Puzzle x Felicis Ventures
Take it from Dasha Maggio, Partner and Head of Founder Success at Felicis, a VC firm investing in companies across stages, sectors, and geographies. They’ve just announced their ninth core fund of $825 million and have a portfolio that includes companies like Shopify, Adyen, and Credit Karma.
For our expert funding series, we sat down with Dasha to get into topics like:
Read on for more...
TL;DR
- Founders who understand their numbers — burn, runway, margins — maintain control over what they can actually influence, even when macro conditions turn hostile.
- Great investor updates show real-time KPIs and variance from the prior period; transparent, consistent reporting builds trust and keeps investor relationships healthy.
- Data and gut instinct aren't opposites — use numbers to quantify runway-constrained decisions and to give stakeholders an objective rationale for the choices you make.
- Investing in clean bookkeeping from day one is a green flag to investors — and in Dasha's experience, inconsistent numbers in a pitch deck have become deal-killers that cause investors to walk away entirely.
- In 2026, financial discipline is table stakes at every stage — founders who run a clean financial engine from the start are the ones who can actually raise.
“Knowing your numbers is fundamental to figuring out how to turn strategy, capital, people, and inputs into something that will ultimately deliver your vision.”
Here’s the deal: Founders need to understand their company’s engine to know exactly what’s in vs. what’s out of their control.
There will always be movement outside your company’s bubble that you cannot control — macro conditions, competitive moves, you name it.
So, focusing on your own business formula and understanding its inputs and levers is the path to success.
The internal engine of a company is composed of two things:
That’s why knowing your numbers from day one is integral to your ability to turn strategy, capital, people, and inputs into the brand vision you’re striving for.
While KPIs vary dramatically by business, there are still metrics that all founders should track — including the core startup metrics like burn rate and runway. Founders who want to pressure-test those numbers can use a founder burn rate audit to surface gaps before an investor does.
When Dasha reads a great investor update, it gives an instant snapshot of the company. The update typically includes KPIs like:
| Investor Update Metric | What It Signals | Include Variance? |
|---|---|---|
| Revenue & total dollars raised | Top-line growth trajectory and capital efficiency | Yes — show period-over-period change |
| Current headcount | Burn composition and hiring pace relative to growth | Yes — flag new hires or reductions |
| Margins | Unit economics health and path to profitability | Yes — flag compression or improvement |
| Burn rate | How fast the company is consuming capital | Yes — compare to prior period and plan |
| Runway | Months of capital remaining at current burn | Yes — critical for investor confidence |
Superior updates also indicate variance, AKA what’s changed since the previous check-in. This includes both positive and negative spikes to investors so they know what’s working.
Ultimately, the investor update is a source of truth and visibility into company dynamics. In Dasha’s experience, founders who send consistent updates with transparent numbers have a better handle on their runway and more comfortable investor relationships.
“Understanding the engine of what you're building so that you know your level of control as a founder is, in my opinion, the critical piece. I think it is never too early to get connected with that.”
Often, founders have the right gut instincts about what growth levers to pull. The instinct to hire, expand a channel, or double down on a product bet is usually grounded in pattern recognition — and that matters.
But some decisions can't run on instinct alone, because the constraint is a hard number. Take a common scenario: your burn rate tells you you have 4 months of runway left. Your gut says hire 3 engineers to accelerate the roadmap. Before you act on that instinct, you have to stress-test it against the number — what does adding 3 salaries do to your runway? Does it drop you to 2 months, below the threshold where you can close a round? The data doesn't override your judgment; it tells you whether you can afford to act on it right now, or whether you need to sequence the decision differently.
A simple rule of thumb: use your gut to identify which levers to pull, and use your data to determine how far you can pull them given your current runway and burn. When the two conflict, that tension is the signal — it usually means you need to either find more capital or reorder your priorities before you move.
Also, numbers are the clearest way to convey decision-making rationale to stakeholders. When you've already stress-tested a decision against your financials, you walk into that board conversation with objective input — not just conviction. Tools like real-time accounting software keep those numbers current so you're never caught off guard.
The founder of Felicis, Aydin Senkut, is a fan of Formula 1, so he brought the idea of telemetry to his team.
