A first-person review of getting started with Operating Principles - 7 days in
Creating a personal OS seems too complex without a base set of operating principles to work with. So here's v1 of building operating principles for the rest of my life ahead.
For a while now, I have been trying to build a personal OS and falling short - creating a complex personal OS with multiple degree of interplay and context-switching is hard.
So here’s a re-attempt starting with building first a set of personal operating principles for now. The aim is to embrace a curated set of principles, see what works and sticks with me into helping build up my mental models of the things I do, and help me build a world model based on which I operate. The key lever is to continuously update, iterate and add/remove aspects to it, on a 14-day feedback cycle.
Since this is the v1 - the goal is to create a simple codex of operating principles from observed social effects, laws from across domains such as system design and information theory; and key observations or statements that are loosely defined, and are probably incomplete.
The effort is to apply them and evaluate if they are needle movers over the next 120 days as I practice and iterate on/with them everyday.
Note: the principles might not be in the “right” form or “original definitions” , but more as distillations of what I understand them to be.
So I’ll keep what works and prune the rest over 120 days, and hopefully have a revised set in the second week of February, 2026.
On Decision and focus
Do not fear: Action > anxiety. Default to movement.
Kidlin’s Law: Write the problem precisely; half the work is done.
Pareto Principle: 20% of inputs drive 80% of outputs. Identify the 3 highest-leverage movers and ship them first.
Falkland’s Law: If a decision isn’t required now, don’t decide now.
Hick’s Law: Fewer options → faster choices. Pre-limit menus, eliminate abundance of choices.
Inversion: Think by inversion. Avoid stupidity before seeking brilliance. Hence, first remove known and identifiable stupidity and known failure modes. Then optimize for what remains.
Second-Order Thinking: Trace consequences of consequences before acting.
Le Chatelier’s Principle: Systems in equilibria resist change. Start with nudges, not force.
On Systems and Information
Shannon’s Principle: Clarity reduces noise. But ensure that when you compress information, it does not lose its meaning. (Intent > Quantifiable Metrics). So maximize signals. Compress these signals without losing meaning. Favor intent over vanity metrics.
Chesterton’s Fence: Do not remove a system unless you understand why it was built in the first place. Don’t dismantle what you don’t yet understand yet.
Goodhart’s Law: When a measure becomes a target, it stops being a good measure. Track lead indicators, audit for gaming. (related to Shannon’s)
Base Rates > Outlier Stories: Start with priors, then update with evidence. Default to what usually happens, not to a compelling anecdote.
Small Bets: Prefer reversible, low-cost experiments to big irreversible moves.
On Networks and Value
Sutton’s Law: Go where the money or root cause is.
Metcalfe’s Law: Network value grows with the square of connections. Network utility scales ~ n². Design for density and interoperability.
Lindy Effect: The longer a thing has lasted, the longer it is likely to last. Weight proven playbooks more.
Craft and execution
Wilson’s Maxim: Compound knowledge and judgment; money follows.
Gilbert’s Law: The method is your responsibility; optimize for the desired result.
Rate × Duration: Quality is throughput over time. Ship on a schedule.
Constraint First: Identify the bottleneck and elevate it before adding resources.
Interpersonal and error-handling
Hanlon’s Razor: Don’t attribute to malice what is adequately explained by incentives or error.
Surface Area for Luck: Be willing to be wrong often, partner well, make it easy to find and help you.
Reduce Blast Radius: Contain failures, log them, write the guardrail.
Field Notes per Principle
Kidlin: Start every work block with a 3-line problem spec: state, constraint, success test.
Pareto: Daily 3×5: three needle-movers, five quick wins.
Hick: Pre-decide defaults: toolchain, KPI set, hiring bar, pricing guardrails.
Inversion: Pre-mortem: list the five most likely failure modes; design one counter for each.
Shannon: One-page brief before any project; one-page readout after.
Chesterton: Before changing a legacy process, write a paragraph on why it existed and what breaks if removed.
