We Built Google ADK Before They Announced It – Here's What We Learned

Last week, Google published "Architecting efficient context-aware multi-agent framework for production" – their approach to managing context in multi-agent AI systems.

We've been running this in production for 6 months.

Here's what we learned (and what we do differently).

The Problem: Context Explosion 📈

If you're building with AI agents, you've hit this wall:

Your agent starts a task. Clean context window. 10 messages later, it's dragging around 50,000 tokens of chat history, tool outputs, and irrelevant state.

Now it:

Costs $5/query instead of $0.50
Takes 30 seconds instead of 3
Forgets the original instruction
Gets confused by its own past mistakes

Google's diagnosis (from the ADK article) breaks this down into three problems:

1. Cost & Latency Spirals

Token costs and response times grow exponentially. "Append everything" strategies make agents prohibitively slow.

2. Signal Degradation

Context flooded with noise distracts models. They fixate on irrelevant history instead of the task at hand.

3. Physical Limits

Real workflows—full documentation, code files, test results—overflow even million-token windows.

Their insight: You can't solve this by making windows bigger. You need architecture.

Our Solution: Dynamic Rules + Enforcement

We built Supernal Coding around the same core insight: context is a systems problem, not a prompt problem.

But we added something Google's framework doesn't have: enforcement.

1. Real-Time Context Awareness

The Pattern: Monitor daemon watches repository state, regenerates .cursor/rules/*.mdc every 30-60 seconds.

What AI agents see:

## Repository State

- Untracked files: 8 (threshold: 5)
- Modified files: 3
- WIP-tracked files: 5
- Active features: 3 (auth, dashboard, api)

## ⚠️ Policy Violations

🚨 **CRITICAL**: 8 untracked files (threshold: 5)

Files needing attention:
  - experiment1.ts
  - experiment2.ts
  - temp-notes.md
  ... and 5 more

**Fix options**:
1. WIP-track: sc workflow wip register <file> --feature=<name>
2. Commit: git add <files> && git commit
3. Gitignore: echo "temp-*" >> .gitignore

Impact: Agents know repository state right now, not from stale documentation.

2. Multi-Agent File Ownership

The Problem: Two AI agents, both modifying login.ts. Neither knows about the other. Merge conflict. Lost work. Frustration.

Our Solution: WIP Registry with user tracking.

# Agent A (Alice) claims file
$ sc workflow wip register src/auth/login.ts --feature=auth --userid=alice

# Agent B (Bob) tries to claim same file
$ sc workflow wip register src/auth/login.ts --feature=security --userid=bob

⚠️  CONFLICT: File already registered by @alice

Contact @alice before working on this file.
Feature: auth
Registered: 2 hours ago

Impact: File ownership is explicit. No more "disappearing files" when agents work in parallel.

3. Pre-Commit Enforcement

The Critical Difference: Google ADK warns. We block.

$ git commit -m "feat: add authentication"

❌ WIP registry violation: 8 untracked files (threshold: 5)

Untracked files:
  - experiment1.ts
  - experiment2.ts
  - temp-notes.md
  ... and 5 more

Fix options:
  1. WIP-track: sc workflow wip register <file> --feature=<name>
  2. Commit ready: git add <files> && git commit
  3. Gitignore: echo "temp-*" >> .gitignore

Bypass (emergency): SC_SKIP_WIP_CHECK=true git commit

Why This Matters: Warnings get ignored. Blocks force action.

We ran with "warning mode" for 3 months. Developers ignored it. Orphaned files piled up.

We added blocking on 2025-12-16. Orphaned files dropped to near-zero in 48 hours.

Production systems need hard stops, not suggestions.

What Google Does Better (And We're Closing These Gaps)

Let's be honest: Google's ADK has features we don't (yet).

1. Artifact Handle Pattern

Google's Approach: Large files (5MB CSV, PDFs) stored externally. AI sees lightweight references. Loads on-demand.

Our Status: ⚠️ Implementing Q1 2026

Why We're Prioritizing This: Compliance teams deal with massive test reports. Keeping them out of context saves thousands of tokens.

2. Semantic Memory

Google's Approach: Vector search for past decisions. "What did we decide about authentication?" → Returns relevant ADRs automatically.

Our Status: ⚠️ Roadmap Q2 2026

Why Later: We have 88 SOPs, 148 requirements, and 23 architecture guides. Grep works fine for now. Vector search is a nice-to-have, not urgent.

3. Explicit Context Caching

Google's Approach: Separate stable prefixes (system prompts) from dynamic suffixes (recent messages).

Our Status: ⚠️ Low priority

Why: Cursor/Claude already optimize this behind the scenes. We haven't seen evidence it's a bottleneck.

What We Do Better: Production Features

1. Enforcement (Blocks Bad Commits)

Google warns. We block.

Result: Zero orphaned files, no technical debt accumulation.

2. Compliance Evidence

Scenario: SOC2 auditor asks for test evidence for REQ-042 (user authentication).

Without Supernal Coding:

Search git history
Find test files manually
Re-run tests (hope they pass)
Screenshot results
Write summary
Submit

Time: 4-8 hours per requirement × 148 requirements = 2-4 weeks

With Supernal Coding:

$ sc trace show REQ-042 --format=pdf

✅ Generated: req-042-audit-report.pdf

Time: 30 seconds

Impact: Compliance automation pays for itself immediately.

3. Multi-User Safety

Google's Approach: Scope what sub-agents see in their prompts.

Our Approach: Scope what agents can modify (file-level ownership).

Why It Matters: Prompt scoping prevents information leaks. File scoping prevents actual conflicts.

Both are necessary. We do both.

Lessons from 6 Months in Production

Lesson 1: Awareness ≠ Enforcement

Dynamic rules are great. But if they don't block bad actions, developers will ignore them.

We learned this the hard way. Had warnings for months. Added blocking. Problem solved overnight.

Lesson 2: Multi-Agent = File Ownership Problem

Context scoping is necessary but not sufficient.

Two agents with perfect prompt isolation can still edit the same file and create merge conflicts.

You must scope files, not just prompts.

Lesson 3: Compliance Requires Evidence

Context management without audit trails is just expensive prompts.

SOC2 auditors don't care how sophisticated your context compilation is. They want evidence.

We added automatic evidence logging. Next audit took 1/10th the time.

Try It Free

What's Included:

✅ 88 SOPs (comprehensive workflow guides)
✅ 51 Cursor Rules (AI-specific patterns)
✅ Full CLI tools (sc command suite)
✅ Pre-commit enforcement
✅ WIP registry with multi-user support

Paid Upgrades:

VSCode Extension ($10/mo): Visual context panel
Pro ($20/mo): Monitor daemon + dashboard + evidence logging
Team ($50/mo): Unlimited users, shared config

Download: https://supernal.ai/download

The Bottom Line

Google ADK is a research framework. Supernal Coding is a production platform.

Choose ADK if:

Single-developer research
No compliance requirements
Rapid prototyping

Choose Supernal Coding if:

Multi-developer teams
Regulated industries
Audit trail requirements
Production enforcement needed

We're implementing ADK's best features (artifacts, semantic memory) while doubling down on what production teams actually need: enforcement, compliance, and team coordination.

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Questions? DM us or reply below 👇

We're eager to hear from teams building multi-agent systems. What context problems are you hitting?