In F1 racing, cars have hundreds of sensors on them that send data to the driver, the ground team, and the crew during a race. Each sensor tracks one variable in real time — tire pressure, fuel load, brake temperature — so the team can make a pit-stop decision with 10 laps to go rather than reacting after something fails. A startup's burn rate works exactly the same way: it's a live sensor on your financial system that tells you whether you can push harder or need to conserve, before you're forced to react.
This allows the teams to achieve their ultimate internal goal: improving efficiency.
The name of the game isn’t building as many features as possible or spending the most money. It’s figuring out how to translate inputs into outputs efficiently. The team at Felicis emphasizes that this approach is also directly applicable to companies and metrics.
As companies mature, they tap into that telemetry — or complex, real-time metrics that provide a rigorous way of assessing trade-offs and options.
“There's no one correct path that works across every single company. You need toweigh your gut instinct and the data against each other.”
Founders are constantly trying to avoid different types of debt: tech debt, organizational debt, financial debt, trust debt, and more.
How can you avoid debt when it comes in so many forms? The answer is by investing in your accounting and bookkeeping from the beginning.
Prioritizing your accounting is a green flag to investors
Imagine the concept of a trust battery between investors and founders (the ‘trust battery’ concept comes from Tobi at Shopify). You risk exhausting that battery if you blindside investors or make bad decisions due to accounting errors.
Accounting often gets lost in the push to hire the right people and find product-market fit. However, the errors that may occur if you overlook it are existential and painful — and a smooth month-end close is the clearest signal that your books are under control.
The key here is that bookkeeping is within your control, so you should strive to own it.
In addition, when investors see great accounting, it signals that this company understands potential risks and has the tools to handle them. Founders heading into diligence should review their book value due diligence prep to avoid the inconsistencies that have caused Dasha to see investors walk away entirely from companies with inconsistent numbers in their pitch decks.
“If you believe in maintaining trust with investors, investing in bookkeeping is an important ingredient in maintaining that trust. It allows for consistency, visibility, predictability, and a sense of control over your growth.”
Dasha emphasizes that no matter the market environment, founders should strive to be as nimble as possible and determine their own paths.
It’s true that there is less margin for error in the current market.
At the same time, Dasha notes this doesn’t mean “doom and gloom” for founders.
The macro-environment may not be within their control, but how dialed in they are to their business inputs and understanding of business mechanics absolutely is.
Founders can make great decisions when they arm themselves with the right financial tools.
Everything Dasha describes above has become table stakes in today's funding environment. The era of raising on vision alone is over. In 2026, investors expect the financial discipline of a public company — even at seed stage.
According to a July 2026 analysis by Burkland, Series A investors are now underwriting a machine, not a thesis. They want founders who can defend their forecast assumption-by-assumption — and they're walking away from decks where metric definitions shift between the pitch and the data room. Specific red flags include less than 6 months of runway, inconsistent ARR definitions, and a forecast the team can't explain.
The practical implication: the founders who will raise in this climate are the ones who've been running their financial engine cleanly from day one. Real-time visibility into burn, runway, and unit economics isn't a fundraising tactic — it's the foundation that makes every other decision defensible. Founders preparing for a raise can get a head start with the Series A Readiness Pack, while those serious about tightening their books are turning to financial close automation software to get there without adding headcount.
The numbers back it up. Global VC is on track to hit $1T in 2026 — but Dealroom data shows 77% of that capital is landing in scaleup rounds of $100M or more, leaving early-stage founders competing harder for a shrinking share. In that environment, one metric has become a de facto gate: burn multiple. Investors are now expecting burn multiples well below 2x — many citing a range of 1.5x or lower — before they'll seriously engage at the Series A level, meaning every dollar you spend needs to be traceable to revenue. If your books aren't clean enough to defend that number in a first meeting, you're not in the running.
It depends on how messy "messy" is. If you're mid-cleanup, the safest path is to finish reconciling and categorizing in QuickBooks first, then migrate — you don't want to import errors you're actively fixing. If your historical books are a lost cause (years of uncategorized transactions, no reconciled periods), starting fresh from a clean cutover date is often faster and cheaper than importing chaos. A good rule of thumb: import cleaned data only when you have at least one fully reconciled period you trust. Puzzle's onboarding team can help you set the right historical start date so your opening balances are solid before any data moves.
