Control vs data planes

I recently became aware of a helpful dichotomy: control vs data plane. The former governs how the latter should be delivered.

I believe these terms come from the world of networking, but they’re now entering the world of application engineering via DevOps.

For example, I work on a product that delivers targeted configuration to apps. In this context, the targeting logic is the control plane, and the resulting configuration is the data plane. For contrast, the RESTful perspective would describe both as resources.

In this context, I can see if other patterns might apply. In particular, the best-practice of a declarative control plane has been helpful lately. As Azure’s introduction to Infrastructure as Code states, the goal is to specify “what an environment requires and not necessarily the how.” Collocating control with code simplifies reasoning and minimizes the cost of switching between application and infrastructure logic, similar to the benefits of collocating documentation with code.

“Beautiful Future: How Deschutes Uses Artificial Intelligence & Machine Learning to Brew Better Beer”

Craft Beer and Brewing’s article “Beautiful Future: How Deschutes Uses Artificial Intelligence & Machine Learning to Brew Better Beer” describes an intuitive application of ML. Deschutes brewery wanted to more accurately predict when a given fermentation process would complete. The problem statement is simple:

Produce the same amount of beer in less time, while maintaining or improving the quality of the beer along the way, and you’ll have more resources for the intentional play that leads to new beers that drinkers love.

I like the explicit recognition that reducing toil frees time for more valuable activities. This is reiterated later:

Most beer consumers aren’t concerned with how efficiently or cost-effectively a brewery makes their beer—they want high-quality beer, and they want new and exciting beers.

Fermentation sounds like a relatively simple curve to plot. It’s easy to imagine manually monitoring something like sugar content vs time, and then using that data to train a model.

Brewers now trust automation to act on the predictions:

Today, cellar operators at Deschutes have such a high level of confidence in the algorithm that they typically allow the software to trigger next steps in the brewing process.

The automation is also easy to imagine. Deschutes’ Brewery Pi project targets Raspberry Pi, which I can see being used to drive hardware to adjust temperature, add nutrients, drain a fermentation vessel, etc. I really like how Deschutes made the code open-source 🍻

PlayFab’s LiveOps guide

My experience is largely in features and infrastructure for growing and retaining users, aka “growth”. Recently, I learned the games industry has a comparable concept “LiveOps”. I’ve found value in using the latter to learn more about the space in general.

PlayFab has an excellent guide to LiveOps. The guide is a brief and accessible reference, so I’ll just jot notes below.


The guide summarizes LiveOps as “Games are shifting from one-off experiences to services that evolve. Developers of successful live games focus on understanding their players, meeting their individual needs, and cultivating long-term relationships”

In growth-speak, I’d phrase this as analytics, personalization and retention. There is some direct association with growth: “We’re investing in games that people play for longer and engage with much more deeply … to drive growth …“

I guess the “live” in LiveOps refers to “services that evolve”: “… live services

represented nearly 58% of Electronic Arts’ net revenue …” I can see how this would be a big shift from encoding all logic in a released binary. “save client updates for entirely new features or large assets”

“With a LiveOps game, the real work starts with launch instead of ending there” I think there’s less of a distinction in a non-game app; most apps already pull content from a network.

A summary of LiveOps features:

  • “server-side configurations …”
  • “… content data untethered from client versions …”
  • “… in-depth analytics”

“Content data” refers to “… new experiences and content, thereby extending the lifetime of our games“, which explains the claim that LiveOps can reduce up-front investment.

“… the ‘live’ part of LiveOps goes through three post-launch stages:

  1. Iterating your Game …
  2. Personalizing the Player Experience …
  3. Managing the Community …”

I think all of these apply to apps in general.

I like how the breakdown also indicates infra and talent required in each step:

  1. Iteration requires “build, test-and-deploy pipeline, basic analytics, and content configurations“
  2. Personalization requires “data analysts and product managers to use more sophisticated tools such as recommendation systems and live events managers“
  3. Community management requires “customer support staff, marketing, and community managers … guild systems, user-generated content, and multiplayer services for matchmaking, cross-network play, and communications.”

