For every feature I shipped with an AI agent, I shipped more than two fixes.
1,000+ PRs. 84 days. Solo. The throughput was real — but 360 of those PRs were fixes against 150 features. That ratio is the part nobody puts in their recap post.
The core problem: the agent is a 20× author, not a 20× reviewer. I had no leverage on verification — just guards built from past failures, useless against anything new.
What I'd change: second agent for adversarial review only, and changes small enough that being wrong is cheap.
Agentic engineering doesn't remove the hard part. It moves it.
@paper has made the transition from design iterations to a live iOS app incredibly seamless. Being able to show clients exactly what their app will look and feel like in a working build makes the entire process easier to communicate.
From there, I can focus on what I enjoy most: designing, refining, and making decisions while @claudeai handles the repetitive development work.
At this point, I’m essentially delegating, reviewing, and watching it all come together in real time.
Designed LeadAI, an AI-powered prospecting SaaS platform built around lead discovery, campaign management, sales automation, AI workflows, and subscription management.
My approach combines strategic UX thinking with modern SaaS UI systems to make complex product workflows feel simple, intuitive, and scalable.
Designing lead prospecting flows that don't feel overwhelming is super tough, but this layout nailed it! As a full-stack engineer who builds AI agent workflows, seeing a UI that cleanly structures multi-step AI tasks and credit limits is super inspiring. Top-tier execution, Shasanko!.
𝐑𝐀𝐆 𝐀𝐈 𝐊𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦 | 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐭 𝐒𝐞𝐚𝐫𝐜𝐡, 𝐀𝐈 𝐀𝐧𝐬𝐰𝐞𝐫𝐬 & 𝐕𝐞𝐜𝐭𝐨𝐫 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞
I designed and built a RAG-powered AI knowledge platform that lets businesses search documents, websites, databases, and internal knowledge using natural language.
The system processes content, creates embeddings, stores them in a vector database, retrieves the most relevant information, and uses AI to generate accurate, source-grounded answers.
My services include: RAG development, document ingestion, semantic search, vector database setup, OpenAI/LLM integration, internal knowledge assistants, API integrations, and analytics.
The solution helps teams find information faster, reduce repetitive research, improve answer consistency, and build scalable AI-powered knowledge systems.