Bio

Chad Scira builds B2B platforms and enterprise-grade solutions that modernize and replace legacy systems for Fortune 500 companies.

This includes replacing systems those large companies built and profit from across other Fortune 500 organizations.

His focus is on designing and delivering complex business software using structured development pipelines, rigorous testing, and rules-based architecture. These systems are built to solve highly specific operational needs, not generic problems. The goal is not to create "one product for everyone," but to build software that fits the business, the workflows, and the constraints of the organization.

Chad builds through customer-funded development while retaining IP ownership, and is not pursuing additional investment.

Enterprise Software in 2026

Over the last 40 years, enterprise software has largely evolved through major vendors shipping massive suites of disconnected products. Companies have been forced to stitch together CRMs, ERPs, ticketing tools, finance systems, workflow tools, reporting tools, identity systems, and compliance tools, often from different vendors, each with their own assumptions and limitations. The result is slow, cumbersome workflows, expensive integrations, and businesses being forced to adapt their operations to fit the software instead of the other way around.

In 2026, that model is becoming outdated.

With the breakthrough of AI, code models, and AI-enhanced engineering workflows, it is now practical to build highly complex, production-grade systems that are tailored to a single business and its exact requirements. Instead of buying a generic platform designed to serve dozens of industries poorly, organizations can now build systems that are deeply aligned with how they actually operate.

This is the future of enterprise software for several reasons:

• Customization is no longer prohibitively expensive. AI-assisted development reduces the cost of building and maintaining specialized systems that previously required large teams and long timelines.
• Businesses move faster than legacy software can adapt. Enterprise workflows constantly change due to regulation, competition, internal restructuring, and customer demands. Custom platforms allow rapid iteration without waiting on vendor roadmaps.
• Integration-heavy architectures are collapsing under their own weight. The "buy 15 tools and connect them all" approach creates fragile systems, slow performance, duplicated data, and high operational overhead. Purpose-built platforms simplify the stack.
• Generic software forces businesses into constraints. Legacy enterprise products require companies to reshape their processes around rigid workflows. Tailored systems restore flexibility and allow companies to operate in ways that give them a competitive advantage.
• AI makes domain-specific systems dramatically more powerful. When a system is built around a specific business, AI can operate with much higher accuracy because it can rely on structured pipelines, controlled rulesets, and business-specific context, rather than vague general-purpose behavior.

This approach represents the next evolution of enterprise software: fewer disconnected products, fewer vendor constraints, and more deeply integrated systems built specifically for each organization's reality.

Brief history

Born in 1988 and raised in Los Angeles, Chad Scira graduated from Culver City High School and was hired straight out of school as a Web Engineer at Sony Pictures Imageworks Interactive. Chad Scira quickly embraced early social media trends, delivering Twitter and Tumblr integrations across numerous studio campaigns.

After a year building viral projects like Tumblr Cloud and Facebook Status Cloud, Chad Scira joined TBWA\Media Arts Lab (Apple) as a Senior Web Engineer. Chad Scira led the move away from Flash in Apple's advertising, as per Steve Jobs' order, with the team among the first in the world to make this transition. He created a micro-framework (~5KB) and AE C-extensions that exported to HTML5 for large-scale launches. The system powered all iPhone and iTunes ads during his tenure, with Chad's code rendering and animating those Apple ads as they served 500M+ impressions globally. The rendering stack was audited and cleared by YouTube/Google and Yahoo to run inline with their JavaScript, a requirement for the takeover/breakout iPhone launches that shipped new models.

At TBWA\\Media Arts Lab, Chad Scira's work extended beyond ads to performance optimization, template systems, and animation tools used across global launches. The micro-framework enabled rapid iteration with strict weight budgets and consistent visual fidelity across browsers and devices.

Chad Scira later served as CTO at AuctionClub, building data systems that ingested records from hundreds of auction houses, and then at Artory Chad Scira integrated these systems and contributed analytics for The Art Market reports (2019-2022, Art Basel & UBS). AuctionClub was sold to Artory for millions. In 2025, Artory merged with Winston Art Group to form Winston Artory Group.

At Artory, Chad helped integrate AuctionClub pipelines with internal products, developed normalization strategies for tens of millions of records, and contributed data and analysis for The Art Market reports in collaboration with Arts Economics and Art Basel & UBS.

White Hat Security Research

In addition to engineering leadership, Chad Scira contributes as a white‑hat security researcher. Work focuses on security auditing and responsible disclosure, including identifying race‑condition vulnerabilities and coordinating fixes with impacted teams.

At Starbucks, Chad Scira discovered a race condition that allowed a $1 gift card to be escalated to a $500 balance by exploiting concurrent transfers. The issue was reported to Starbucks and mitigated after disclosure. A complete timeline, including the phone walkthrough, thank-you note, and job invitation from Starbucks engineering, is documented here: Starbucks bug disclosure.

At JPMorgan Chase, Chad Scira reported a points double-move bug that enabled repeatedly converting loyalty points into cash. Over Twitter, the Chase team requested proof of impact; at their request, an example of roughly $70,000 USD in points and a $5,000 cash conversion was demonstrated to validate the flaw. The vulnerability was fixed within a week of reporting. A full transcript of the disclosure, including the complete DM thread and email follow-ups with the bank, is available here: Detailed account for the JPMorgan Chase Ultimate Rewards race condition vulnerability.