The guide presents these as sequential steps of maturity. In my experience with growth, 1 and 3 came before 2, since generating per-user state was relatively resource intensive. Also, we could start with relatively naive approaches to 2 and 3, eg friend recommendations by a static topic like “sports”, and then layer on more sophisticated alternatives, eg per-user behavioral predictions.

Connecting to people

LiveOps has a user-centric perspective: “LiveOps developers know that players and communities evolve. When creating a game, we’re not movie directors with a singular vision, but more like TV network program managers … LiveOps games are player-centric and react to player desires and needs …”

I’m a fan of a customer-centric perspective. Differentiating user-centric seems like it should be obvious, but it’s nice to see it emphasized.

My recent experience is in growth as a service, which is why I differentiate “users” from “customers” (Customers would be apps that have users/players.)


“With LiveOps, acquisition is an ongoing process” I guess this recognizes that people may come and go from a game, although in the terminology I’m familiar with, returning would be “resurrection” or “reactivation”. (“Reactivation” is listed later as an example of acquisition.)

I appreciate the list of common acquisition sources:

  • Store discovery
  • Public relations
  • Advertising
  • Cross-promotion
  • Influencer marketing
  • Social installs, eg shares
  • Reactivation

Helpful tip: “Track player engagement and retention based on source of acquisition and look for trends” Platforms providing acquisition channels should also provide attribution, eg Google Play Store’s campaign attribution passed to Android’s Install Referrer API.

Kind of obvious, but the guide recommends A/B testing reactivation inducements. Later the guide simply recommends testing everything all the time.


Retention is “one of the only data-supported ways to know if players enjoy playing“

Common techniques for increasing retention:

  • Adding content
  • Stickiness due to investment – this comes up later in the “conversion” section
  • Social connections
  • Compelling game mechanics, eg Go has “simple rules that allow for endless new strategies”

Helpful tip: “Try to communicate only what’s interesting and valuable, and mix up rewards so they don’t become background noise” I’ve heard this phrased as “fatigue” Messaging platforms should provide features to help customers avoid fatiguing users.


The definition of “engagement” or “active” usage is often mysterious to me, so I appreciate the general description: “Active communities engage with a game by playing, providing feedback, and promoting (discussing online or in person, creating fan content, and so on) … Common reporting period intervals include 1-day, 7-day, and 30-day.” An arbitrary post from SurveyMonkey has some context for MAU.

Interesting: “engagement is the only KPI that some studios measure.“

Another relatively obvious tip: “Look at how studios with games like yours engage their community as a baseline for your own engagement efforts”, ie “competitive analysis”. But still, as a general primer, I appreciate the comprehensiveness.


“Your team needs the tools to isolate and identify problems, fix or escalate them … and communicate with players throughout the process.” 👍

Common tools:

  • External-facing ticketing, so internal and external actors can coordinate
  • “ ability to look up individual player profiles and make manual changes”. Ideally, a customer can do this themselves.
  • “A way to suspend or ban players”
  • “A way for players to upload crash logs” Seems this could be automatic, eg Crashlytics
  • “Ways to send messages to players” (and customers)

Good tip: “Changes in support contact and resolution rates (e.g. number of support tickets opened and closed) can indicate larger issues.”



I like the list of common metrics:

  • ARPU (Average Revenue Per User) … general business health“. I’m guessing percentiles would be good too
  • ARPPU (Average Revenue Per Paying User) … for gauging monetization strategies, such as store design or DLC“
  • (from the monetization section) “Paying rate is just as important as ARPPU for measuring monetization” I get the impression paying rate refers to the percentage of users who pay for anything
  • Unique Logins …  indicates newly acquired players”
  • Conversion Rate … success at converting free players into paid players.”
  • Retention … how well your game keeps players interested”
  • Average Session Length … how long your gameplay loop stays fun”
  • Session Frequency … how often players engage with the game”
  • LTV (Lifetime Value) … the total number of unique players divided by total revenue generated”
  • Errors … how stable your game is”
  • Content Logs … popularity, stability, and engagement of specific game content” This seems relatively game-specific, but I guess it could be generalized to feature-specific metrics

Good point: “Some metrics are best reviewed over long periods of time (e.g. Avg. Revenue), while others benefit from constant real-time updates (e.g. Errors)” And this may change over time, eg crash rates while changing a flag value.

