10. Progression

Progression has three layers inside a company:

1. Eras gate content by company stage. They decide which request kinds arrive and which research is available.

2. Research spends Insight to unlock Components, variants, techniques, and visibility.

3. Features spend Dev Hours to grow the market and change the request mix (Team and velocity).

Above the company, Exit and Legacy carries progress between companies.

Eras#

Market size is multiplied by features, regions, and Venture rules. It caps user growth inside an Era (Simulation).

Request mix by Era#

Shares of demand, in percent. Features and Ventures shift these shares.

Era 0: Garage#

Garage is the tutorial, without tutorial screens. A player who wants to learn a later Era's mechanics first plays its Sandbox track.

• Start. 150 users, $300, and one Burstable App Server running PHP with Apache mod_php and PostgreSQL on the same box, connected to Users and Payments. Analytics is linked to the box.

• First choices, in order.

  1. Collect revenue from the Payments drawer.

  2. Upgrade the box (it is out of CPU credits).

  3. Research "Structured logs" or "Stripe Billing" with the first Insight.

  4. The box runs out of RAM because the database and Apache share it. Split the database onto its own Node. It is the classic first scaling step.

  5. Research "DNS round robin" or "Load balancing" and add a second App Server.

• The lesson. Vertical scaling first, then the first horizontal step. Measure income per second.

• Unlocks available. Stack: PHP-FPM, OPcache, Laravel, Ruby with Rails, Node.js with Express. Components: DNS, Load Balancer.

Era 1: Pre-seed#

• New kinds. write changes the database from read-mostly to contended. login brings bcrypt, 80 ms of CPU per request.

• New problems. The database is the bottleneck. More app servers exhaust Postgres connections. Node.js players see the event loop stall on login. PHP players see FPM workers wait on the database.

• New systems. Hiring and Dev Hours (Team). Incidents begin, with types up to SEV2 only (Incidents).

• Unlocks available. Cache, Connection Pooler, Read Replica, CI/CD Pipeline, Auth Provider, percentiles, alerting, Python, Node.js cluster mode.

Era 2: Seed#

• New kinds. search needs a search engine (Postgres full-text search works at low volume). upload is CPU-heavy and large. bot earns nothing and costs capacity.

• New problems. One App Server type cannot serve all kinds well. Work must be separated: CPU work to Workers through a Queue, bots blocked at the edge, payloads moved to Object Storage.

• Unlocks available. WAF, CDN, Search Engine, Object Storage, Queue, Worker, distributed tracing, Go, Java, C#.

Era 3: Series A#

• New kinds. media makes egress the largest bill line. rt holds connections open, which breaks process-per-request runtimes. buy is worth $25 and needs correctness: no stale reads, no double charges. bid is worth a tenth of a cent and has to answer inside 100 ms; every Venture serves a little of it, and Ad tech serves ten times as much (Exit and Legacy).

• New problems. Availability. Zone outages begin, so a single database is a single point of failure. Users expect 99.9%.

• New systems. Zones (Components), pricing models (Economy), SLOs and error budgets (Incidents), team types.

• Unlocks available. Multi-zone, Kubernetes, Autoscaler, Serverless Functions, Realtime Hub, Document Store, Payment Provider, Feature Flags, canary deploys, Elixir, Rust.

Era 4: Series B#

• New kinds. report scans tables and hurts the transactional database. job runs for seconds and must be asynchronous. ai needs GPUs or an LLM API.

• New problems. Analytics and transactions must separate. GPU cost per prompt decides whether ai makes money. The team passes 15 people and coordination drops velocity.

• New systems. Service splits (Team), data pipelines.

• Unlocks available. Data Warehouse, Event Stream, CDC Connector, GPU Node, LLM API, Vector Index, Service Mesh, sharding, ARM instances.

Era 5: Series C#

• New kinds. feed fans out. hook calls slow customer servers. push fans out on write.

• New problems. Users are global. A single region gives users far away 200 ms of extra round trip, and each region's users leave on their own Apdex. Celebrity accounts create hot keys. Region outages begin.

