I’ve been experimenting pretty heavily with AI agents and workflows over the past few months, and I feel like we’re at a weird but exciting stage right now. Not in the “AI will replace everything tomorrow” sense more like we finally have enough pieces to build genuinely useful systems if you’re willing to stitch things together. For example, instead of using a single tool like ChatGPT or Claude in isolation, I’ve been building small pipelines: One agent plans (breaks down tasks) Another writes or codes (Copilot / Codex-style) Another reviews / refactors And sometimes a final pass that explains or documents what just happened It’s kind of like recreating a mini dev team, except each “person” is a different model with a different strength. What’s interesting is how different models feel in these workflows: Claude (especially Sonnet/Opus) is great at reasoning and structuring things ChatGPT is fast and versatile for iteration Copilot is still the smoothest for inline coding Codex-style agents feel more “task-driven” than conversational But the real unlock for me wasn’t switching models it was thinking in terms of workflows instead of prompts. Like: Instead of asking “write me X” You build: plan then draft then critique then improve then finalize That shift alone made outputs way more consistent. I’ve also been playing with lightweight orchestration setups. Even small things like chaining outputs manually or using simple scripts makes a big difference. There are also some newer tools popping up trying to make this easier. I came across something called Traycer recently that’s trying to map workflows visually. It really helped. Curious how others here are approaching this: Are you using single tools or building multi-agent workflows? Any setups that actually stuck for you beyond experiments? submitted by /u/Classic-Ninja-1
Originally posted by u/Classic-Ninja-1 on r/ArtificialInteligence
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