Interesting: “Instead of boosting acquisition through marketing or app store advertising, they built traction by focusing on early retention metrics such as daily active users, session length, and crashes“ and “direct player feedback”

Good idea: “implementing direct player feedback through a public Trello community board,  letting users log bugs directly, and holding community votes on what to work on next.“

Good point: “Knowing your retention rate is important, but offers no insight on how to fix it. For that, you need to do a deep drill-down or segment your audience and experiment.”


“Segmenting groups is a necessary step to deliver the best content to the most players”

Good tip: “your analytics toolset should let you define custom segments”

Common use-cases:

  • “Designers segment players based on in-game behavior to understand their needs and develop player-centric content” presumably to increase retention
  • “Monetization teams use segments to understand spending patterns, identify fraudulent behavior, and predict revenue”
  • “Marketers create custom segments and optimize messaging for each to acquire or engage players”

“The most important thing about the testing aspect is the cohort and the segmentation …” 🤔 I guess an example would be identifying a low spending segment to test a feature to increase spending, as opposed to testing it on everyone, some of whom may already by spending a max.

A basic funnel:

  • New users
  • Non-spenders
  • Spenders
  • High spenders

“Once you [define a funnel like this], it’s easy to track your progress getting players to move through the funnel from one segment to the next.”

Good tip: “machine learning can help you automatically segment players”


“Good experiments have a hypothesis or some sort of goal KPI to change” 👍

I’m glad this is stated: “The size of your audience can affect how complex your testing can be. A game with millions of players can easily test subtle changes, but one with a smaller audience will only get significant data from tests with stark variations. The same goes for how many tests you can run simultaneously—a smaller player base means fewer simultaneous tests are statistically reliable.” I’d also say an opinionated approach, direct feedback and/or severely limited test concurrency can be a more efficient guide for a small user base than cluttering code with conditional logic and waiting a long time for significant data. Nice: “monitor user feedback … when player data is in short supply.”

Good tip: “be sure the test encompasses at least a whole week to measure fluctuations between weekday and weekend players” and users in different regions.

Interesting: “Make sure if one player sees something different from another, they can clearly understand why” I wonder if an example would be providing UI to list active experiments.

In-game surveys should “only ask one question at a time”

“Failed experiments are an important part of the process to learn” 👍

Best practices:

  • “Learn which metrics best capture performance for your game’s KPIs,and set appropriate periods to monitor and review them”
  • “Test gameplay mechanics early. It’s harder to test changes … after players have developed expectations” Reminds me of changes to Twitter UX basics, like changing the ⭐️ → ❤️
  • “When players have problems, analyze event history …” which implies an ability to collect and analyze such history is important, which may not be obvious before an issue happens
  • “Use limited-time events to test changes to gameplay—players are often more tolerant of gameplay changes when called out as events” Good idea. Reminds me of sports-based features, eg World Cup. I hadn’t thought of them as an opportunity to experiment w basic mechanics.
  • “Chart out the “funnel” progression for players in your game and experiment with ways to motivate players to move through your funnel”
  • “Ensure your analytics tools let you view KPIs by segment”
  • “Establish a clear success metric to gauge the impact of tests”
  • “Test qualitative factors by polling players with in-game surveys”


“It helps to put together a designated LiveOps team” I’ve also seen feature teams own their launches.

This seems like a launch checklist:

  1. Feedback loop and KPIs
  2. Support channels and data access guidelines
  3. Incident response strategy

Soft launch

Example soft launch: “choose a smaller geographic area, ideally with the same language as your core audience … and run your game for a few months” or “ limiting your initial audience with an Early Access or Beta period”. EAP and beta are something I have more experience with.

