I think the value right now is to focus less on external orchestration if at all. trust the (current best) model to do it better than anything you bolt on to the harness. focus your energy on providing clearer specs. I think the optimal spec is a disambiguated (through liberal use of the AskUserQuestion tool) 1 intent, 2, input/output contracts 3 constraints and 4 preconditions. focus on that and get out of the models way. I think of it like this, imagine a person who was not as smart as you was trying to tell you how to do a task. would you want more verbosity and step by step instructions or would you want them to just cut to the chase (ie, what are you trying to do, what are the obstacles, I'll let you know if I have questions).

also let the model verify itself. don't give it an objective that is vague, give it clear exit criterias for goals and let it loop until it gets there so much of the orchestration scaffolding seems like massive technical debt

oddly, I do the opposite of a lot of conventional advice when it comes to models. I use no memory, I think there is something similar to context rot when everything is stored. I like creating markdown files as memory that the model can grep if needed. I also havent found a real use for hooks yet, I have tried but they always seem to get in the way. skills on the other hand are very undervalued. they are so much more powerful than many realize. I used to think agents were where the power was. I think its actually skills. agents are really for context preservation. skills are what increase capabilities

I'm not even talking about quantity of items in memory, I mean dilution of intent. I really love a model with a clean slate and only the items it needs. I fear the memory guides the model in areas that might not be what I want with the current prompt

progressive disclosure is a big one. you can make context available but it is only loaded when needed. like lazy loading for prompt engineering. skills are to be used to instruct the model how to do something specific that is not in its training data. like how to access my proprietary system, how to interface with a custom program. you can embed templates in skills, you can embed code that executes in skills and only the output is loaded into context. skills expand capabilities, agents constrain context

(constraining context is a very good thing btw, don't mean to infer that agents are somehow inferior to skills)

It feels like everyone and their grandma is building an agent orchestrator at the moment, but I'm not hearing a lot of success stories. The fact that Anthropic and OpenAI haven't laid off all their software engineers already is probably a sign that orchestration breaks down somewhere. I suspect it's just a more elaborate way of burning tokens. I'm still interested in experimenting though.