Plaid — the bank connectivity layer most accounting platforms use — typically pulls 90 days of historical transactions for most U.S. banks, though some institutions limit it to 30 days or less. A handful of larger banks (Chase, Bank of America, Wells Fargo) have negotiated direct data feeds that can reach further back, but that varies by account type. Credit unions and smaller regional banks are often the most restrictive. The practical implication: if you need transaction history beyond 90 days, plan to import a CSV directly from your bank's portal rather than relying solely on the Plaid connection. Puzzle supports both methods so you're not stuck with whatever the bank allows.
Puzzle runs a guided close checklist that surfaces outstanding items — uncategorized transactions, unreconciled accounts, missing receipts — so you're not hunting for problems manually. Once every bank account is reconciled, all transactions are categorized, and your balance sheet ties to your bank statements, your books are ready to share. For investor updates, that threshold is reconciled + categorized. For the IRS or audit purposes, you also need accruals and any adjusting journal entries finalized. Puzzle's close status indicators show you exactly where you stand in real time, so you're not guessing whether the books are investor-ready — you can see it.
Start with your oldest unreconciled period and work forward chronologically — reconciling out of order creates cascading discrepancies that compound fast. If you're importing years of history, set a realistic cutover date (typically the start of the current fiscal year, or the start of the most recent quarter you care about), reconcile from there forward, and treat everything before that date as a historical import with a validated opening balance. Never try to reconcile backwards from today. Puzzle flags accounts with no prior reconciliation history so you know exactly what needs attention, and the reconciliation workflow walks you through matching statement balances step by step.
Your data in the old platform stays intact — migration doesn't delete or overwrite anything in QuickBooks or wherever you're coming from. What moves to Puzzle is a copy: your chart of accounts, historical transaction data (within the import window you choose), and opening balances. You set the go-live date, and Puzzle takes over from there. Most teams keep their old platform in read-only mode for 60–90 days after migration so they can reference historical reports while getting comfortable with the new setup. Your historical financials are always accessible; the only thing that changes is where new transactions are categorized and reconciled going forward.
The biggest gains come from two places: automated transaction categorization and OCR-based document capture. Instead of manually coding each bank transaction to a GL account, AI learns from historical patterns — vendor name, amount, account type — and categorizes the bulk of transactions automatically. OCR handles the document side: receipts and invoices are captured, parsed, and matched to transactions the moment they're uploaded, eliminating manual re-keying entirely.
In practice, firms using AI-native tools like Puzzle are shifting from a data-entry workflow to a review-and-approve workflow. Rather than spending hours on categorization each month, bookkeepers review a queue of AI-suggested entries, correct the edge cases, and close. The time savings compound: clean, real-time books mean fewer catch-up reconciliation sessions, faster month-end closes, and fewer errors that require manual investigation. For founders, this is the operational difference between books that are always three weeks behind and books that reflect yesterday's transactions — the kind of real-time visibility Dasha describes as table stakes for investor-ready companies.
Puzzle's AI handles the bulk of transaction categorization automatically — instead of manually coding each line item, it matches transactions to the correct GL accounts based on vendor, amount, and historical patterns. OCR captures data from receipts and invoices the moment they're uploaded, eliminating manual re-keying entirely.
The practical result: work that used to take hours per month — sorting, categorizing, and reconciling — is reduced to a review-and-approve workflow. Your books stay current in real time rather than lagging weeks behind reality, giving you exactly the kind of financial visibility Dasha describes as table stakes for investor-ready companies.
Both Gusto and Rippling can sync payroll data directly to your accounting software, but the setup determines whether you get a clean journal entry or a lump-sum transaction you still have to break down manually.
With Gusto, you map each payroll component — gross wages, employer taxes, benefits deductions, net pay — to the corresponding GL accounts in your chart of accounts before the first payroll run. Once mapped, every payroll syncs as a fully itemized journal entry: debits to the right expense accounts, credits to cash and liability accounts, dated to the payroll period. Puzzle's Gusto integration handles this mapping automatically, so the journal entry lands in your books the moment payroll processes — no manual journal entry required.
Rippling works similarly: its accounting sync pushes payroll journal entries to your GL in real time, with each line item tied to the correct department or cost center if you've set up class tracking. The key configuration step is making sure your Rippling cost centers map to the right GL accounts in Puzzle before your first sync — otherwise you'll get a consolidated entry that requires manual splitting. Once that mapping is set, payroll journal entries are fully automated every cycle. The practical result is that payroll stops being a monthly reconciliation headache and becomes one less thing between you and a clean month-end close.
