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Your AI coding agent comes with defaults: which model runs, what you pay, and what leaves your machine. You can turn those defaults into choices. In our new short course, AI Coding Workflows: From Cloud to Local, built in partnership with JetBrains and taught by Paul Everitt | @[email protected],... show more

DeepLearning.AI

350,142 subscribers

18,765 次观看 • 2 个月前 •via X (Twitter)

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Tony Tong | Founder | Ancient Systems x AI 的头像

Tony Tong | Founder | Ancient Systems x AI2 个月前

@jetbrains @paulweveritt Defaults hide decisions, whether it's a coding agent or a career. Back in 2016 I interviewed a startup co-founder for a founder interview show, and the pattern across guests like her was nobody explains their real decision process, they just show you the result.

Rachel Alvarez 的头像

Rachel Alvarez2 个月前

@jetbrains @paulweveritt Amazing you are building @DeepLearningAI! It’s super useful

安叫兽|Bird🕊️ 🔶 BNB 的头像

安叫兽|Bird🕊️ 🔶 BNB2 个月前

@jetbrains @paulweveritt 默认配置最容易被忽略，数据去哪儿确实该先搞清楚。

Tanvir 的头像

Tanvir2 个月前

@jetbrains @paulweveritt Great practical guide for building smarter workflows

Saqlain Yousuf 的头像

Saqlain Yousuf2 个月前

@jetbrains @paulweveritt Model choice looks like an intelligence decision. In practice it’s an infrastructure decision: cost ceiling, privacy boundary, latency, and whether your workflow survives a provider change. Local support isn’t a feature. It’s an exit option.

bee 的头像

bee2 个月前

@jetbrains @paulweveritt Thread 1 What a timely drop ! As an educator in the vfx & animation industry I struggle with this everyday. please add chapters on how to improve local llm (gemma4) failure recovery. -

Bob Lee 的头像

Bob Lee2 个月前

@jetbrains @paulweveritt The underrated part is making model choice boring. If switching clouds or going local changes the workflow, the abstraction leaked.

Web3WithAi 的头像

Web3WithAi2 个月前

@jetbrains @paulweveritt Finally someone addressing the actual control issues—defaults hide a lot of decisions we should be making ourselves.

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