Asset & Permission Map
Permission Boundary Excerpt
tool: customer-note.write
scope: approved workspace only
owner: platform engineering When your AI Agent takes real action
Production requires deterministic engineering guards
Independent engineering reviews for teams preparing to give AI agents production access. Get a permission map, scenario tests, and documented release dependencies before deciding to launch.
DELIVERABLES
The 5 evidence artifacts behind every release decision
Every engagement produces five versioned engineering records owned by your team, integrating directly into your repository and CI/CD pipelines.
ILLUSTRATIVE EVIDENCE EXCERPTS
How review evidence is made actionable
Illustrative examples only. No customer data or system records.
Release Policy & Guardrails
Release Dependency Excerpt
human approval: required
rollback path: verified
scenario coverage: pending reviewBlast Radius & Risk Register
Risk Register Excerpt
R-03 external content boundary
control: typed allowlist
evidence: scenario replay required 01
Agent Inventory & Tool Boundary
Model versions, data sources, tool call interfaces, and strict read/write permission tiers mapped out end-to-end.
02
Scenario & Failure Pack
Domain-specific evaluation suites covering task success, edge-case corner failure modes, indirect prompt injection, and recovery behaviors.
03
Blast Radius & Risk Register
Quantified maximum damage ceiling if a tool misbehaves, sensitive data leakage boundaries, and tenant isolation verification.
04
Release Policy & Guardrails
Hard release thresholds, canary rollout steps, automated kill-switch criteria, and human-in-the-loop escalation rules.
05 Readiness
Launch Readiness Assessment
A formal, auditable readiness assessment that documents release dependencies, residual-risk acceptance, and named owners.
ENGAGEMENTS
Three ways to de-risk your agent release
1 Week
Launch Gate Review
Fast, independent pre-release verification for high-consequence agents approaching production. We deliver architectural review findings, release dependencies, and mitigation control recommendations before real users are exposed.
2 Weeks
Production Readiness Audit
End-to-end teardown of your agent architecture: tool blast radius, permission tiers, data boundaries, and failure containment with a prioritized engineering fix roadmap.
4-6 Weeks
Scenario & Eval Infrastructure
We build the domain-specific scenario library and automated regression pipeline needed to test prompt, model, and tool changes in CI/CD before they hit production.
ARCHITECTURAL RIGOR
Hard engineering controls over prompt-only tricks
Prompts drift and get hijacked. Consequential agents require deterministic infrastructure guards before reaching production.
← Scroll horizontally to compare →
| Dimension | Fragile Prompt-Only Hacks | BartsAI Production Standard |
|---|---|---|
| Tool Execution Safety |
✕ Fragile
Declaring rules only in system prompts (e.g., "Do not delete data") |
✓ Deterministic
Strict JSON schema verification, read/write token separation, least-privilege API scopes |
| Irreversible Actions |
✕ Fragile
Relying on the LLM to ask confirmation verbally before executing writes |
✓ Deterministic
Two-phase approval tokens, dry-run previews, deterministic transaction state machines |
| Blast Radius Control |
✕ Fragile
Shared database connection string across all agent tools |
✓ Deterministic
Per-tool scoped service accounts, tenant isolation, rate & volume circuit breakers |
| Regression & Rollback |
✕ Fragile
Relying on manual spot-checks when foundation models update |
✓ Deterministic
Automated scenario regression suites in CI/CD, instant canary rollback to deterministic code |
SOURCE-AVAILABLE ENGINEERING STARTERS
Drop deterministic guardrails straight into your CI/CD
Beyond checklists, we provide deterministic validation examples you can run locally and in CI; adapt and test the real executor before production use.
✓ Live v0.2.0
Python 3.10–3.12
Optional test dependencies
AI Agent Production Guardrails & Trajectory Eval
Includes step and cost circuit breakers, tool allowlists, recognized path-argument checks, and strict JSON Schema validation when dependencies are installed, plus negative tests and a CI template.
git clone ... && python3 run_tests.py --demo
⏳ In Development
TypeScript / Node.js
Zod & Vitest
Full-Stack Serverless Agent Production Guardrails
Tailored for Next.js, Vercel, and Node.js AI agent architectures. Enforces Zod schema gatekeeping, environment secret scrubbing, and AbortController execution breakers.
Scheduled for Cycle 1 release. Follow the repository for updates.
Spec ID: STARTER-02 Review 50-Item Standards →
APPROACH
How we work
- 01
Reproduce the failure first
Before any recommendation, we reproduce your failure and tool misuse cases in a controlled sandbox. No policy gets proposed without a failing test.
- 02
Measure, don't guess
We replace subjective quality checks with measurable evaluation and bounded risk scores. If we can't verify containment, we don't mark it ready.
- 03
Build with your team, not around them
Your engineers are in key sessions. Our job is to give them the rubric, tooling, and confidence to own release safety permanently.
- 04
Solidify critical infrastructure
Audit trails, regression suites, permission scopes, and fallback policies. The robust infrastructure that separates demo agents from production systems.
ABOUT
Engineer-led · Production-tested
Built for teams that actually ship
BartsAI was founded by a senior engineering leader from production-scale AI/fintech. We approach production assurance the way we wish vendors had done it for us: opinionated, technical, with skin in the game.
We help teams assess permission boundaries, data exposure, and failure recovery. Our reviews document tested controls, evidence gaps, and residual risks; they do not guarantee incident-free operation.
Based in Singapore. Working globally.
CONTACT
Tell us about your upcoming agent architecture
Share your release timeframe and a high-level concern. No source code, prompts, logs, credentials, or customer data are needed for the first conversation.
Direct Email: hello@bartsaiconsulting.com
Location: Singapore (Serving Global Engineering Teams)
Confidentiality: Mutual NDA available before sharing non-public technical materials
What happens after you contact us
- We discuss the use case, release timeframe, and whether a review fits your needs.
- We agree on scope, deliverables, fees, and confidentiality terms before any engagement.
- Before sharing non-public material, agree on an NDA and a secure transfer method; then prepare the agreed evidence and test access.
- Once prerequisites are ready, we confirm the start date and delivery schedule together.
Scoped Independent Review
Launch Gate Review Deliverables
- 1. Asset & Permission Map: Explicit mapping of read vs write credentials and network boundaries.
- 2. Domain Scenario Pack: 20-30 custom edge-case, injection, and timeout test cases.
- 3. Blast Radius Matrix: Quantified bounds on financial, operational, and data exposure.
- 4. Circuit Breaker Blueprint: Two-phase human sign-off tokens and automated rollback.
- 5. Release Dependencies & Architecture Review: Independent engineering assessment documenting unmitigated risks, release dependencies, and rollback controls.
Proposed: 5 Business Days Target: VP of Engineering / CTO
Phases: D1 Threat Model → D2-3 Scenario Testing → D4 Radius Verification → D5 Final Review
The five-business-day schedule is a proposed review window, starting on the agreed date after scope, materials, and test access are confirmed. Scope changes or missing prerequisites may change the schedule.
Scope: one agreed agent workflow and test environment. This is not a security certification, full implementation project, or ongoing incident-response service. Your team owns the release decision.