Business came first.
Technology followed.
This is the connected story of how basic Excel learned for business needs led to KDP, physical ecommerce, manufacturing, China sourcing, Amazon scale, international marketplaces, large catalogs, advertising, automation, software, infrastructure, content systems and eventually AI.
I did not begin by learning programming and then searching for a business problem. I began with business problems. The first technical step was basic Excel because products, prices and operations needed to be organized. When spreadsheets became repetitive, I learned automation. When automation became too limited, I moved into Python and APIs. When applications needed to run reliably, I learned infrastructure. When rule-based systems reached the limits of messy real-world data, AI became the next layer.
Between those technical transitions came years of physical commerce: KDP, marketplace selling, product development, manufacturing, sourcing from China, inventory, FBA, advertising, compliance, international accounts and owned ecommerce stores. Content production became another parallel distribution system, using many of the same operational lessons in a different medium.
The story is organized around connected experience rather than as a résumé. Every chapter shows why a capability appeared, what problem it was used to solve and what it led to next.
Read the journey
in order.
I first learned Excel for basic business needs. As the amount of product, pricing and marketplace data grew, simple spreadsheets became formulas, bulk files, automation and eventually software.
02Before Gifts LoftKDP was an early doorway into digital commerce.Before Gifts Loft, I worked with Amazon Kindle Direct Publishing. KDP gave me early experience with Amazon, digital products, metadata, keywords, categories and online discovery.
03Founder chapterThen the work became physical.Gifts Loft became an early serious ecommerce venture. The work covered product selection, listings, pricing, stock, packaging, customer operations and selling through Indian marketplaces.
04Product & operationsEcommerce taught me the factory side too.For years I worked around manufacturing and product development, especially wall clocks, home décor, mirrors, posters and related consumer products.
05Cross-border sourcingThe supply chain expanded beyond India.Direct sourcing work in China and Yiwu added supplier discovery, factory negotiation, procurement, product costing, bulk buying and cross-border logistics to my experience.
06Marketplace scaleAmazon turned the operation into scale.Over roughly five years around Amazon India, I worked across Seller Central, FBA, catalog operations, inventory, pricing, advertising, account health, compliance and customer operations.
07International operationsOne marketplace became more than twenty accounts.The marketplace experience expanded into 20+ international seller accounts and cross-border operations, with responsibility spanning listings, inventory, advertising, account health and repeatable workflows.
08The data problemThe catalog became too large for manual work.Large catalogs became a recurring problem across marketplaces, Shopify and WooCommerce: titles, descriptions, variants, attributes, taxonomy, metadata, feeds and search all had to remain usable at scale.
09Owned commerceMarketplaces led to owned storefronts.I built and operated Shopify and WordPress/WooCommerce sites across books, home décor, jewelry and high-SKU commerce, including Universal Reads, Amegweb and Efinito.
10Demand generationBuilding the store was only half the job.Growth work spans Google Ads, Performance Max, Shopping, Amazon PPC, Merchant Center, product feeds, technical SEO, Search Console, conversion optimization and international acquisition.
11AutomationSpreadsheets eventually started writing their own work.When bulk ecommerce workflows became repetitive, Apps Script became a way to transform data, call APIs, generate fields and automate work directly around Google Sheets.
12Software builderThe spreadsheet became an application.I began building Python applications for CSV/Excel ingestion, header detection, bulk SEO, AI generation, product cleanup, partial saving, resume logic and book-data verification.
13Production systemsBuilding software meant learning where it runs.As more applications and commerce systems moved beyond managed platforms, I learned to deploy and troubleshoot the infrastructure underneath them.
14Digital productThen I started building software for users, not only for myself.Gergeant is a Next.js utility platform spanning PDF, image, calculator, networking, business and productivity tools, with ongoing work around SEO, accounts, browser/server processing and AI.
15AI operating layerAI made messy business data programmable.Current AI work combines OpenAI APIs, Python, structured prompts, verification, classification, SEO enrichment, catalog cleanup and approval-driven workflows.
16Now & nextThe next step is agents that can operate the system.The current direction connects AI models with n8n, FastAPI, APIs, databases and operational tools so an agent can inspect, decide, act, validate and escalate when human approval is needed.
+Parallel chapter · distributionContent became another operating system.YouTube, live streaming, OBS, editing and AI-assisted media became another place to apply repeatable operating systems.
This biography does not end with “success.” It continues with whatever gets built, learned, scaled or changed next.