A bottoms-up forecast is the projection methodology that builds revenue, costs, and other projections from specific underlying drivers rather than top-down market-share assumptions. Drivers include customer counts by month, ARPC by segment, conversion rates, deal sizes, and sales rep productivity, rather than vague claims like "1% of a $50B market." It produces projections that are testable, defensible, and credible to sophisticated investors because the math is built from observable inputs. It is the methodology that distinguishes rigorous financial modeling from optimistic projection.
The bottoms-up approach:
Identify driver components:
The Business Model Canvas is a one-page framework by Alex Osterwalder that maps nine building blocks of a business model on a single visual canvas. The blocks are customer segments, value propositions, channels, customer relationships, revenue streams, key resources, key activities, key partnerships, and cost structure. Popularized in Osterwalder's 2010 book "Business Model Generation," it facilitates strategic discussion, business model iteration, and team alignment around how the business actually creates and captures value. It is particularly useful for established companies exploring new business models, founders pre-launch thinking through their model, and strategic planning sessions, and it's one of the most wide...
A business plan is the written document describing a company's business model, target market, competitive position, operating strategy, team, and financial projections. It's used to align stakeholders and guide execution. Modern startup business plans rarely take the form of the traditional 30 to 40 page document; they more often appear as a pitch deck, a one-page Lean Canvas, or a short narrative memo.
The traditional business plan, with its executive summary, market analysis, organizational structure, marketing plan, operations plan, and 3 to 5 year financial projections, originated in mid-twentieth-century corporate planning and remains the format banks and SBA loan officers expect. For startups, the format has shifted. Mos...
Business strategy is the integrated set of choices that determines how a company creates and captures unique value. It includes which markets to serve (and which to exclude), how to position relative to competitors, what to build vs buy vs partner for, how to win in chosen markets, and what trade-offs to accept. The discipline is making explicit choices that produce a differentiated position rather than defaulting to generic "be excellent everywhere" non-strategy that produces no actual competitive advantage. Strategy is choices; without choices, there's no strategy.
What strategy actually is (per Michael Porter and others):
Choices about scope:
The foundational vocabulary every founder needs before everything else. This cluster covers what a startup actually is, the categories that distinguish them (bootstrap vs venture-backed, lifestyle vs scale-up), the support ecosystem (accelerators, incubators, agencies), the early credits and grants founders chase, and the structural concepts (founder-market fit, why startups fail) that shape every decision that follows. 21 entries.
If you're new to startup vocabulary, start here. If you're a few years in, this cluster is the conceptual baseline against which everything else is read.
Accounts Payable (A/P) is the balance-sheet liability tracking money a company owes vendors for goods or services received but not yet paid for. It's recorded as a current liability because the company has an obligation to pay, with payment timing managed strategically to balance cash flow against vendor relationships. A/P is the mirror image of A/R: where A/R is what customers owe the company, A/P is what the company owes others.
The basic mechanics:
Company receives an invoice from a software vendor for $10K with Net-30 terms. On the day of receipt:
30 days later, company ...
How startups end (and what determines who gets what). This cluster covers the major exit paths (IPO, acquisition, SPAC, direct listing), deal structures and terms (LOI, definitive agreement, earnout, holdback, reps and warranties), the rights that affect exit outcomes (drag-along, tag-along, ROFR, lockup), and the mechanics specific to exits (liquidation waterfall, exit multiples, QSBS). 26 entries.
Exits are the moment when years of equity decisions become real money. Founders should know this vocabulary years before they need it.
North Star Framework vs North Star Metric: the framework is the full operating system, the NSM plus input metrics, business outcomes, team rituals, and decision rules. The [North Star Metric] is just the single number at the center of it. If you're picking the metric, read NSM; if you're installing the operating system around it, you're in the right place.
The North Star Framework is the strategic alignment system developed by Amplitude that connects a North Star Metric to input metrics and business outcomes. The North Star Metric is the one metric most-correlated with long-term business success and customer value; input metrics are levers teams can move to improve it; business outcomes are the financial results the N...
Strategy meets numbers meets operations. This cluster covers business strategy frameworks (BMC, lean canvas, SWOT, blue ocean), financial modeling and projections, SaaS metrics (ARR, MRR, CAC, LTV, NRR, Rule of 40), market sizing (TAM/SAM/SOM, addressable market), sales operations (pipeline, quota, cycle length), CFO-level financial discipline (working capital, AR/AP, DSO, deferred revenue), and the reporting cadences that hold it all together (board deck, OKRs, KPIs, business reviews). 87 entries.
This is the largest cluster, the home for everything quantitative about running a startup.
A foundation model is a large-scale AI model trained on broad, diverse data and designed to be adapted to many downstream tasks. Adaptation happens via fine-tuning, prompting, or API access. The term was coined by Stanford's Center for Research on Foundation Models in 2021 and now describes GPT-4, Claude, Gemini, Llama, Mistral, and similar models that form the base layer of the modern AI stack. The foundation model is to AI applications what AWS is to web applications: shared infrastructure that powers everything built on top.
What distinguishes foundation models:
Scale: hundreds of billions to trillions of parameters. Trained on hundreds of billions to trillions of tokens of data.
General-purpose training: trained on broa...