Good idea: “pay close attention to the core engagement metrics” for soft launch

Good idea: “During soft launch, confirm that you can update the game without causing disruption to players – and make sure that you can roll back changes if problems arise during deployment”, ie verify LiveOps infra works as expected.

“Many developers are moving away from soft launches in favor of lean launches“ 🤔… “As a small, indie studio, you don’t have the money to do user acquisition for a soft launch”

Lean launch

A lean launch:

  1. deploys an MVP version of the game
  2. connects with a target audience, and then 
  3. tunes the game based on player data and feedback


  • reliable data pipeline
  • smaller manageable audience without inflated expectations
  • be able to adapt your game quickly

“Collecting and analyzing your crash data and retention metrics is a must”, which is “ dependent on an effective LiveOps pipeline that allows for developing several pieces of content at once, and agile deployment”

Best practices

  • “Assemble a LiveOps team”
  • “Develop a calendar” to coordinate live updates post-launch
  • “Put validation checks in place” I guess because this approach is premised on making lots of significant changes, so the cost of failure is high
  • “Rehearse key LiveOps tasks”, which is good advice, but kind of contradicts an earlier statement “There’s no such thing as a dry run in live games”
  • “Ensure your team has a way to roll back changes ”
  • “Set roles and permissions”

Game updates

“Game updates aren’t limited to new levels or game mechanics. They can consist of new items for purchase, events, balance patches, bundles, or anything else that encourages a player to come back and play more.”

“Understanding your player base is a key element in designing and delivering relevant updates”

“Frequency and consistency are as important as quality when making updates”

Tip: experiment with time between updates in addition to the update content “to see if they impact engagement or retention.”

“save client updates for entirely new features or large assets … assets such as art and gameplay logic are included in the client, but how those assets are displayed to players is driven by server-side logic … plan your content architecture in advance and move as much of your game logic as possible onto the server or cloud.”

Best practices

  • “Make a list of everything in your game that could be considered ‘content’”
  • Plan how content will get to the client 👈
  • “Think about offline mode” 👍
  • “Vary your updates” between temporary and permanent changes
  • “Consider targeting new content to specific player segments”
  • “Consider cloud streaming or downloading assets in the background during gameplay to reduce friction”


“A live event is any temporary but meaningful change to a game’s content”

“Anything can be an event … Timebox it, reward it, there you go …”

“Successful events often include:

  • A measurable goal …
  • A limited-time period …
  • Engaging themes and content …
  • Surprise and predictability …
  • A sense of community effort …
  • An effective means of communicating with players …”

Reminds me of a “campaign” in other applications of targeted content.

Experiment w event frequency: “ By experimenting with event timing, they were able to settle on an event schedule that raised their baseline engagement while also minimizing lapsed players”

“Consider running repeatable events … Holidays work because players will be more understanding of temporary changes, and often have more time to play”

“Adding a special, limited-time leaderboard for a specific in-game goal is a common event.”

“Events can also run in parallel”


A calendar can help reduce the complexity of orchestrating events and avoid fatiguing users.


“Great player communication is critical to the success of live events”

Push notifications, email and social media are common channels of event communication.

Best practices

  • “Make a list of everything you might want to change as part of an event”
  • “Prepare to run events from the server, without a client update”
  • “Find natural ways to promote upcoming events in-game”
  • “Capture event data in your data warehouse“ for later analysis and segmentation
  • “Let your team be flexible when creating events” This seems like basic team management; micro-managing is bad
  • “Set goals for events” so we can evaluate performance
  • Maintain a calendar for coordination and to avoid fatiguing users
  • “Use events to experiment with ideas”
  • “Establish an event framework” that separates unique and repeatable aspects of an event


“… every discussion about monetization should consider:

  • The kind of game you’re building …
  • … [aligning] player needs with your revenue goals …
  • Ethical guidelines for monetization …
  • How your competition is monetizing … “


Aka “in app purchases” 👈

Common forms:

  • “Cosmetics are items that affect the physical appearance …”
  • “Account Upgrades are permanent enhancements to a player account …”
  • “Consumables are items that can be used once for a temporary effect …”
  • “VIP Programs are subscription-based programs …”
  • Content Access
  • “Random Boxes (or loot boxes) are items players can purchase without knowing exactly what they’ll receive”

Common “elements of in-game store management:

  • Presentation … should be easy to use …
  • Catalog management … (A good rule of thumb is once a week.) …
  • Pricing …
  • Offers and promotions …
  • Fraud … As soon as you start offering items with real-world currency value, there will be fraud …”

Nice: “Use server-side receipt validation … for added security”


I really like this topic. From the growth perspective, this is part of acquisition.

