Contagious

Podcast 2 — In conversation

Speaker A: The excitement in the room was absolutely contagious. By the end of the presentation everyone was energised.

Speaker B: Contagious excitement — the figurative use at its most vivid. The energy spreading through the room as if by contact, person to person, until everyone has caught it.

Speaker A: The child has chickenpox and is still contagious. She needs to stay home for at least five more days.

Speaker B: Contagious in the medical sense — still in the period during which the virus can be transmitted to others. The contagious period for chickenpox extends until all the blisters have crusted over.

Speaker A: His pessimism is contagious in the worst possible way. It brings the whole team down in every meeting.

Speaker B: Contagious negativity — the mirror image of contagious enthusiasm. Emotional contagion works for negative states as readily as positive ones. Research on social contagion shows that moods, behaviours, and even some conditions spread through social networks.

Speaker A: People sometimes confuse contagious and infectious.

Speaker B: Infectious means the disease can infect a host — it is caused by a pathogen that can enter and establish itself in the body. Contagious means it spreads specifically through contact — person to person. All contagious diseases are infectious, but not all infectious diseases are contagious. You can get an infectious wound from a rusty nail — that infection isn't contagious.

Speaker A: And don't confuse contagious and epidemic. An epidemic is the rapid spread of a disease through a population — it describes the scale and rate of spread. Contagious describes the mechanism: it spreads by contact. An epidemic can be driven by a contagious disease, but the epidemic is the event; contagious is the property of the pathogen that makes that event possible.

Podcast 3 — Prompt engineering

Speaker B: Scenario one — a viral coefficient prompt.

Build a contagious growth model for a product's viral loop. The model calculates the viral coefficient K, where K equals the average number of invitations sent per existing user multiplied by the conversion rate of invitations to new users. If K is greater than 1, growth is contagious — each user generates more than one new user on average, producing exponential growth. Model scenarios for different invitation rates and conversion rates and show the growth trajectory over 12 weeks for each scenario.

Speaker B: K greater than 1 as the contagious growth threshold is the product growth equivalent of an R number above 1 in epidemiology — the point at which spread becomes self-sustaining.

Speaker A: Invitation rate times conversion rate as the K formula gives the product team two separate levers — increase either and growth becomes more contagious.

Speaker B: Next — a social contagion analysis prompt.

Design a social contagion detection tool for a platform trust and safety team. The tool identifies content that is spreading in a contagious pattern: a contagious spread signature includes rapid growth in shares within the first hour, share network with low clustering (spreading to new communities rather than staying within one group), and a characteristic S-curve growth pattern. The tool flags content showing contagious spread for review, distinguishing organic contagious virality from coordinated inauthentic amplification.

Speaker A: Low clustering in the share network is the contagious spread indicator — organic virality jumps between communities; coordinated amplification stays within a cluster of coordinated accounts.

Speaker B: Right. Now a database schema.

Create a PostgreSQL schema for a disease outbreak and contagious spread tracking platform. Tables: cases, contacts, transmission_events, contagious_periods, outbreak_clusters. cases stores patient_id, diagnosis, confirmed_at, contagious_period_start, contagious_period_end, and isolation_status. transmission_events stores source_case_id, secondary_case_id, likely_transmission_date, and transmission_setting enum household, workplace, healthcare, community. contagious_periods stores case_id, is_contagious boolean, period_start, and period_end. outbreak_clusters stores cluster_id, primary_case_id, cluster_size, and cluster_setting.

Speaker B: Transmission_setting enum captures where contagious spread occurred — household transmission behaves differently from community transmission and requires different public health responses.

Speaker B: Fourth — an SIR model prompt.

Implement a basic SIR epidemiological model for a public health education platform. The model divides a population into Susceptible, Infectious, and Recovered compartments. Parameters: population size N, basic reproduction number R0 (representing how contagious the disease is — the average number of secondary cases per infectious case in a fully susceptible population), and infectious period in days. The model simulates the outbreak over time and plots: the number of susceptible, infectious, and recovered individuals each day, the peak infectious count and the day it occurs, and the final epidemic size.

Speaker A: R0 as the contagiousness parameter is the public health number that became widely known during COVID-19 — it quantifies how contagious a disease is in a single number.

Speaker B: Fifth — a feature flag contagion prompt.

Design a gradual feature rollout system modelled on contagious spread. Instead of a simple percentage rollout, the contagious rollout strategy starts with a seed group of highly connected users. When a seed user interacts with a non-seed user who is in the rollout cohort, the feature spreads to that user automatically. The rollout spreads contagiously through the user graph rather than randomly. This prioritises users most likely to benefit from network effects. Track the contagious spread map showing which users activated which others.

Speaker B: Contagious rollout through the social graph rather than random percentage is the network-effects-aware rollout — features with network value should spread along the network, not randomly across it.

Speaker B: Sixth — a full small app.

Build a single-page web app called Contagious Ideas — a team innovation tracker. Team members submit ideas. Other team members can mark an idea as catching (it has spread to them — they are now thinking about it and advocating for it). An idea's contagious score is the number of team members who have caught it, weighted by their role influence. Ideas above a contagious threshold are surfaced to leadership for consideration. The spread map shows who caught the idea from whom.

Speaker A: Spread map showing who caught the idea from whom traces the actual contagion path — revealing which team members are the most influential spreaders of new thinking.

Speaker B: That's the lesson — contagious means spread by contact. In medicine, it names the mechanism of disease transmission. In growth hacking, it names the property of a product that spreads itself through social networks. In human experience, it names the quality of enthusiasm, laughter, and energy that we most want to be around — the things worth catching.

Speaker B: Prompt example: