Proposal: make architecture governance an opt-in / pluggable layer for DeepSeek-TUI

[Jianfengwu2024]

Motivation

In long-running coding sessions, especially when multiple edits accumulate across files, there is a real risk of architectural drift:

• a new change lands in the wrong attachment point
• a reusable abstraction is reimplemented instead of reused
• local fixes gradually degrade the topology of the codebase
• architecture intent is lost across long agent/tool interactions

My original TriadMind PR was trying to address this by adding:

• topology extraction
• protocol / structure verification
• runtime mismatch diagnostics
• abstraction memory for reuse-first guidance
• post-edit drift detection

The concern raised in review is fair: landing all of this as an always-on default layer is too large and too opinionated.

So I’d like to reframe the proposal.

Reframed Proposal

Instead of embedding one always-on methodology into the default agent loop, introduce a pluggable governance interface with these properties:

• fully opt-in
• disabled by default
• measurable performance budget
• methodology-neutral host boundary
• capable of supporting different governance strategies, not only TriadMind

In this framing, TriadMind would be one possible governance provider, not a hard-coded worldview.

Proposed Integration Shape

A possible shape could be:

1. Governance hook interface

   • DeepSeek-TUI exposes lifecycle hook points such as:
     • before edit planning
     • after file edit
     • before apply/commit
     • on explicit “analyze drift” request

2. Optional provider registration

   • governance providers can be enabled through config
   • for example:
     • disabled
     • manual-only
     • post-edit sampling
     • strict mode

3. Bounded inputs / outputs

   • provider receives a limited project snapshot / changed-files set
   • provider returns structured guidance, for example:
     • warnings
     • reusable abstraction matches
     • suggested attachment points
     • optional protocol seeds

4. No default lock-in

   • the host should not assume one topology model
   • the host only understands a generic governance result shape

Why this may fit DeepSeek-TUI

DeepSeek-TUI already has strong infrastructure around:

• tool-driven coding sessions
• long-context workflows
• session management
• edit/apply loops
• LSP-adjacent development support

An optional governance layer could complement this by helping when the user explicitly wants stronger architectural guardrails.

I think the most interesting use case is post-edit drift detection, sitting alongside existing coding/tool flows:

• after an edit, check whether the change appears to attach to the intended architectural mount point
• surface reusable abstractions before new ones are introduced
• warn when a change increases topology fragmentation

Concerns Raised in Review

The PR review highlighted three important concerns, which I agree with:

1. Opt-in / pluggable shape

This should not be baked into the default agent loop.

2. Performance cost

Parser + verification + abstraction-memory lookup on every edit needs real measurement.
A governance layer needs:

• explicit sampling strategy
• caching
• changed-file scoping
• measured overhead

3. Methodology lock-in

DeepSeek-TUI should not force future users into one architectural worldview.
The host boundary should stay generic.

A More Incremental Path

Instead of reviving the original large PR as-is, a safer staged path might be:

Phase 1: governance host boundary

• define a minimal provider interface
• add config for opt-in/manual-only usage
• no default provider enabled

Phase 2: lightweight post-edit hook

• only changed-file scope
• emit advisory diagnostics only
• no blocking behavior

Phase 3: provider experiments

• TriadMind as one provider
• potentially other governance styles later
• compare usefulness and overhead

Questions for the Community

I’d love feedback on these points:

1. Would an opt-in architecture governance layer be useful in DeepSeek-TUI?
2. Should governance run only manually, or also as a post-edit advisory hook?
3. What would be an acceptable per-edit overhead budget?
4. What should the provider interface return to remain methodology-neutral?
5. Should this live as:
   • an internal plugin system
   • an external tool/provider bridge
   • or a command-triggered analysis layer only?

My Current Position

I still think the original problem is real:
long coding sessions do drift architecturally.

But I agree the right next step is not “merge one large methodology-driven governance stack by default”.
The better next step is to discuss whether DeepSeek-TUI should support a generic, optional governance extension point, and only then experiment with providers like TriadMind.

Happy to turn this into a smaller RFC or prototype if there is interest.

[Jianfengwu2024]

It’s easy to view the Vertex Triad Method ($T = (V, L, R)$) as just another opinionated pattern like MVC or DDD. However, it's actually designed as a minimal physical conservation law for executing software:

• Right Branch ($R$): Static Constraints (Schemas, Types, State).
• Left Branch ($L$): Dynamic Execution (Actions, Mutations).
• Vertex ($V$): The boundary ensuring $L$ never expands without proportionally defining $R$.

It doesn't dictate how users write code. It simply intercepts drift at a topological level, guaranteeing mathematically that agent edits don't break the codebase's structural integrity.

A Pragmatic, Pluggable Path Forward:
Instead of a hardcoded engine, I propose we build a Pluggable Architecture Drift Detection Engine through a 3-step decoupled integration:

1. Lightweight Hooks (The Interface): Introduce standard lifecycle hooks in the core loop (e.g., on_agent_edit_staged, on_commit_ready) with near-zero overhead.
2. Opt-in Middleware (The Implementation): TriadMind (or any other governance engine) runs as an external service activated via a flag (e.g., --enable-drift-detection), communicating via IPC/LSP.
3. Asynchronous Verification (Solving Perf Cost): To avoid blocking every keystroke, verification calculates the "Blast Radius" asynchronously. It only pauses the agent and requests human review if a topological rupture is detected.

I’d love to hear the community’s thoughts: What would a standardized Governance Hook API look like for deepseek-tui? Would this decoupled approach align better with the project's roadmap?