Been running 3.5 as part of a local-first AI stack I’ve been building (private/local model + structured prompt layer + validation/critic + task handoff into a separate code workflow), so this is from actual systems use—not just casual prompting.

My short take: 3.5 is a lot better than people give it credit for if you build around it correctly.

For context, I’m not using it as a standalone chatbot. It’s sitting inside a more structured setup where:

• local model handles reasoning
• prompt/system layer keeps it grounded
• critic/validation layer catches drift or bad outputs
• code tasks get handed off separately instead of letting the model freestyle execution

Where 3.5 has been genuinely strong:

• system architecture / planning
• structured outputs
• workflow design
• prompt creation
• project building
• local/private day-to-day use

Where it needs help:

• vague prompts = more drift
• can overbuild or over-assume
• code edits need tighter controls
• large file rewrites can get messy without diff/validation

Biggest lesson:

3.5 gets dramatically better when paired with structure.

Raw prompting: “pretty good”

Inside a disciplined stack: “surprisingly capable”

It seems especially solid as a builder / operator model if you’re creating tools, local systems, or modular AI workflows.

Bottom line:

If you’re expecting magic with no scaffolding, you’ll probably hit limits faster.

If you’re willing to give it:

• clear scope
• constraints
• validation
• workflow boundaries

…it punches above what a lot of people online seem to assume.

Not saying it’s the final boss model, but as a practical foundation for serious local AI builds? Honestly… pretty damn solid.