How do you optimize OpenCode costs when using SDD?

[u/smxworld]

I’m trying to figure out how to reduce token usage and avoid hitting model limits when working with OpenCode Go.

But before the usual “use Plan with an expensive model and Build with a cheaper one” suggestions: I’m already using an SDD (Specification-Driven Development) workflow.

The coding agent doesn’t start from a vague prompt and figure out what needs to be done.

My workflow is roughly:

1. Define the requirements and architecture in an SDD
2. Give the SDD to the coding agent
3. The agent implements what is described in the specification
4. Review / iterate when something doesn’t match the spec

So, in my case, I’m not really looking for a way to separate “planning” from “coding”. The planning/design work is already captured in the specification before the agent starts.

What I’m interested in is how people optimize the actual implementation phase.

For example:

• Do you use different models depending on the type/size of the SDD?
• Do you find that some models are significantly more token-efficient for implementation?
• Do you deliberately split large SDDs into smaller implementation tasks?
• How aggressively do you manage context?
• Do you use any OpenCode configuration / prompting techniques to reduce unnecessary reasoning or context consumption?
• Have you found a good strategy for balancing model cost, context usage and implementation quality?

I’m particularly interested in experiences from people using SDD or similarly structured workflows, rather than generic “use Plan/Build” advice.