# Catalysts > Identify and deploy small interventions that lower activation energy for desired change without being consumed - accelerate reactions that would happen anyway - Skill: `lev-os/catalysts` (Agent Skill) - Install (CLI): `npx skillmds@latest add lev-os/catalysts` - Raw SKILL.md: https://api.skillmd.com/api/skills/lev-os/catalysts/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: DevOps & Infra - Author: lev-os (https://skillmd.com/u/lev-os) - Updated: 2026-09-10 - Page: https://skillmd.com/skills/lev-os/catalysts --- # Catalysts ## Overview Catalysts, from chemistry, are substances that accelerate reactions by lowering activation energy (the initial energy barrier required for change) without being consumed in the process. A catalyst provides an alternative pathway with a lower energy threshold, making reactions that were theoretically possible become practically feasible. As a mental model, catalysts reveal how strategic small interventions can unlock disproportionate change by reducing friction, providing initial momentum, or creating enabling conditions - critically, the catalyst itself isn't the fuel (it doesn't create new capacity) but rather the spark that makes existing potential kinetic. Applied beyond chemistry, catalysts explain why well-timed small investments (infrastructure, tools, introductions, policies) can unleash exponential value, while massive investments without catalytic design produce linear results. The catalyst's power is in efficiency: same outcome, less energy required. ## When to Use - Change initiatives stalled despite clear benefits (high activation energy problem) - Resource-constrained situations requiring force multiplication - Designing incentive systems, tools, or processes to accelerate adoption - Identifying why some small interventions create outsized impact (catalytic design) - Removing friction from customer journeys, employee workflows, or partnerships - Evaluating whether to invest in enabling infrastructure vs. direct execution ## The Process ### Step 1: Diagnose the Activation Energy Barrier Identify what prevents a beneficial change from happening spontaneously. What's the initial energy/effort/risk/friction that blocks action, even when people want the outcome? **Common activation energy barriers:** - **Coordination cost:** Everyone benefits from change, but no one wants to organize it - **Initial setup effort:** Switching tools/processes requires painful migration period - **Information gap:** People don't know how to start (procedural friction) - **Risk perception:** First-movers bear uncertainty that later adopters avoid - **Social proof:** No one wants to be first, but everyone would join second **Example:** Team wants to document processes, but writing first doc feels like huge lift. Activation energy = starting from blank page. ### Step 2: Design the Catalytic Intervention Find the minimal intervention that lowers activation energy without replacing the underlying process. The catalyst makes change easier, not unnecessary. **Catalyst characteristics:** - Small relative to the reaction it enables (10x return on effort) - Reusable across multiple instances (template, tool, introduction) - Removes initial friction but doesn't do the work - Not consumed (one investment unlocks many uses) **Example catalysts:** - **Documentation:** Pre-built templates + first example � Lowers "blank page" barrier - **Network effects:** First 100 users recruited manually � Enables viral growth - **Infrastructure:** CI/CD pipeline setup � Unlocks 10x faster deployments - **Introductions:** Connect two people who should collaborate � They handle the rest ### Step 3: Validate Catalytic vs. Non-Catalytic Investment Test whether your intervention is truly catalytic (accelerates inevitable change) or compensatory (replaces underlying capacity). Catalysts enable self-sustaining reactions; non-catalysts require continuous energy. **Catalytic test questions:** - If we remove this after 3 months, does the reaction continue? (Catalyst = yes) - Does this unlock existing capacity or create new capacity from scratch? (Catalyst = unlock) - Does the benefit scale beyond the initial investment? (Catalyst = scales) **Example:** - **Catalytic:** Building developer platform/APIs � Others build on top indefinitely - **Non-catalytic:** Hiring more customer support � Stops when you stop hiring ### Step 4: Deploy Catalysts at Tipping Points Timing matters - catalysts are most effective when the underlying reaction is ready but stalled. Too early, and you're pushing against systemic barriers. Too late, and activation energy was already overcome. **Optimal catalyst timing:** - Desire for change exists but execution hasn't started - Experiments are happening ad-hoc; catalyst would standardize and accelerate - Network effects or compounding are possible but need initial critical mass **Example:** GitHub launched when developers wanted to share code (desire existed) but setup was painful (activation barrier). Git existed (underlying capacity), GitHub made it frictionless (catalyst). ## Example Application **Situation:** Software company struggling with 6-month sales cycles - prospects interested but require custom demos before committing. **Application:** - **Activation barrier diagnosis:** Every prospect needs custom demo (20+ hours sales engineering time per deal). First demo = huge lift. - **Catalytic intervention:** Build interactive self-serve demo environment + 5 pre-configured industry use cases. Prospects explore independently. - **Investment:** 2 engineers � 4 weeks = 320 hours one-time - **Catalytic return:** Eliminates 20 hours � 50 prospects/year = 1,000 hours saved annually. Demo environment reused indefinitely (not consumed). **Outcome:** Sales cycle dropped from 6 months to 3 months. Conversion rate increased 40% (prospects who self-demo are more qualified). Catalyst unlocked latent demand without scaling sales team linearly. ## Example Application 2 **Situation:** Open source project with high interest but low contributions - 10,000 stars, 12 active contributors. **Application:** - **Activation barrier:** New contributors don't know where to start. Code is complex, documentation assumes expertise. - **Catalytic interventions:** - Label 50 issues "good first issue" with detailed context (lowers "where to start" barrier) - Create contribution guide with setup walkthrough (lowers technical setup barrier) - Assign maintainer to mentor first 10 contributors (lowers social/approval barrier) - **Investment:** 1 maintainer � 20 hours total **Outcome:** Contributors increased from 12 to 87 within 6 months. "Good first issue" label alone drove 40+ first-time PRs. Catalyst wasn't writing the code (non-catalytic) - it was removing friction that prevented existing interest from converting to action. ## Anti-Patterns - L Confusing catalysts with fuel (catalyst enables, doesn't replace underlying work) - L Deploying catalysts when no underlying desire/capacity exists (pushing rope) - L Building "catalysts" that require continuous maintenance (defeats reusability principle) - L Over-engineering the catalyst (should be minimal intervention for activation energy reduction) - L Assuming all small interventions are catalytic (many are just small non-catalytic investments) - L Timing catalysts poorly - too early (no latent reaction) or too late (already activated) ## Related - activation-energy (the barrier catalysts reduce) - leverage-points (catalysts are often high-leverage interventions) - network-effects (catalysts can trigger network effect tipping points) - compounding-effects (catalytic investments compound by enabling repeated use) - critical-mass (catalysts help reach critical mass for self-sustaining reactions)