21–30 of 372 posts
My buddy is at GH working on an adjacent project & he hasn't stopped talking about this for the last few days. I think I've been reminded to 'make sure I tune into the keynote on Monday' at least 8 times now. I gave up trying to watch the stream after the third authentication timeout, but if I'd known it was this I'd maybe have tried a fourth time.
What specific keynote are they referring to? I'm curious, but thus far my searches have failed
I tried doing some vibe coding on a greenfield project (using gemini 2.5 pro + cline). On one hand - super impressive, a major productivity booster (even compared to using a non-integrated LLM chat interface). I noticed that LLMs need a very heavy hand in guiding the architecture, otherwise they'll add architectural tech debt. One easy example is that I noticed them breaking abstractions (putting things where they do…
> LLMs need a very heavy hand in guiding the architecture, otherwise they'll add architectural tech debt I wonder if the next phase would be the rise of (AI-driven?) "linters" that check that the implementation matches the architecture definition.
Everything old is new again!
> Copilot excels at low-to-medium complexity tasks in well-tested codebases, from adding features and fixing bugs to extending tests, refactoring, and improving documentation. Bounds bounds bounds bounds. The important part for humans seems to be maintaining boundaries for AI. If your well-tested codebase has the tests built thru AI, its probably not going to work. I think its somewhat telling that they can't share n…
In any case, I think this is the best use case for AI in programming—as a force multiplier for the developer. It’s for the best benefit of both AI and humanity for AI to avoid diminishing the creativity, agency and critical thinking skills of its human operators. AI should be task oriented, but high level decision-making and planning should always be a human task.
So I think our use of AI for programming should remain heavily human-driven for the long term. Ultimately, its use should involve enriching humans’ capabilities over churning out features for profit, though there are obvious limits to that.
[0] https://www.cnbc.com/2025/04/29/satya-nadella-says-as-much-a...
> Copilot excels at low-to-medium complexity tasks Oh cool! > in well-tested codebases Oh ok never mind
I tried doing some vibe coding on a greenfield project (using gemini 2.5 pro + cline). On one hand - super impressive, a major productivity booster (even compared to using a non-integrated LLM chat interface). I noticed that LLMs need a very heavy hand in guiding the architecture, otherwise they'll add architectural tech debt. One easy example is that I noticed them breaking abstractions (putting things where they do…
> I also ended up blowing through $15 of LLM tokens in a single evening. This is a feature, not a bug. LLMs are going to be the next "OMG my AWS bill" phenomenon.
It seems Copilot could have really owned the vibe coding space. But that didn’t happen. I wonder why? Lots of ideas gummed up in organizational inefficiencies, etc?
I tried doing some vibe coding on a greenfield project (using gemini 2.5 pro + cline). On one hand - super impressive, a major productivity booster (even compared to using a non-integrated LLM chat interface). I noticed that LLMs need a very heavy hand in guiding the architecture, otherwise they'll add architectural tech debt. One easy example is that I noticed them breaking abstractions (putting things where they do…
Consider using Aider, and aggressively managing the context (via /add, /drop and /clear).
GitHub had this exact feature late last year itself, perhaps under a slightly different name.
That seemed to drop off the Github changelog after February. I’m wondering if that team got reallocated to the copilot agent.