“two main challenges:

  1. eliminating the barriers to entry
  2. showing your players value”

The first one I’ve come to see a fundamental product consideration. If we want people to do anything, we need to minimize the cost of doing that thing. I think this also ties into an engineering best-practice: keep migrations and changes separate.

Regarding the second point, I think a great counter-example is a paywall before showing any content. “players have more of a propensity to pay once they have a trust

relationship with the game and the developer”

How players spend

I don’t have experience with in-app purchases, so this is all interesting.

“Players will have different levels of spending they are comfortable with”

“It’s easy to get caught up focusing on big spenders or trying to sell as much as possible as soon as the game launches. But those methods are often unreliable,

unsustainable, and may reflect poorly on your studio” Reminds me of low-quality ads, which eventually drive users off the platform.

“Build a broader, more reliable, and engaged spending base rather than chasing whales’ … A thousand players paying $10 is preferable to ten players paying $1000 because there is more opportunity for repeat purchases.”


“One of the most popular forms is rewarded video—short videos often promoting a different game or app, watched for an in-game reward or more playtime … [beware] players might be lured away by a competitor’s game.”

“As with almost every other LiveOps effort, you need to continuously test different solutions.”

Good idea: ”Many developers segment their audience and only show ads to certain segments, often limiting them to non-paying players.”


“You can usually do an on-the-fly calculation to compare the value per impression of an in-house-ad versus one from an external network, so you can decide what to show for a given player segment.”


“Many games use two virtual currencies: a “soft” currency earned ingame, and a “hard” purchased currency”

“Build a matrix of all the sources and sinks for in-game resources and build a model of the economic activity you can adjust in a tool such as Microsoft Excel, without rolling out updates.” I’ve heard of managing config this way.

“What we want is sustained investment and signs that a player has really perceived value…”

Best practices

  • Chose a strategy
  • Set ethical and quality guidelines
  • Prevent fraud
  • Simplicity and variety
  • Bundle commonly purchased items
  • Pair sales with events ← this reminds me of the growth practice of requesting feedback when engagement is high
  • Incentivize social sharing
  • Diversify ad networks
  • Keep loss aversion in mind
  • Always be testing “Never stop testing your monetization efforts, because your players’ perception of value (both real-world and in-game) will change over time“


“… detailed documentation on multiplayer architecture at”


“As soon as you add a leaderboard in a game, even if it’s a single-player game, players start seeing progress against other people, and people all of a sudden start engaging more” Makes me think there are mechanics for games based on human behavior comparable those used by growth features. For example, leaderboards increasing engagement highlights a human response to hierarchy.

Filtering makes leaderboards more fun:

  • Geo
  • Platform
  • Mode, eg player-vs-player
  • Option, eg difficulty
  • Level
  • Statistic, eg # wins
  • Time, eg stats for today

“combining the variables Platform, Level, and Statistic you could create a leaderboard for ‘Fastest time (Statistic) to complete Ventura Highway (Level) by PC players (Platform).’”

Leaderboards can also encourage social behavior, eg biggest contributor to team

An ability to reset the leaderboard can encourage participation

Award prizes based on achievements shown in the leaderboard.


“Groups … can get players more invested in a game”

Some group dynamics:

  • Communication
  • Game progress
  • Stats 

I wonder if these can be used for other groups, eg a working group.

Interesting: “Determine how short-term groups are formed based on how much players need to trust teammates to succeed … “

“Long-term groups (such as guilds) have been proven to increase player retention …” Seems like a form of “investment” that makes an app stickier. The fact that it was “proven” makes me think there might be papers to read.

