culture
13 notes tagged culture in the Applied LLMs topic. Putting language models to work: retrieval, prompting, evaluation and the behavior you only learn in production.
- How trust works at Dwarves: from your team to the people we call first
Trust grows in three circles, from your team to the people we call first in a crisis. What each circle gets, what membership costs, and how a person or a report loses it.
- We stopped testing engineers on speed
Dwarves cut the weight of timed algorithm problems in its technical interview from 60% to 15%. The dates, the weights, and the new hour.
- Record a Discord talk on your own machine
Discord has no recorder, and a copy captured off the call costs three quarters of the pixels. Record locally as the presenter, have the host capture the call for the…
- What the Engelberg report got right about us
Thoughtworks published the findings of its second Future of Software Engineering retreat. Most of what the room converged on is what we have been learning and putting…
- What stays valuable when anyone can build anything
As AI makes building cheap, value concentrates in judgment (inside) and trust (outside): the two inputs it cannot mass-produce. A lens on what to own in the AI era.
- The tells
AI writing gives itself away at the level of structure, not word choice. A field guide to the patterns, and the guideline change that bans them from our posts.
- Better engineering
A personal take on how AI is changing software development and why better engineering still comes down to human judgment, not just better tools.
- Engineers in the AI landscape: architects, tinkerers, planners, and the vibers
Exploring the new archetypes of software engineers in the age of AI: architects, tinkerers, planners, and vibers.
- Strategic thinking behind our hiring
Why we're building a complete pipeline from research to delivery - the philosophy behind our role strategy and how it supports our research-first consulting model.
- Skillmaxing
A guide for talents on how to cultivate the mindset and skills to become a proven, AI-augmented engineer, inspired by the principles of vetting top-tier individuals.
- Vetting proven talents
Guidelines and criteria for vetting high-level engineering talents, especially those leveraging AI.
- Working with legacy code
Learn how to navigate large, established codebases without losing your sanity. Discover technical strategies, cultural insights, and AI assistance for thriving in…
- Ideas over titles at Dwarves
The working principles behind how Dwarves runs its team, from ideas that win on merit to open check-ins, hiring on skill and shipping to users, collected from culture…