Building the trust layer for AI agents

AI agents fail in production. Logs lie. Retries hide root causes.
I build systems that measure, trace, and fix agent failures at the protocol layer.

Focus: AgentOps · Reliability · Observability · Tooling
Current sprint: CLI launch by May 31

73 percent of agent failures start at the interface layer: JSON parsing, tool calls, retries, and state drift.

I build systems that:

• Trace every tool call and response
• Surface failure points in real time
• Increase task success rate with measurable deltas

Problem: Teams debug agents manually across logs, prompts, and tools

Fix: CLI that traces execution across the full agent loop

Output:

• Per-step trace logs
• Tool call validation
• Failure classification
• Retry impact measurement

Target result:

• Debugging time: 2 hours → 15 minutes
• Task success rate: +30 to +80 percent

Detects pricing anomalies and extracts contract fields.

Result:

• Standardized outputs across varied documents
• Reduced manual review cycles

Tech: Python · NLP · FastAPI · Docker · CI/CD

View Repository

Chains tools with structured execution paths.

Result:

• Stable tool execution across workflows
• Reusable testbed for reliability experiments

Tech: FastAPI · LangChain · Tool execution

View Repository

Before: Manual publishing
After: 2-hour workflow → 10-minute pipeline

View Repository

Every system meets this:

• Runs on a clean machine
• Dockerized
• CI pipeline validates execution
• Measurable success metric included
• 5-minute install path

Each repo includes:

• /llms.txt for structured AI-readable context
• /pricing.md for limits and usage
• Machine-readable outputs

Goal: Make tools indexable by AI systems

Agent Systems

• LLM execution pipelines
• Tool orchestration
• RAG systems
• MCP integration

Backend

• Python · FastAPI · APIs
• Function calling systems

Infrastructure

• Docker · CI/CD · GCP · AWS
• Observability pipelines

• Built 15+ AI systems with measurable outputs
• Deployed production-ready pipelines with CI/CD
• Led GenAI prototyping team
• Worked with academic and industry mentors

• Reliability over features
• Constrained agents over autonomous agents
• Small teams over enterprise systems

Install the upcoming CLI.
Trace your agent failures.
Fix execution, not prompts.

Or continue debugging blindly.

• GitHub: https://github.com/Sasisundar2211
• Email: sasisundhar2211@gmail.com