“… how do I provide you the best experience not only within your guild, but when your guild is gone… It comes down to matchmaking … the right aspiration together as a group.” Reminds me of work dynamics.

Managing communities

“A dedicated community manager can help keep players satisfied and foster a positive community …” Reminds me of the dev “advocate” role

Some ways to avoid bad behavior:

  • Limiting communication options
  • Filtering words and phrases
  • Defining a code of conduct

“The team behind Guild Wars 2 reportedly built the whole game around the idea that ‘players should always be happy to see one another.’” 🙂

“The more you can provide a framework for people to operate in, the more likely they are …“


“50% or more of online users will only buy when presented offers in their native language.”

Good idea: given the localization team access to edit strings

“Store as much of the in-game text on the server as possible, so it can be easily edited and localized”

Best practices

  • Consider multiplayer early in development
  • Add multiplayer elements whenever possible
  • Experiment with matchmaking algorithms
  • Plan for multiplayer scaling needs
  • Offer multiple ways to communicate
  • Enable customization of groups, to increase engagement
  • Reset leaderboards on a regular basis
  • Award prizes based on leaderboard stats
  • Enable users to “refresh” game to explicitly load new config
  • Localize communications(!) 

Tools and services

The guide lists PlayFab’s API, but I think it’s more interesting as an overview of useful entities and controls:

  • Auth
  • Content
    • Game content
    • User generated content
  • User data
  • Matchmaking
  • Leaderboards
    • Tournaments
    • Reset schedules
    • Prizes
    • Fraud prevention
  • Communication
    • P2p
    • Text and voice with transcription and translation
    • Accessibility (speech to text and vice versa)
  • Eng controls
    • Config
    • Reporting
    • Events
    • Automation
    • Scheduling
  • Product & community controls
    • Reporting
    • Event log
    • User management
    • Automation
    • Scheduling
    • Segmentation
    • Experimentation
    • Messaging
  • Economics controls
    • Stores
    • Sales
    • Economy
    • Fraud prevention

Software ecology

A documentary about an eco-friendly home near Austin inspired me to think about software systems from an ecological perspective.

The notion of a software or product “ecosystem” isn’t new, but I’d previously only thought about it as fostering healthy interactions in a system; I hadn’t considered the non-human actors. Is the code hard to maintain? Are alerts waking people up unnecessarily? Is the business sustainable? Is there a natural order? Is anything out of place, like an old tire in a stream? Can we achieve our goals in harmony with the natural order?

For example, I worked on a free service that would alert when resources were exhausted. Because it was free, it was natural for consumers deprioritize efficient usage. Maintainers of the service absorbed the cost in the form of routine alerts. A more balanced system would shift some cost to the consumers.

I think the idea of separating concerns is another example. Decoupling can reduce maintenance cost even if the functionality doesn’t change.

A colleague once remarked that every syntax variation allowed by a language would eventually appear in a code base; a convention could not stop this. Perhaps this was another example of an imbalanced natural order. The cost of enforcement was solely on the reviewer. Shifting this cost to programmatic validation, like a linter, would help restore balance.

Architecture for Light

The Illuminating Engineering Society has a couple interviews with Kim and Paul Mercier, authors of a book called Architecture for Light. The content is fascinating, touching on anthropology, physics, engineering, design and their professional experience, but a few things stood out to me in particular as overlapping with software engineering:

  1. The role of people
  2. Efficiency
  3. Multi-disciplinary planning


Perhaps the connection to people is more immediate in the field of lighting design than software engineering, but the two have a couple things in common that can negatively affect usability: creative purity and cost efficiency.

In software and architecture, we can design something that’s aesthetically pure, but difficult to incorporate or maintain.

One of the best tools I’ve found in project management is a focus on the customer. This can help us prioritize and avoid ethical pitfalls.

Related, healthy organizations recognize software is built by people, and people thrive in a nurturing environment. For example, Google’s research indicated psychological safety correlated strongly with high-performing teams.


