Listen friend I’m also in the camp of LLMs are just math and data and don’t actually “have an idea” about anything but that doesn’t make them any less accurate/effective at generating tokens
I’m not sure why this prompt is different than any other in that regard
Yeah i have a similar setup at the harness level - a “devlog” at the end of every session about the experience developing, what could have been better, what was confusing
And also files issues for blockers
I’ve absolutely caught things and made improvements just from skimming them occasionally - they are particularly useful when you get a PR that makes you scratch your head
But I’m definitely not taking full advantage of all the feedback coming in yet
I have to imagine parsing signal from noise there is a massive challenge when it’s other agents that are using your MCP and not just your own
i have a vague memory of hunter s thompson talking about sitting down and typing out the great gatsby to see how it would feel to write a great american novel
Yes I had a fun experience where it kept on timing out on a seemingly mundane task and it turned out I had written the ask in a way that was impossible to test
so i think the thing that everyone building these git alternatives is missing is a multi-repo story - unless the expectation is that everyone is going to start operating out of monorepos
i've settled on all of this context attached to issues in a project management system and referenced from commits
it works just fine - its not like your agent cannot read your issue tracker
don't let the title fool you - the first half of the book is just elixir
over the past 8 years this is the book i've used to ramp back up on elixir and it works like a charm every time - i've never finished it
for me, a mark of a good programming book in this tutorial-project style is that I have started it half a dozen times and never finished it because at some point before the end I've been equipped w/ the tools to go off and do my own thing
yeah this is one of the few AI-related products that I have seen that make sense to me
but i also wonder to what extent this needs to be its own thing or if this is just something that it looks like we need but really people just need to shovel more stuff into their data warehouse / data lake that you never had reason to before, because now that's all fodder for agentic search
sounds very familiar to what I ended up doing on my internal system - especially anything to do with search - much better to just sync everything to a DB and give the agent access to the DB
it's straightforward to spin up a custom MCP wrapper around any API with whatever access controls you want
the only time i reach for official MCP is when they offer features that are not available via API - and this annoys me to no end (looking at you Figma, Hex)
Yeah I’ve had a lot of success with agentic search against a database.
The way I think of it, the main characteristic of agentic search is just that the agent can execute many types of adhoc queries
It’s not about a file system
As I understood it early RAG systems were all about performing that search for the agent - that’s what makes that approach “non agentic”
But when I have a database that has both embeddings and full text and you can query against both of those things and I let the agent execute whatever types of queries it wants - that’s “agentic search” in my book
"Assign agents the biggest piece justifiable. I can summarize a product outcome or a feature in two lines. That’s what goes on the ticket. Let the agents figure out subtasks when the work is ready for review, not before. Once you break an initiative into technical issues upfront, the outcome gets lost and the focus shifts to minutiae."
This is not about the ticket being well defined, this is about the agent having the larger context of what you are trying to do
I've had the same thought recently and this definitely is a thing that you can do - but there are also cases where you get dramatically better results if you put some more effort into your setup.
e.g. spend time creating a skill about how to query production logs
I’m not sure why this prompt is different than any other in that regard