Built by a Middleware Engineer. Designed for Every Role with Constraints.
I spent 10+ years getting paged at 3am to fix production issues. When AI tools became popular, I watched them give confident advice that was impossible to follow.
That's when I realized: This isn't just an IT problem. It's universal.
The Origin Story
I'm Grimy, a middleware engineer with 10+ years debugging production systems under pressure. Database locks at 3am. Cascade failures taking down entire regions. Making irreversible decisions with incomplete information and a 5-minute SLA breathing down my neck.
When ChatGPT and other AI tools exploded in popularity, I saw DevOps teams start using them during incidents. At first, I was excited. Finally, some help!
Then I watched the disasters unfold.
AI would confidently suggest "rolling back the deployment" without asking if backups existed. It recommended "restarting the database" without considering the blast radius. It told junior engineers to "check the logs" when they didn't have SSH access.
The advice was often technically correct. But it was operationally impossible.
I started building workarounds - structured prompts that front-loaded constraints. "I'm a DevOps engineer with read-only database access, 99.9% SLA requirement, 5-minute resolution window..." It worked. AI finally gave advice I could actually follow.
The Universal Pattern
I shared my workaround on Twitter. The responses caught me off guard.
A paralegal messaged: "This is exactly my problem. ChatGPT tells me to 'negotiate directly with opposing counsel' - but I can't, I'm not licensed. I need the AI to know I can only draft documents for attorney review."
A hospital administrator wrote: "AI suggests changes to clinical protocols that require Board approval and 6 months of review. I need it to understand my decision authority stops at operational logistics."
A customer success manager said: "It tells me to offer refunds or discounts I'm not authorized to give. I need context that knows my escalation limits."
Every role has constraints. AI doesn't know about them.
Access level. Budget authority. Timeline requirements. Compliance restrictions. Reversibility needs. Blast radius concerns.
The problem isn't AI being wrong. It's AI not knowing what you CAN'T do.
That's when Lens Coding stopped being a "DevOps tool" and became a universal constraint-awareness framework.
How Lens Coding Works
Lens Coding is a structured framework for teaching AI about your constraints BEFORE it gives advice. It's built on four core pillars that apply across every industry:
1. Constraint-First Reasoning
Establish what you CAN'T do before exploring what you CAN do.
IT Operations
"I can't restart the database (requires Director approval). I CAN restart application pods, adjust connection pools, or enable read replicas."
Legal
"I can't make settlement offers (not licensed). I CAN draft motions, conduct research, prepare discovery documents for attorney review."
Healthcare
"I can't override clinical decisions (not a physician). I CAN reschedule resources, coordinate departments, escalate to medical staff."
2. Explicit Information Gaps
Track what you KNOW, what you ASSUME, and what's UNKNOWN.
IT Operations
Known: DB connection pool at 98%
Assumed: Recent deploy caused it
Unknown: Impact on user sessions
Legal
Known: Contract expires in 30 days
Assumed: Client wants renewal
Unknown: Budget for new terms
Healthcare
Known: Bed shortage in ICU
Assumed: Elective surgeries are flexible
Unknown: Tomorrow's discharge count
3. Reversibility Analysis
Classify every action as Reversible, Partially Reversible, or Irreversible.
IT Operations
Reversible: Restart pod
Partial: Clear cache
Irreversible: Drop table
Legal
Reversible: Draft response
Partial: File motion
Irreversible: Miss statute of limitations
Healthcare
Reversible: Reschedule elective
Partial: Discharge patient early
Irreversible: Cancel urgent surgery
4. Blast Radius Mapping
Surface worst-case scenarios before execution.
IT Operations
Action: Scale DB connections
If wrong: DB crashes, all services down, P2 → P0 escalation
Legal
Action: File for extension
If denied: Miss deadline, case dismissed, malpractice exposure
Healthcare
Action: Transfer ICU patient
If deteriorates: Emergency airlift, family lawsuit, regulatory review
The Vision: Context-Aware AI for Every Professional
Lens Coding generates role-specific reality lenses that work with any AI - ChatGPT, Claude, Gemini, whatever you use. You paste the reality lens, then ask your question. The AI finally understands your constraints and gives advice you can actually follow.
Live Now
✓ AVAILABLEComing 2026
Q2-Q4 2026Legal
Paralegals, Contract Admins, Compliance Officers
Healthcare
Nurses, PAs, Medical Admins, Coordinators
Customer Success
CSMs, Account Managers, Support Engineers
Finance
Analysts, Accountants, Risk Managers
Education
Teachers, Admins, Academic Advisors
Future Roadmap
2027+Manufacturing
Production, QA, Supply Chain
Government
Public Admin, Compliance, Policy
Real Estate
Agents, Property Mgmt, Appraisers
HR & Recruiting
Recruiters, HR Ops, Talent Acquisition
Why Start with IT Operations?
I'm being honest here: I'm starting with IT because it's what I know deeply. I've lived the 3am pages. I understand the constraints viscerally. I can build reality lenses that actually work because I've been in the role.
That same principle applies to every industry I expand into:
- Deep domain expertise matters. I'm partnering with practicing paralegals for Legal, working nurses for Healthcare, active CSMs for Customer Success.
- Constraints are role-specific. A junior associate has different limitations than a partner. A staff nurse vs. a charge nurse. A support engineer vs. a CSM.
- Quality beats speed. I'd rather launch one industry correctly than five industries poorly. Each vertical gets built with practitioners who live the constraints daily.
IT is live now because I can guarantee the quality. The other industries will launch when they meet that same bar.
Try It Yourself
See how constraint-first reasoning changes AI advice from "technically correct" to "actually actionable."