minio overeng story
• redis debug story
• reinventing dbt
• duct tape
• a custom system, hard for data engs

• slow builds, rewrite dockerfile, remove deps, parallelize tests and CI steps

• reverse engineered and diagrammed
• driven the discussion and planning, even discussed with the director and the CTO
• laid out the problems and our possible actions with their tradeoffs
• created an MVP and iterated it to feature parity and beyond
• simple to complex, standard library vs an orchestrator dependency, redis to postgres
• then led people to integrate it to other systems
• got 4 swes and 3 data engineers up to speed

• and had the happiness to see it flourishing

• new airo, adding people won’t help with deadlines
• onboarded juniors, no prisma orm, plain postgres
• dependency script

blackops

concept to production in 6 weeks manual entry bug initialization bug currency conversion bug, 10x the size, exposing us to more risk 5-7 concurrent traders, $20k, $1m trades per day

MS

MS onboarding volunteered for accessibility quickly joined on call for a complex system with 2 stacks and > 5 teams

WIP

FEEDBACK

fb: error codes

approach it as tech discussion of numbers vs names as enum keys rather than criticism

we decided to change the approach

fb: distractions after a manager change

shields vs funnels talk with my manager

haven’t solved but helped

DIFFICULT SITUATIONS

dif: minio overeng

suggested a session to address their concerns

led to improvements about deployment and monitoring processes

dif: nm, focus on one vs many

delegated but not really worked

dif: pushback against a deadline

a major release in 3 months and CTO meeting, shift resources

having new people are great in the long term but won’t help with releasing earlier in the short term

he already knew this but such feedback from the team helped to clarify expectations

COLLABORATION

guided an unhappy teammate in a chaotic period

provided direction with suggestions for things we can improve, pair programming

he turned out to be one of the most effective people in the team

onboarding 3 junior engs

created onboarding docs

creating helpful starting tasks

pair programming

no data engs

cover but advocate

doodle jump

overcomplicated trajectory

process the main character image

TECH

tech: slow gitlab

tech: driven monitoring work

little structure, no telemetry

better monitoring

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stories are about people

so if I think of people I worked with, I can come up with some interesting cases, and the stories don’t have to be extraordinary