31–40 of 62 posts
How is the invalidation handled in Warp? Is it actually self-improving, or just better retrieval?
My way to do the self improving agents is a CLAUDE.md instructed to write my every decision to the decision log with the relevant context. Agent is using it to challenge me, to make things better and remind me why I did something. It also helps with the invalidation. How is the invalidation handled in Warp? Is it actually self-improving, or just better retrieval?
> What if it turns out the real AGI was the SKILL.md files we made along the way?
> In our series, we highlight how startups are transforming their industries with AI.
I'm sorry, but I don't see Warp transforming shit.
> Agents need to handle recurring tasks reliably and effectively This core problem remains unsolved. The solution presented in the article with Human In The Loop and some skill-magic such as "Write principles, not rules etc." is unsatisfactory because it offers no guarantees whatsoever. I find it difficult to harness agents into deterministic workflows which need to produce reliable outcomes.
You want workflows where the human gates are properly placed, not a "software factory" that you never place eyes on.
Earlier quoted context omitted.
The fact that it’s called “the quick pitch” screams Claude-written pithyness pulled from some context that doesn’t match the article’s style (like investment pitch decks).
The whole article screams Claude-written.
wired: this company could have been a prompt
My way to do the self improving agents is a CLAUDE.md instructed to write my every decision to the decision log with the relevant context. Agent is using it to challenge me, to make things better and remind me why I did something. It also helps with the invalidation. How is the invalidation handled in Warp? Is it actually self-improving, or just better retrieval?
How to you handle the problem of the decision log becoming so large that it cannot fit inside the context?
Btw it’s a fair challenge, I will probably hit it one day so something like a “compact” skill for decision log would be useful.
> Agents need to handle recurring tasks reliably and effectively This core problem remains unsolved. The solution presented in the article with Human In The Loop and some skill-magic such as "Write principles, not rules etc." is unsatisfactory because it offers no guarantees whatsoever. I find it difficult to harness agents into deterministic workflows which need to produce reliable outcomes.
Genuinely not trying to be pedantic but deterministic workflows are not what agents do. Indeed they're not capable of them. You want workflows where the human gates are properly placed, not a "software factory" that you never place eyes on.
They do get to it later on - casually mentioning it opens a PR for changes that a human accepts in the middle of a paragraph somewhere. Even there though, the focus isn't on risk mitigation (eg: against embedded prompt injection) but rather just "check if this is a good idea or not".
It seems to me that, in engineering terms, identifying self-modifying agent loops and managing the risk of them is going to be one of the key aspects that will emerge in best practises for how these systems are eventually designed.
There is a thriving and vibrant terminal ecosystem out there, with Ghostty, Kitty, Herdr, Tmux, and others leading the way with all kinds innovations and features. I can't imagine how a closed SaaS / freemium, telemetry sending, login requiring terminal like Warp competes in this environment. I know they've got all these enterprise features like runbooks, shared workflows, and some compliance do-dads, but I can't see…