Goodhart: Pair every target metric with a counter-metric that catches gaming.
Metcalfe: Prefer platforms that deepen connections: APIs, standards, shared data models.
Le Chatelier: Sequence changes: observe → nudge → measure → escalate.
Gilbert: Optimize for outcome, but document the playbook to make it repeatable.
Hanlon: Escalate by data, not tone. Propose the smallest fix that could work.
Daily Loop (≤30 minutes)
Define (5m): 3-line problem spec for the day.
Select (3m): Pick the Pareto 3 and the five quick wins.
Premortem (5m): List top risks; add one guardrail each.
Ship (work).
Debrief (10m): One-page readout: what moved, what didn’t, why.
Log (7m): Update metric + counter-metric, note any Goodhart drift.
Monthly Cadence
Day 1 - Constraint Pick: Identify one bottleneck to elevate. Define a single success test and guardrail.
Day 5 - Plan Lock: Freeze the Pareto 3 for the month. Set target + counter-metric pairs.
Day 10 - Network Density: Ship one integration, one partner touchpoint, or one community artifact.
Day 15 - Midpoint Audit: Check Goodhart drift, remove one metric, one meeting, one tool.
Day 20 - Experiment Block: Run two small bets. Pre-commit stop/scale rules.
Day 25 - System Hygiene: Document deltas, retire a legacy step (only after a Chesterton note).
Day 28–30 - Lindy Review + Closeout: Keep/kill old playbooks. One-page readout: results, failures, counters. Queue next month’s constraint.
120-Day Review
Keep: Principles used ≥60% of days with measurable lift.
Modify: Principles used but neutral; rewrite into a tighter heuristic.
Drop: Principles unused or net-negative.
Add: Max 3 new principles sourced from observed wins.
End note:
Principles are tools, not beliefs. Measure, prune, replace. Nothing is sacred except outcomes. Default to action. Close the loop every day and every month.Operational checklists:
Daily (≤30 minutes)
Define: 3-line problem spec (state, constraint, success test)
Select: Pareto 3 + five quick wins
Premortem: top 3 failure modes + one guardrail each
Ship
Debrief: one-page readout
Log: target + counter-metric, note Goodhart drift
Monthly
Constraint: pick one bottleneck, set single success test
Plan lock: freeze Pareto 3 for the month
Metrics: set metric + counter-metric pairs, baseline captured
Network: 1 integration or partner artifact shipped
Experiments: 2 small bets with stop/scale rules pre-committed
Hygiene: retire one legacy step after Chesterton note
Review: Lindy check, keep/kill playbooks, one-page closeout, queue next month’s constraint
Project start (once per project)
One-page brief: objective, constraints, acceptance criteria
Interfaces: inputs/outputs, owners, SLAs, guardrails
Risks: top 5 with mitigations, rollback plan
Defaults: toolchain, naming, data model, logging
Observability: dashboards, alerts, review cadence
Postmortem (after any miss or incident)
Facts only timeline
Root causes (inverted): process, design, human, environment
Blast radius: what failed, what contained it
Fixes: smallest change that works, owner, due date
Learning: update principle, playbook, or guardrail; delete one thing
Clean Definitions for the one’s I am sure of:
Pareto Principle: A minority of inputs generate a majority of outputs.
Falkland’s Law: When no need to decide, the best decision is to delay.
Hick’s Law: Decision time increases with the number of choices.
Lindy Effect: Future life expectancy increases with current age for non-perishables.
Shannon’s Principle: Information = reduced uncertainty; clarity beats verbosity.
Chesterton’s Fence: Understand purpose before removal.
Sutton’s Law: Address the most probable cause first.
Metcalfe’s Law: Network value grows roughly with the square of user count.
Le Chatelier’s Principle: Systems counteract imposed changes.
Goodhart’s Law: Measures degrade when they become targets.
Inversion: Solve by asking “how would this fail?” and avoiding that first.
Hanlon’s Razor: Default to error/incentives over malice.