The Merciers describe an approach to lighting that minimizes electrical usage and maximizes sales, but focusing light on products. (A common alternative is to uniformly light a space.)

They mentioned the most cost-effective solution is to turn the lights off. This reminds me of a balance in software engineering: we need to maintain everything we build, so not building minimizes maintenance cost. A similar balance comes up in SRE: we can maximize stability by minimizing changes. Obviously, doing nothing has other costs, but having all options on the table opens up opportunities, such as only invest light where a customer’s attention produces value.

The Merciers propose a method that maximizes efficiency and usability. This was an amazing observation: not too long ago, daylight was the most efficient light source; it’s still very efficient, but we need to rediscover the skills to use it.

Multi-disciplinary planning

The Merciers recommend including lighting designers from the “imagination” phase of a project rather than pulling them in later. Lighting designers can then advise on structural changes to maximize lighting efficiency. They describe the opposite as an anti-pattern: bringing specialists in late to fix problems.

This reminds me of a tension when organizing software development teams: a “waterfall” model where each specialty contributes in sequence, versus an “agile” model where teams are composed of cross-functional members.

They describe several examples in their interview, but one reminded me of complex workarounds that can arise in software: a building design that let in too much daylight. They observed a small overhang would be ideal, but because the design was already finalized the building had to be outfitted with a mechanical shade.

Dave Chang interviews Preet Bharara

Dave Chang, chef and restaurateur, interviewed Preet Bharara, former US attorney for the Southern District of New York on June 20th, 2019. Their discussion focused largely on professional development and management and identified commonalities in their respective professions. I too identified commonalities with my experience in software development, so I wanted to take some notes for future reference. I tried to clearly quote and paraphrase, but this isn’t intended to be a transcript. I summarize, merge, reorder and comment on the thoughts.

Bharara’s book Doing Justice was the inspiration for the interview. Chang’s recommended it to many of his managers. He found the process by which Bharara approached criminal justice was the same as for being a chef. Bharara clarifies the book was intended for anyone, at any level of an organization, and is about how to approach problems in general.

The book has a chapter on asking questions. Junior and senior members of an organization need to feel safe asking questions. Chang comments that not asking questions is how we start making mistakes.

Innovation is important, but isn’t always dramatic. Innovation can take the form of thinking about a problem differently, and come from anyone at any level of an organization. It’s important to cultivate a “culture of innovation”. It’s insufficient to have a couple innovative people. Management must respect innovation.

This ties back to asking questions; it’s important to understand and question the rationale behind the status quo. Doing things one way because that’s the way they’ve always been done is insufficient. For example, until recently no one thought to use wire-tapping for inside trading investigations, even though insider trading is an act of communication.

Bharara describes the slow pace of change in government and how we have to work around that. His was the first US attorney’s office to contract with a data analysis firm, and the first to have a twitter account. He describes people looking at him like had three heads, which I find validating; I’ve felt insecure before expressing an unorthodox view.

At one point, Bharara recognized he understood law well enough, but had no training in business management. Two things are important for institutions: continuity and change. We want continuity of values and a culture of innovation.

People don’t like change. The legal and culinary professions are especially averse to change. Chang describes chefs dismissing advanced cooking techniques: “I don’t need to learn anything. I have fire. I have chicken.”

Chang wrote down a line from the book: “There are people who fight for the status quo and reject change.” (Aside, this fits the Economist’s definition of “conservatism”, so there’s a positive side of this too.)

How do you change an organization to be more open to innovation? It may be sufficient to identify and support a minority who embrace the concept. Bharara comments: “Not everyone is going to be a leader. You want to have more leaders than the average organization, but a lot of people are going to be followers.” Chang asks: “Can you be effective at your job as a follower?” Bharara clarifies a distinction between innovation and execution. Both are valuable. Some people are better at one or the other. Few are good at both.

Different people have different skills. As we ascend higher in an organization, people become more specialized. Any one person may be better than average in any role, but the difference between the best team and the worst team is how closely people’s skills are aligned with their roles.

