This article is based on interviews originally published by Built In Chicago. Company details reflect conditions at the time of publication (June 2019).
Innovation in tech is not always about chasing the newest framework or the hottest cloud service. Sometimes it comes from questioning a long-standing workflow, hiring differently, or applying a familiar pattern — such as continuous delivery — to an unexpected domain like hardware. Leaders at nine Chicago-based tech companies explained how they keep their teams sharp, what engineering practices they rely on, and which trends they were watching heading into the 2020s.
1. Guaranteed Rate — Continuous Improvement of Core Product
Company focus: Digital mortgage origination and processing.
Founder and CEO Victor Ciardelli said Guaranteed Rate has invested heavily in proprietary technology since its founding in 2000. In 2015 the company launched what it described as the first online lock-to-close mortgage processing engine. Rather than treating that launch as a finish line, the engineering team continued iterating on speed and usability.
“We’re always working to make our existing technology better and exploring new tech to make us more efficient and ahead of the curve. It’s all about changing the future of homebuying.”
— Victor Ciardelli, Founder & CEO, Guaranteed Rate
Key takeaway: First-mover advantage means little without sustained iteration. Guaranteed Rate’s approach treats the initial launch as a baseline and treats every subsequent release as an opportunity to close the gap between what customers tolerate and what they actually want.
2. IMC Trading — Bringing Software CI/CD Practices to Hardware
Company focus: Technology-driven trading across 100+ regulated international platforms.
Hardware Engineering Team Lead Rob (last name not provided in the source) described a deliberate effort to apply software-world release discipline — verification automation, integration testing, and fast feedback loops — to the FPGA (field-programmable gate array) development process, which traditionally moves far more slowly than software delivery.
“We heavily invest in verification, release and integration automation in ways that you just don’t see in the larger hardware world yet.”
— Rob, Hardware Engineering Team Lead, IMC Trading
The team was also evaluating Bazel, Google’s open-source build system, to accelerate FPGA build caching and iteration cycles.
Key takeaway: DevOps principles — automated testing, incremental releases, fast feedback — are not exclusive to software. Trading firms and other latency-sensitive hardware shops are beginning to apply the same discipline to HDL development pipelines.
3. HealthJoy — Microservices, the Strangler Pattern, and Distributed Team Tooling
Company focus: Employee healthcare benefits guidance platform.
VP of Engineering Sajal Dam outlined a three-layer approach to staying current: architectural patterns, DevOps practice, and culture.
- Strangler pattern: Rather than risky big-bang rewrites, HealthJoy incrementally replaces legacy components by routing traffic to new microservices while keeping the old system in place until it can be safely retired.
- Technical debt cadence: Agile planning explicitly budgets time for paying down debt alongside feature work.
- CI/CD pipeline improvements: Dam was evaluating new plugins to improve build, test, and deploy stages.
- Container orchestration: The team was analyzing multiple Docker orchestration tools to handle dynamic scaling, service discovery, monitoring, and maintenance of their SaaS platform.
- Collaboration tooling: New development tools were being evaluated specifically for distributed engineering teams.
“Using DevOps best practices, we minimize the risks in regularly upgrading and deploying new technologies.”
— Sajal Dam, VP of Engineering, HealthJoy
Key takeaway: The strangler pattern and microservices architecture give teams a safe path to modernisation. Pairing that with rigorous CI/CD and explicit debt-reduction sprints reduces the accumulation of risk over time.
4. Kin Insurance — Talent First, Technology Second
Company focus: Data-driven home insurance platform.
Co-founder and CTO Lucas Ward argued that the most important engineering decision a company makes is a hiring decision, not a technology decision.
“We don’t chase trends, we chase talent. Your tech is only as good as the people implementing it.”
— Lucas Ward, Co-founder & CTO, Kin Insurance
Once strong people are in place, Ward said, tools like Looker (analytics) and Segment (customer data infrastructure) give operational teams the insight to iterate on customer-facing workflows without blocking core engineering from building complex, domain-specific systems such as Kin’s own policy administration system — the internal platform handling underwriting, rating, billing, and accounting.
The team was also exploring machine learning for catastrophic risk prediction, and anticipated that smart-home data would eventually feed into more granular insurance products.
Key takeaway: Separating operational tooling (off-the-shelf analytics and data pipelines) from domain-specific engineering (proprietary insurance systems) lets talented generalists move fast in one layer while specialists go deep in another.
5. CityBase — Hackathons, Conferences, and Canary Deployments
Company focus: Digital payment and engagement services for government agencies and utilities.
Director of Engineering Mike Awine emphasised that sustainable innovation requires diverse input, not a single visionary. Concrete practices CityBase uses include:
- A multi-day, companywide hackathon to surface ideas from across the organisation.
- Sponsoring engineers to attend conferences such as ElixirConf.
- Open sharing of articles and conference talks internally.
- Transparency around company goals so individuals can make well-informed decisions.
On the engineering side, the team was building toward canary deployments — releasing changes to a small subset of traffic before full rollout — supported by improved monitoring and instrumentation in their CI/CD pipeline.
