gfqdjb

gfqdjb

The reality of AI-Assisted software engineering productivity

tl;dr: AI functions as a situational force multiplier - providing modest, uneven boosts that augment rather than transform engineering productivity. Individual developers and those working on “new” projects see speed boosts with AI tools, but these gains aren’t (yet) translating to overall team productivity:

  • AI excels at greenfield projects but struggles with complex legacy codebases
  • 84% of devs use AI tools; only 60% view them favorably, down from 70% in 2023
  • Studies show 20-30% productivity improvements, far from “10x” claims
  • Most use basic autocomplete features, not full autonomous coding agents
  • 66% cite AI’s “almost correct” solutions their biggest time sink due to debugging

Read in full here:

Where Next?

Popular Ai topics Top

First poster: bot
AI Is Discovering Patterns in Pure Mathematics That Have Never Been Seen Before. We can add suggesting and proving mathematical theorems...
New
New
CommunityNews
GitHub - MadRabbit/halmak: The final version of the AI designed keyboard layout. The final version of the AI designed keyboard layout - ...
New
First poster: bot
DeepMind AI learns simple physics like a baby. Neural network could be a step towards programs for studying how human infants learn.
New
First poster: bot
Chri Besenbruch, CEO of Deep Render, sees many problems with the way video compression standards are developed today. He thinks they aren...
New
First poster: bot
Exascale Cerebras Andromeda cluster packs more cores than 1,954 Nvidia A100 GPUs.
New
First poster: bot
BBC documentary used face-swapping AI to hide protesters’ identities. Filmmakers used an AI to swap the faces of anti-government protest...
New
First poster: alvinkatojr
Giving AI systems the ability to focus on particular brain regions can make them much better at reconstructing images of what a monkey is...
New
First poster: AstonJ
From fear to optimism: why I am convinced AI is worth embracing.
New
CommunityNews
Study shows how patterns in LLM training data can lead to “parahuman” responses.
New

Other popular topics Top

PragmaticBookshelf
Learn from the award-winning programming series that inspired the Elixir language, and go on a step-by-step journey through the most impo...
New
AstonJ
Or looking forward to? :nerd_face:
485 12600 258
New
Exadra37
I am thinking in building or buy a desktop computer for programing, both professionally and on my free time, and my choice of OS is Linux...
New
Exadra37
Please tell us what is your preferred monitor setup for programming(not gaming) and why you have chosen it. Does your monitor have eye p...
New
AstonJ
I’ve been hearing quite a lot of comments relating to the sound of a keyboard, with one of the most desirable of these called ‘thock’, he...
New
PragmaticBookshelf
Author Spotlight Rebecca Skinner @RebeccaSkinner Welcome to our latest author spotlight, where we sit down with Rebecca Skinner, auth...
New
PragmaticBookshelf
Author Spotlight: VM Brasseur @vmbrasseur We have a treat for you today! We turn the spotlight onto Open Source as we sit down with V...
New
PragmaticBookshelf
Get the comprehensive, insider information you need for Rails 8 with the new edition of this award-winning classic. Sam Ruby @rubys ...
New
AstonJ
Curious what kind of results others are getting, I think actually prefer the 7B model to the 32B model, not only is it faster but the qua...
New
PragmaticBookshelf
A concise guide to MySQL 9 database administration, covering fundamental concepts, techniques, and best practices. Neil Smyth MySQL...
New