Equals solves the startup data problem by integrating directly with modern data infrastructure tools (Stripe, Salesforce, QuickBooks via Fivetran/Stitch-like ETL) and connecting that data into a spreadsheet interface, eliminating the need for a separate data warehouse or BI tool

A CRO (Chief Revenue Officer) told Chase that his financial model was 'just a spreadsheet exercise' that didn't reflect how the business actually operates, but Chase's ability to articulate multiple scenarios and use the model as a framework for testing assumptions allowed him to defend the model's value

Equals' Command+K shortcut (on Mac) enables users to ask natural-language questions of their spreadsheets and data, similar to Spotlight search on macOS, and is being powered by AI to handle requests like 'sum this column' or 'add a border to this range' without manual formula entry

The most important lesson Chase learned in his career is active listening: FP&A professionals are naturally high-execution, confident people who tend to state opinions with false certainty, but the longer he's practiced, the more he realizes listening to others' perspectives and business mechanics understanding is more valuable than pushing his own model

Learning financial modeling fundamentals early (via formal education, courses from providers like Wall Street Preps or Carl Talamanidis, or resources like FMI) is critical because self-taught modelers often develop bad habits that are hard to break later, whereas structured learning prevents Franken models and builds design discipline

Financial models are not the primary decision-making tool; rather, decision-making is driven by the intuition of directly responsible individuals (DRIs) informed by multiple inputs, of which financial models are a heavily weighted but not determinative part

Early-stage startups face a fundamental data infrastructure problem: they lack data warehouses, BI tools, and integrated data pipelines, making it impossible to pull source system data (billing, CRM, accounting) into analysis without manual copy-paste workflows

Chase's master's degree in engineering (rather than MBA) was pivotal because it gave him the dual mindset needed to bridge finance and software engineering, enabling him to recognize that VBA models could be replaced with cleaner architectural approaches and later to understand modern data infrastructure integration

Spreadsheets remain the fundamental tool for financial thinking and prototyping because they force explicit, precise problem articulation that prevents analysis paralysis and ambiguous decision-making

Equals' actual use cases at Unicode include: (1) AR reporting connected to Stripe billing data, (2) automated weekly revenue reports sent to senior staff via Slack showing week-over-week ARR additions and quarterly progress vs. goals, and (3) three-statement financial models pulling GL accounts from QuickBooks

The key to building a robust financial model is not starting with formulas or elegant mechanics, but first understanding what stakeholders are trying to accomplish and putting yourself in their shoes to articulate that into model structure

Balance sheet analysis is one of the most powerful but underused tools in financial modeling because most practitioners focus only on P&L, yet the balance sheet reveals acquisitions, product expansion, and capital structure decisions that P&L alone obscures

Chase created a model counting F-words in the Netflix show Bloodline by downloading scripts, loading them into Excel via Excel Wings (a Python-Excel tool), and analyzing the results, finding approximately 28 F-words per episode—a fun but ultimately frivolous application of modeling

Chase does not use circular references, VBA, or external workbook links in his models because they create maintainability and auditability problems; he prefers horizontal layouts, uses VLOOKUP almost exclusively with INDEX MATCH as a secondary option for time-constrained situations, and follows the FAST standard for model design

Chase believes Excel will never die because it is embedded in enterprise infrastructure and human behavior, comparable to Twinkies and cockroaches for their cultural permanence, but that doesn't preclude newer tools like Equals from replacing it in specific use cases like data integration and collaborative reporting

In the short term, AI will be fantastic as a co-pilot to help with financial modeling and spreadsheet tasks, but it's unlikely to fully replace human modeling and judgment in the near term

Chase uses Equals' AI shortcut almost daily, sometimes hourly, and has noticed himself becoming 'lazier' (more efficient) because the tool removes the friction of clicking through menus or remembering formula syntax

Finance professionals are by nature skeptical of AI and black-box tools because finance demands risk aversion, transparency, and understanding of every calculation, which may slow AI adoption in finance relative to other domains

Chase moved from a corporate finance role at University of Alabama Birmingham (earning $27,000/year) to grad school, then to consulting, driven by both necessity and curiosity, suggesting that career pivots often come from dissatisfaction with current compensation or growth prospects rather than vocational clarity

Chase encountered a financial model written entirely in VBA at an IT consulting company early in his career where there was significant disconnect between the VBA code and what appeared in the spreadsheet, creating a nightmare for a junior finance person trying to understand the model.