[AloysB]

Give it a read, he mentions briefly how he uses for PR triages and resolving GH issues.

He doesn't go in details, but there is a bit:

> Issue and PR triage/review. Agents are good at using gh (GitHub CLI), so I manually scripted a quick way to spin up a bunch in parallel to triage issues. I would NOT allow agents to respond, I just wanted reports the next day to try to guide me towards high value or low effort tasks.

> More specifically, I would start each day by taking the results of my prior night's triage agents, filter them manually to find the issues that an agent will almost certainly solve well, and then keep them going in the background (one at a time, not in parallel).

This is a short excerpt, this article is worth reading. Very grounded and balanced.

[datsci_est_2015]

Okay I think this somewhat answers my question. Is this individual a solo developer? “Triaging GitHub issues” sounds a bit like open source solo developer.

Guess I’m just desperate for an article about how organizations are actually speeding up development using agentic AI. Like very practical articles about how existing development processes have been adjusted to facilitate agentic AI.

I remain unconvinced that agentic AI scales beyond solo development, where the individual is liable for the output of the agents. More precisely, I can use agentic AI to write my code, but at the end of the day when I submit it to my org it’s my responsibility to understand it, and guarantee (according to my personal expertise) its security and reliability.

Conversely, I would fire (read: reprimand) someone so fast if I found out they submitted code that created a vulnerability that they would have reasonably caught if they weren’t being reckless with code submission speed, LLM or not.

AI will not revolutionize SWE until it revolutionizes our processes. It will definitely speed us up (I have definitely become faster), but faster != revolution.

[kaibee]

> Guess I’m just desperate for an article about how organizations are actually speeding up development using agentic AI. Like very practical articles about how existing development processes have been adjusted to facilitate agentic AI.

They probably aren't really. At least in orgs I worked at, writing the code wasn't usually the bottleneck. It was in retrospect, 'context' engineering, waiting for the decision to get made, making some change and finding it breaks some assumption that was being made elsewhere but wasn't in the ticket, waiting for other stakeholders to insert their piece of the context, waiting for $VENDOR to reply about why their service is/isn't doing X anymore, discovering that $VENDOR_A's stage environment (that your stage environment is testing against for the integration) does $Z when $VENDOR_B_C_D don't do that, etc.

The ecosystem as a whole has to shift for this to work.

[djhn]

The author of the blog made his name and fortune founding Hashicorp, makers of Vagrant and Terraform among other things. Having done all that in his twenties he retired as the CTO and reappeared after a short hiatus with a new open source terminal, Ghostty.

[datsci_est_2015]

I had a bit of an adjustment of my beliefs since writing these comments. My current take:

  - AI is revolutionizing how individuals work
  - It is not clear yet how AI can revolutionize how organizations work (even SWE)

[adammarples]

If you had that article, would you read it fully before firing off questions?

[lawgimenez]

Can't believe you don't know who the author is my man.