I Built a Go Control Plane That Stops AI Agents From Drowning in Context

#agents #ai #go #softwaredevelopment

Every AI coding agent has the same bad habit: dump the whole repo into the prompt and hope.

The result? Slow runs, burned tokens, and confident edits to the wrong files.

I got tired of it, so I built AI Workflow V3: a single Go binary that decides how much context an agent actually needs, before it writes a line of code.

The one rule: escalate capability, not context volume.

🧠 How it works

Give it a task, and it runs a deterministic pipeline:

Task
 → lane + risk classification   (Answer / Small / Full)
 → hard context budget
 → repo-aware retrieval         (index, BM25, structural, semantic)
 → evidence check               (sufficient / requires_exploration / abstain)
 → bounded context → agent
 → verification → compact handoff
 → verified memory only

Your agent gets a tight brief instead of a haystack:

ai-workflow setup
ai-workflow brief "refactor payment retry" --format prompt
# agent works...
ai-workflow verify --check "go test ./..." --strict
ai-workflow memory add --type verified-fix --keywords "payment retry" \
  --summary "retry uses jittered backoff" --file svc/retry.go

⚡ What makes it different


📦 One native binary	No Python env. Windows, Linux, macOS, WSL.
🔌 Built-in MCP server	Plug into Claude Code, Cursor, Codex, Windsurf.
🗂️ Multi-repo discovery	Finds nested Git roots and routes retrieval across them.
🚦 "Should I even edit yet?"	Evidence states stop agents from guessing when context is thin.
🔒 Hardened by design	No shell execution, bounded output, timeouts, constrained env.
🧾 Replayable runs	Hash-chained run journals show why every decision was made.
✅ Memory you can trust	Only verified fixes are saved. No junk in, no junk out.
🛡️ Supply-chain safe	SHA-256 verified installs + GitHub build-provenance attestations.

🔌 Connect your agent in one line

claude mcp add ai-workflow -- ai-workflow --root /path/to/project mcp

Your agent then calls brief, context, route, search, memory_search, verify, and more natively, with no shelling out.

🔁 Why a V3?

V2 was Python and proved the idea. V3 is a clean Go rewrite, and it doesn't get to call itself compatible just because features were reimplemented. Every V2 behavior counts as migrated only after a differential fixture proves the same input gives an equivalent result.

🚀 Try it in 10 seconds

curl -fsSL https://raw.githubusercontent.com/Taki7980/Ai-workflow-V3/main/install.sh | sh

Windows:

irm https://raw.githubusercontent.com/Taki7980/Ai-workflow-V3/main/install.ps1 | iex

⭐ Repo: https://github.com/Taki7980/Ai-workflow-V3

MIT licensed. Stars, issues, and brutal feedback welcome.

How do you keep your agents' context under control? Drop your approach below 👇

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