• New systems. Regions as separate boards, Users per region (Simulation), GeoDNS, regional demand peaks (follow the sun).

• Unlocks available. Multi-region, GeoDNS, Infrastructure as code (Mirror a region), Anycast, Wide-column Store, Distributed SQL, Edge Functions, HTTP/3, hedged requests.

Era 6: Pre-IPO#

Pre-IPO brings no new kinds. Play shifts from growth to proof.

The IPO checklist. All items must be true at the same time:

The list gives the late game concrete goals that are not "more users". It answers the missing end target that Upload Labs has (Influences).

Era 7: Public#

The company is listed, and play becomes an endless series of quarters.

• A quarter lasts 7 calendar days (2 hours 48 minutes of real time at 1×).

• At the start of each quarter, the player sets guidance: a revenue growth target and a margin target. Higher guidance raises the valuation multiple if met.

• At the end, the market compares results to guidance. A beat raises the multiple. A miss lowers it. A streak of beats adds a bonus.

• The player can Exit at any time in the Public Era. The payout uses the current market value (Exit and Legacy).

• Growth slows near the online population. The late Public Era is about margin, regions, latency, and reliability.

Research#

Research costs Insight of named request kinds and takes time, and each item is a Study. Each item belongs to a track, needs an Era, and may need other items. The research screen shows the tree by track, with the locked items of the next Era visible so that the player can plan (Interface).

The track tables below list every item the game offers: 188 items across 10 tracks.

Recipes#

The ◇ column in the track tables is an item's total cost. Its recipe says which Insight pools pay it (Observability). The cost is split equally across the pools in the recipe.

Until Seed, the default recipe is the request kinds that the item's Era brings. From Series A, it is the kinds of the Era before. A Series A kind such as buy arrives only when its Feature ships, and the Checkout Feature itself needs research, so a Series A default of buy could never be paid.

A player cannot study Series B research before Series A's Features bring their traffic, and more page traffic never buys it. Items that teach a new kind's problem ask for that kind, so the player ships the Feature first. The Feature is the production line for that kind's Insight, and no item a Feature needs costs the kind that Feature brings.

A Venture's request mix changes which recipes are cheap. Fintech serves 4× buy, so its Series A research is fast. Every Venture serves every request kind, so every recipe can be paid.

Reliability track rule. Half of every Reliability item's cost is Failure Insight. The other half uses the item's recipe.

Items whose recipe is not the default:

Breadth. Some Observability items also need their recipe kinds sampled at a number of Component types. A trace needs more than one hop.

The rum rule reads the Ledger's breadthRegions. Each of its kinds must be sampled by an Analytics tap on a Node in two regions, so the Study stalls until a second region has its own tap.

Studies#

A Study runs one item. One Study runs at a time; the player queues up to 8, reorders them, and can switch the running Study. A switched Study keeps its progress, as in Factorio. The effect starts when the Study completes.

A Study takes its Insight as it runs, like a Factorio lab takes packs. In each Step:

Each pool pays draw(pool) times the same factor. When a pool is empty, the Study runs at the rate that pool earns, so the scarcest kind limits it. Traffic falls at night, so a buy Study slows at night. The player can start a Study with no Insight saved.

A Study stalls when a recipe pool earns nothing and holds less than the Study still draws, or when the Design samples its kinds at too few Component types. A stalled running Study holds every Study behind it. The queue row, the Insight card, and the item's card mark a stalled Study and say why: the pool that earns nothing, and the Feature that brings its kind when one does, such as Password login for login. Queueing a stalled item says the same. While the running Study is stalled, a teammate's Mail waits in Needs action with an Open Research button; its Thread resolves when the Study moves again or leaves the queue.

speed is 1, and two things raise it:

• A Spike. A Team takes the running Study as its backlog item (Team). While it does, speed × 2. A Spike whose Study is not running waits, and no Team takes it.

• Study-speed research. trace-search and notebooks add +25% each.

Studies run offline (Simulation). A postmortem's action item puts its Study first in the queue (Incidents).

