I haven't used it since it became paid, but back then Junie was slow and thoughtful, while Cursor was constantly re-writing files that worked fine, and Claude was somewhere in the middle
kiro from amazon does both tasks (in tasks.md) and specs.
Too many tools soon, choose what works for you
The author has done a pretty good job of reverse engineering Claude Code and explaining the architecture.
update: changed the link to a better repo
This is a better repo to learn about Claude code internals
https://github.com/ghuntley/claude-code-source-code-deobfusc...
Still work in progress, but I'm already using it to code itself. Feedback welcome.
i hate how LangChain has always tried to make things that are simple seem very complicated, and all the unnecessary new terminology and concepts they've pushed, but whatever sells LangSmith.
Next step is to try flood the SEO zone with your thing. It’s great if you can piggyback other key terms (deep *, agents) and.. I’m already bored writing this up it’s so [what’s the word for sheer resigned exhaustion at the capitalist corporate soul kill that is this type of work]
1. You need a good LLM for base knowledge.
2. You need a good system prompt to guide/focus the LLM (create an agent).
3. If you need some functionality that doesn't make any decisions, create a tool.
4. If the agent + tools flows get too wily, break it down into smaller domains by spawning sub agents with focused prompts and (less?) tools.
I think where this ultimately goes is a "coordinator" sort of model where the top-level agent primarily decides what needs to happen next and which agent is most equipped to handle that task. This could potentially happen in a recursive fashion (e.g. an agent for each product the company makes, that agent can dispatch to a "frontend" agent or a "backend" agent, etc).
That allows the agents that actually "do things" to maintain a limited context and set of tools, and the managing agents only have to maintain context on what their sub-agents can do.
Also, that's one way to misinterpret what was said. I acknowledge there are some well-designed pieces of software that were hacked quickly. LangChain is not one of them, it's a mess, and hacking another module quickly is likely going to extend that mess, which was the reason for my comment.
Main takeaways (which I'd love feedback on) are:
There are series of agents recently (claude code, manus, deep research) which execute tasks over longer time horizons particular well
At the core of it, it's just an LLM running in a loop calling tools... but when you try to do this naively (or at least, when I try to do it) the LLM struggles with doing long/complex tasks
So how do these other agents accomplish it?
These agents all do similar things, namely:
1. They use a planning tool
2. They use sub agents
3. They use a file system like thing to offload context
4. They have a detailed system prompt (prompting isn't dead!)
I don't think any of these things individually is novel... but I also think that they are not super common place to do when building agents. And the combination of them is (I think) an interesting insight!
Would love any feedback :)
Now that its increasingly clear that writing MCP servers isn't a winning strategy, people need a new way to jump on the band wagon as easily as possible.
Writing your own agent like geminin and claude code is the new hotness right now.
- low barrier to entry (tick)
- does something reasonably useful (tick)
- doesnt require any deep ai knowledge or skill (tick)
- easy to hype (tick)
Its like “cursor but for X” but easier to ship.
Were going to see a tonne of coding agents built this way, but my intuition is, and what Ive seen so far, is theyre not actually introducing anything novel.
Maybe having a quick start like this is good, because it drops the value of an unambitious direct claude code clone to zero.
I like it.
seabass•6mo ago
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crawshaw•6mo ago
It is relatively easy to get the agent to use it, most of the work for us is surfacing it in the UI.
TrainedMonkey•6mo ago
lmeyerov•6mo ago
most useful prompt stuff seems 'simple' to implement ultimately, so it's more impressive to me that such a simple idea of TODO goes so far!
(agent frameworks ARE hard in serious settings, don't get me wrong, just for other reasons. ex: getting the right mix & setup devilishly hard, as are infra layers below like multitenacy, multithreading, streaming, cancellation, etc.)
re: the TODO list, strong agree on criticality. it's flipped how we do louie.ai for stuff like speed running security log analysis competitions. super useful for preventing CoT from going off the rails after only a few turns.
a fun 'aha' for me there: nested todo's are great (A.2.i...), and easy for the LLM b/c they're linearized anyways
You can see how we replace claude code's for our own internal vibe coding usage, which helps with claude's constant compactions as a heavy user (= assuages issue of the ticking timer for a lobotomy): https://github.com/graphistry/louie-py/blob/main/ai/prompts/...