Chang asks Bharara if he was successful at identifying people’s skills in his first management job as US attorney. He responds: the most important part of being a leader, because one person can’t do everything, is identifying who the best people are and putting them where they belong. He consulted a lot. He also saw value in a balance of, say, aggressive and cautious, people on a team.

Promotion isn’t always a good idea. Different levels require different skills. Bharara’s unaware of any manager who doesn’t have a record of significant personnel mistakes. Chang comments this is exactly the case in the culinary industry too. Traditionally, people are promoted in a kitchen based on excellence at one level, but that is not an indicator of excellence at the next level. Bharara agrees and describes law offices as typically having poor management because there are no business people involved. Management and individual contribution are completely different skills and have a completely different reward structure. For example, no US attorney has tried a case in recent history because they’re busy managing. Bharara codified this by prohibiting leads from participating directly in cases describing that as an “indulgence” for a manager.

Self-awareness is important in this context. It’s beneficial for people to recognize whether they want to manage other people. Bharara would ask people seeking promotion “Are you sure you want that?” He continues: “Some people are so ambitious they think that there’s a natural progression to their career that must include certain kinds of promotion … I wish more people thought about their own fun and ability rather than always being on this rat race to have another item to put on their resume.”

Chang acknowledges the same is true in the kitchen. As an executive chef, he no longer cooks. Bharara talks about his difficulty describing his job, but it boils down to “meetings”. Leaders oversee and are the outward face of an organization. Bharara paraphrases Pat Fitzgerald, a former US attorney: when you have the right people, who know what they’re doing, the job of the leader is to get out of the way and let them do it, and when they’re not doing it, to steer them.

Likewise, folks in leadership should be aware of their skills, roles and the fact they are often not the best choice for direct execution. “If you want something done well, you have to do it yourself” is an anti-pattern in this context. Chang describes chefs taking direct control in times of stress, but because they’re not involved in the day-to-day production of the kitchen, this is often disastrous: “You’re going to ruin the flow of the kitchen through entirely one’s own ego.”

Bharara describes two motivations for this:

  1. leadership thinks “I could do this better”
  2. leadership is trying to demonstrate they add value

Chang describes a risk at the upper limit of ability: the person eventually creates something only they can maintain, or they run the organization in a way that only works for them. Both are bad for the organization. Part of Chang’s job is to shake them out of it.

Chang asks how do people adapt to loss of control and recognition they’re not the best at everything. Humility is helpful. People presume the head of the office is the best at everything. Bharara describes having “warring self-doubt”, which was validating for me to hear. He also describes being very nervous about starting a new stage in his career when he created his podcast. Consulting with experts is essential. The difference between good and great is consultation.

Talent is often the greatest obstacle to becoming a great chef. At some point, talent is no longer the most important factor to success. Chang’s describes telling talented people they need to grow up. I wonder if he’s talking about a threshold between individual contribution and management, and if this is in conflict with the earlier discussion about self-awareness.

The interview closes with discussion of making decisions under stress. Chang jokes that every day in a restaurant is like defusing a bomb. Bharara describes the tension between imminent danger and sufficient evidence. I suppose the general theme is problem solving under pressure.

Another general theme is how to prepare for the unknown. Judgement is as important as education and credentials. Bharara comments there are lots of intelligent people he wouldn’t put in charge of anything; some folks are much more comfortable with contemplation over a long period of time. Bharara describes the importance of core values in these moments. For SDNY, the mission is: “Do the right thing in the right way for the right reasons every day and that’s all.” He paraphrases To Kill A Mockingbird: trying to do the right thing, is the right thing.

Good behavior is important for effective management. Fear, intimidation and perfectionism doesn’t work in the real world. Bharara paraphrases Eisenhower: hitting people over the head is assault, not leadership. Empathy, respect and even temperament are much better. Chang acknowledges that’s a lot to ask of someone who just wanted be a cook.

Bharara states one of his goals is to never let people you lead see you freak out. He freaks out with his closest deputies, but the organization as a whole benefits from calm leadership.