“Navigating a perpetually changing business and technology landscape requires the diversity of thought of many people, not just a single person.”
— Mike Awine, Director of Engineering, CityBase
Key takeaway: Canary deployments require investment in observability before they deliver value. CityBase’s path — improve monitoring first, then enable progressive delivery — reflects a pragmatic sequencing of DevOps maturity.
6. Narrative Science — Revenue Operations and Conversational Marketing
Company focus: Natural language generation platform that converts structured data into plain-English narratives.
COO Nick Beil highlighted an organisational innovation alongside the technical one: merging marketing, sales, and customer success into a unified revenue operations function so that the customer journey is handled with a single coherent strategy rather than handoffs between siloed teams.
On the product side, the company deployed its own NLG technology internally — a tool called Lexio that converted Salesforce pipeline data into plain-English stories delivered by email, enabling non-technical staff to understand sales performance without querying dashboards.
“Our entire team gets stories emailed to them from Lexio as if an analyst was sending them in real time. It’s spurred a continuous internal dialogue about our business performance.”
— Nick Beil, COO, Narrative Science
Key takeaway: Dogfooding your own product is one of the most credible forms of product validation. It also forces the product team to experience the friction that external customers face.
7. Foxtrot — Build vs. Buy Discipline in a Fast-Growing Startup
Company focus: Tech-enabled retail and delivery service for food, beverages, and goods (Built In Chicago profile).
CTO and co-founder Taylor Bloom described a pragmatic framework for technology decision-making: understand popular trends and tools thoroughly, but resist the temptation to adopt them unless they are genuinely the best fit for the problem at hand.
“It’s important to be able to understand if it’s worth actually building something, or if we can adapt a tool off the shelf to meet our needs and save time.”
— Taylor Bloom, CTO & Co-founder, Foxtrot
The engineering team was applying machine learning to two specific problems: personalised product recommendations and courier fleet routing — both areas where proprietary models can produce a measurable competitive advantage over generic solutions.
Key takeaway: The build-vs-buy question has no universal answer. In fast-moving startups, off-the-shelf tools preserve engineering capacity for the problems that genuinely differentiate the product. ML for routing and recommendations is one area where custom models can outperform generic SaaS, making it a reasonable candidate for in-house development.
8. Builtout — Early-Career Internships and Bottom-Up Technology Adoption
Company focus: Marketing and communications platform for commercial real estate operators.
Director of Engineering Alan Spadoni shared two unconventional practices. First, rather than targeting junior or senior university students for internships, Builtout recruits freshmen and sophomores — the reasoning being that the pace of self-directed learning has outpaced the traditional degree timeline, and early recruitment builds loyalty before larger companies can compete.
Second, technology adoption is driven bottom-up: individual engineers investigate frameworks and present findings to the wider team. The article cites an engineer-led evaluation of Vue and React for the front end, and exploration of adding Elixir to the backend stack.
“We encourage people to learn, try things out and teach the rest of the team.”
— Alan Spadoni, Director of Engineering, Builtout
Key takeaway: Bottom-up technology evaluation distributes the cognitive load of staying current across the whole team. It also increases buy-in — engineers who championed a technology are more likely to use it well.
9. Avail — Mobile-First Design Driven by Observed User Behaviour
Company focus: Property management and rental platform for landlords and tenants (Built In Chicago profile).
Co-founder and CEO Ryan Coon described a shift in product strategy driven entirely by observed usage data rather than assumption. When analytics showed that landlords continued using the platform on desktop while renters had moved predominantly to mobile devices, the team split the product approach: desktop-first for the landlord-facing interface (designed to shrink to mobile), and mobile-first for the renter-facing interface (designed to expand to desktop).
“We stay ahead of the curve by keeping the customer at the center of every decision we make.”
— Ryan Coon, Co-founder & CEO, Avail
Looking ahead, the team was exploring how gig-economy on-demand workforce models could be applied to property maintenance — one of the highest-friction pain points in the rental cycle.
Key takeaway: Different user personas within the same product can have radically different device preferences. Treating the platform as a single responsive interface can produce a mediocre experience for everyone. Segmenting by persona and designing intentionally for each is more work but produces significantly better outcomes.
Common Themes Across All Nine Companies
Despite operating in very different domains — fintech, trading, healthcare, insurance, government services, NLG, retail, real estate, and proptech — these Chicago engineering leaders converged on several recurring principles:
- People over tools: Multiple leaders stated explicitly that hiring the right people matters more than selecting the right technology stack.
- Incremental modernisation: Patterns like the strangler pattern, canary deployments, and continuous delivery were preferred over big-bang rewrites.
- Machine learning for domain-specific problems: ML appeared in use cases ranging from risk modelling and fleet routing to product recommendations and workflow automation — always applied to a specific business problem rather than adopted speculatively.
- DevOps as a cultural practice: CI/CD, observability, and automation were treated as ongoing disciplines rather than one-time implementations.
- Bottom-up innovation: Hackathons, conference sponsorships, and engineer-led technology evaluations were used to distribute responsibility for staying current across the organisation.
Original interviews sourced from Built In Chicago. Company details reflect the state of each organisation as of mid-2019.