Cost bands#

The ◇ column in the track tables is a Study's list price. A Study charges that price times its Era's price scale: ×2 in Seed and ×1.5 in Series A, ×1 in every other Era. The bands below are the charged range.

Track: Infrastructure#

Each option is wired to its Component (05 "Load Balancer", "CDN", "WAF", "Autoscaler", "App Server", "GPU Node"): the L4 variant, the Gateway's token bucket, Edge-side includes' 20 points of page, Bot management's half false positives, Scheduled scaling's lead on the peak, the ARM family at 0.8× the price, and the GPU's INT8/INT4 and batch sizes.

Track: Data#

With online-migrations, a migration does not hold a big table's lock (Incidents). expand-contract removes what is left of it, and outbox takes dual-write divergence out of the Search Engine's answers (Data tier).

Track: Reliability#

Four items act on incidents. With on-call the rotation answers the page. With runbooks a written runbook resolves its incident kind by itself (Incidents). With leap-smearing a clock jump does not time out a region.

bulkheads, graceful-degradation, hedged-requests and chaos-engineering each add a behavior (Components):

• bulkheads: a Link option that frees a caller's slot after 1,000 ms.

• graceful-degradation: a saturated App Server drops its dearest kinds first.

• hedged-requests: a Link races a second copy.

• chaos-engineering: scheduled experiments fail the weakest Node and pay Failure Insight.

Track: Observability#

Observability explains what each step reveals.

profiling names each Node's limiting resource and arrives with the Resources (USE) row (Observability); it carries tracing's breadth rule at 4 Component types. tail-sampling doubles Failure Insight. rum adds a device split (desktop, mobile, and tablet) to the Users row; the device shares and each one's extra round trip are the game's own stylization. anomaly-detection halves how long a threshold must hold before the pager fires, and adds a forecast line at tomorrow's peak, projected from the known diurnal cycle rather than fit from history.

Track: Performance#

Denormalization takes 30% off a read's CPU and adds 20% to a write's, Materialized views halve a report's scan, and Binary RPC halves the CPU a Node spends serialising its calls (Data tier).

Track: Runtimes#

PHP is the starting language. Each other language needs its research, and each variant needs its language (Runtimes).

Track: Frameworks#

Track: Security#

credential-protection cuts the Credential stuffing incident's weakness and its bot-login magnitude once a WAF is also in place. pen-testing reveals one weakness a calendar week: it finds the Design's highest-weakness incident kind (the same score the director weighs incidents by) and opens its prevention research as an action item, the same way a Postmortem does.

Track: Cost#

reserved-instances and spot-instances unlock the two pricing models on a compute Node from Series A (Economy). rightsizing marks a Node whose peak utilization stayed under 30% over its kept history, in the Inspector. It reads the client-side Inspector history, not a Ledger field, so it needs no save change. egress-optimization moves upload and media traffic that reaches an Object Storage Node onto an R2-priced path at $0 origin egress, lowering the Egress line by that share (Economy). unit-economics and cost-allocation split Burn by request kind and by the Service that owns each kind's code, shown in the cloud bill panel. savings-plans takes a further 20% off every compute Node's box, on top of whichever pricing model it already runs, with no per-Node commitment. These five numbers are the game's own rates.

Track: Product and business#

Each item does what its Effect column says:

• ab-testing reads a Feature's lift and its interval on the Team card, between 5% and 50% rollout (Measured lift).

• hiring-pipeline takes 30% off the time to hire.

• trunk-based raises the deploy frequency by half, on top of the policy's own cap.

• platform-team and data-team unlock their team types (Team). A Platform team runs the Clusters and halves deploy time; a Data team makes report and ai Features cost 30% less and halves a CDC pipeline's lag.

• sre-team unlocks the SRE team.

• enterprise-sales signs the SLA and its credits.

Pacing targets for the first company#

The times are measured, not targeted: the Balanced bot at the live pace (pacing model), at SIM_VERSION 17 on seeds 1 and 3, reaches each Era at the sim minutes below. The numbers are re-measured when the tuning changes.