100% Agents need reliable state management, conditional logic, and structured execution paths. Prompt engineering is a surface layer solution to a deeper problem
Agents need control flow, not more prompts
321–330 of 348 posts
Re: Agents need control flow, not more prompts
#322Earlier quoted context omitted.
I used to assume they pushed people into the prompt-only workflows because you’re paying them for the tokens, and not paying them for the scaffolding you built. However, I think that they’re really worried about is that a person needs to design and implement that stuff… It throws a wet blanket on their insistence that this will replace entire people in entire workflows or even projects, and I just don’t buy it. I do…
> However, I think that they’re really worried about is that a person needs to design and implement that stuff… It throws a wet blanket on their insistence that this will replace entire people in entire workflows or even projects You can have the AI design the custom harness in advance. It's not especially hard work! In fact, the AI could even come up with the workflow itself; it's a different and much simpler proble…
That's what my system does. It uses a workflow if one already exists, if not, it just creates one on the fly from the primitives.
https://github.com/notque/vexjoy-agent
I would prefer that be deterministic though. This thread has me considering what if anything I can do to make it forced. Like, I could do it with hooks, but that's not elegant at all.
Re: Agents need control flow, not more prompts
#3231000% agree. I am increasingly hesitant to believe Anthropic's continual war drum of "build for the capabilities of future models, they'll get better". We've got a QA agent that needs to run through, say, 200 markdown files of requirements in a browser session. Its a cool system that has really helped improve our team's efficiency. For the longest time we tried everything to get a prompt like the following working: "…
Secret: "compile" that orchestration prompt. Determinism is solved by turning prompts into code that can in turn run agents or run code or both. Everyone misses this pattern with skills: you can just drop code alongside a SKILL.md to guarantee certain behaviors, but for some reason everyone's addicted to writing prompts. You don't even need to build a CLI. A simple skill.py with tasks does it. You can even have helpe…
Yeah, that's how I do skills. If I can make a script, I do. Everything that can be deterministic should be. https://github.com/notque/vexjoy-agent
Re: Agents need control flow, not more prompts
#324[dead]
Re: Agents need control flow, not more prompts
#3251000% agree. I am increasingly hesitant to believe Anthropic's continual war drum of "build for the capabilities of future models, they'll get better". We've got a QA agent that needs to run through, say, 200 markdown files of requirements in a browser session. Its a cool system that has really helped improve our team's efficiency. For the longest time we tried everything to get a prompt like the following working: "…
You could have a skill that is the combination of a minimal markdown file and a set of orchestration scripts that do the deterministic work. The agent does not have to “run everything”, it just needs to know how to launch the right script.
For sure, this is the pattern I use.
And I wish I could make even more deterministic. Maybe I can, but it can also be a bit challenging to sort.
Re: Agents need control flow, not more prompts
#326Earlier quoted context omitted.
So you have the model write the if statements and put itself out of a job.
Alternatively, and sometimes more cost-efficient: you can find a developer who can write bespoke if statements. There are dozens of us!
Additionally, developers tend to become less expensive as venture capitalists turn off the spigot, while access to giant frontier models becomes way more expensive. Beyond that, a developer might go out and have a beer with you after work, which appeals to the sickos that have the gall to prioritize humanity over fanatical efficiency for corporate gains.
Re: Agents need control flow, not more prompts
#327Earlier quoted context omitted.
Secret: "compile" that orchestration prompt. Determinism is solved by turning prompts into code that can in turn run agents or run code or both. Everyone misses this pattern with skills: you can just drop code alongside a SKILL.md to guarantee certain behaviors, but for some reason everyone's addicted to writing prompts. You don't even need to build a CLI. A simple skill.py with tasks does it. You can even have helpe…
Could you elaborate what does "compiling orchestration prompt" mean?
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Re: Agents need control flow, not more prompts
#328I have some notes for a blog along the same lines, called "Determinism vs Agents". I had the same experience with MANDATORY.
Agents are also very slow compared to code. By the time it takes for the agent to ingest the system prompt + your prompt then to send a tool call to search for files in your repo, then another call to find a few patterns in those files, 30 seconds or more have passed. A non-agentic harness like Aider does that step a lot faster. Then it always does checkin of its changes. It doesn't have the flexibility to also run specific commands like code coverage checks from example. Something in between Claude Code and Aider would be useful.
Re: Agents need control flow, not more prompts
#329Correct, that we we should need something like DAG , kanban flow for control agent , there are deterministic combine with undeterministic
the control flow need to be bind with undeterministic agent to keep thing strict but need to flexible enough
Re: Agents need control flow, not more prompts
#330Earlier quoted context omitted.
I used to assume they pushed people into the prompt-only workflows because you’re paying them for the tokens, and not paying them for the scaffolding you built. However, I think that they’re really worried about is that a person needs to design and implement that stuff… It throws a wet blanket on their insistence that this will replace entire people in entire workflows or even projects, and I just don’t buy it. I do…
> However, I think that they’re really worried about is that a person needs to design and implement that stuff… It throws a wet blanket on their insistence that this will replace entire people in entire workflows or even projects You can have the AI design the custom harness in advance. It's not especially hard work! In fact, the AI could even come up with the workflow itself; it's a different and much simpler proble…
yeah , that is what I am do in with the DAG-aware TUI hypervisor agents https://getspur.dev