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K. C. Ramakrishna edited this page May 17, 2026 · 8 revisions

Welcome to the Digital_Assistant_Client wiki!

Enterprise GenAI Adoption: A Comprehensive Guide for Software Teams
(Draft) Enterprise Agentic Adoption: A Comprehensive Framework for Reliable, Maintainable, Hardened code
Some examples on how genAI can solve complex cross domain problems

Wiki pages Pages 65

Home
(Draft) Enterprise Agentic Adoption: A Comprehensive Framework for Reliable, Maintainable, Hardened code
(Placeholder) Risks (and Mitigation Strategies) of using LLMs for generating code for Enterprise Production Deployments
A Developer's Guide to LLM Command‐Line Tools: A Comparative Analysis with Code Examples
Accelerate sprint productivity with genAI assisted Unit Tests
Agent backend journey: opencode‐cli → pi SDK → opencode SDK
Agentic coding
Bot to help me set up Finance and Accounting Practice
Bot to help me with Corporate Law
Bot to help me with Google Analytics
Bot to help me with Marketing UDAN
Bot to help with Business Strategy
Bot to help with design compensation for various positions in the organisation
Bot to help with Market Adoption
Bot to help with Node ‐ a Node expert
Bot‐ception: Creating AI Bot That Build Bots
Building Prompts for Repeated Use
Case Study and Deep Dive into genAI assisted Error Handling
Case Study: Enhancing Code with comments and documentation using genAI
Case Study: genAI assisted validations
Case Study: Generating Unit Tests to get to 95% coverage in under 30 mins
Case Study: Transforming Error Handling Through GenAI ‐ A CTO's Perspective
Client development environment setup
Comparative Analysis of LLM Performance in Generating Unit Tests with SourceGraph Cody
Comparative Study of Coding Agents: Junie, Jules, and AMP
Concept Paper: Open Source Drone Protocols for Public and Private Urban Transport
Docker Compose Optimization Using GenAI: A Technical Case Study
Double the Productivity of Large Developer Teams by Adopting GenAI: A Practical Guide
Draft Error handling
Draft Using genAI to improve Error Handling across the project
Draft: A Software Engineering Framework for Enterprise‐Grade Code using AI Coding Agents
Draft: Enterprise Guide to Agentic AI Development
Draft: genAI benefit variations based on seniority of developers
Draft: How to utilise the freed‐up bandwidth of the Team
Draft: Roadmap to harden the application using genAI
Effortless Security Enhancement: GenAI's Impact on Input Validation and Sanitization
Enhancing Configuration with GenAI: A Case Study in Optimizing "tsconfig.json" for TypeScript
Enterprise GenAI Adoption: A Comprehensive Guide for Software Teams
Experienced Technical Writer
Experiment: Improving webpack Configuration with openDevin and Sonnet 3.5 200k
genAI for secure code in the Enterprise
genAI upgrade of babel.config
List of bots that we created for ourselves (and use frequently)
List of omissions in our hurry to launch MVP (later fixed with genAI)
NGINX Configuration Improvements using genAI
Obsolete: Architecture for true semantic search for better accuracy in retrieving user queries.
Optimizing "Jest" Testing Configuration with GenAI: A Case Study for Enterprise Teams
Pending security documentation
Placeholder for list of stuff to do with LLMs
Prompt: Software Engineering Quantitative Expert
Proof of Concept: genAI excels in cross domain expertise
Quantitative benefits of tsconfig improvements ~ 20% ‐ 30%
Quantitative Productivity Benefits of "Code Hygiene" with genAI
Required Expertise Analysis for Enterprise‐Grade Docker Compose Configuration
Revolutionizing Software Architecture with LLMs: A Concept Paper (and potential my next Open Source Project)
Rough Re architecture Notes
Secure Code Guru Bot
Short overview of genAI Coding Assistants
Short Overview of UDAN Agent
Some tips on prompting to improve DevSecOps
Technical Case Study: GenAI‐Driven Error Handling Implementation ‐ A Technical Deep Dive
UDAN Case Study: Real‐World GenAI Implementation Across the Development Lifecycle
Using LLMs to improve Build Process
Webpack Configuration Refactoring: Testing with a simple, unsophisticated prompt
Why we chose the 'UDAN' approach among the different Approaches to integrating LLMs into user interfaces

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