I have no idea what the two authors think of each other. I don't know if they're friends, enemies, or frenemies. I don't know if they shake their fists at each other or high-five. But as a software developer, I do believe they're both worth listening to.
I've read most of the books in Martin's Clean Code series. I'm a big fan. He was one of the original signatories of the Agile Manifesto.
A recent post by Phillip Johnston, CEO of Embedded Artistry, set me off on a path reading some of Steve McConnell's books and related material. I've become a big fan of his as well.
Week before last, I read McConnell's Software Estimation: Demystifying the Black Art, 2006. Last week, I read his new book More Effective Agile: A Roadmap for Software Leaders, that just came out in August, the one I'm reviewing here.
This week, I'm reading his Code Complete: A Practical Handbook of Software Construction, 2nd edition, 2004, and Software Requirements, 3rd edition, 2013, by Karl Wiegers and Joy Beatty (or maybe over the next few weeks, since they total some 1500 pages; I note that in the Netflix documentary series "Inside Bill's Brain: Decoding Bill Gates", one of his friends says Gates reads 150 pages an hour; that's a superpower, and I am totally jealous!).
These are areas where software engineering practice has continually run into problems.
The Critical Reading List
Martin's and McConnell's new books are excellent, to the point that I can add them as the other half of this absolutely critical reading list:
- The Mythical Man-Month: Essays on Software Engineering, Anniversary Edition (2nd edition), 1995, by Frederick P. Brooks, Jr.
- Peopleware: Productive Projects and Teams, 3rd edition, 2013, by Tom DeMarco and Timothy Lister.
- Clean Agile: Back to Basics, 2019, by Robert C. Martin.
- More Effective Agile: A Roadmap for Software Leaders, 2019, by Steve McConnell.
In fact, I would be so bold as to say that not reading these once you know about them constitutes professional negligence, whether you are an engineer, a manager, or an executive. If you deal with software development in any way, producer or consumer, you must read these.
Brooks' first edition outlined the problems in software engineering in 1975. Twenty years later, his second edition showed that we were still making the same mistakes.
There are a few items that are extremely dated and quaint. Read those for their historical perspective. But don't for a moment doubt the timely relevance of the rest of the book.
Brooks is the venerated old man of this. Everybody quotes him, particularly Brooks' Law: Adding human resources to a late software project makes it later.
Every 12 years after Brooks' first edition, DeMarco and Lister addressed the theme from a different perspective in their editions of Peopleware.
There are a few items that are extremely dated and quaint. Read those for their historical perspective. But don't for a moment doubt the timely relevance of the rest of the book.
Brooks is the venerated old man of this. Everybody quotes him, particularly Brooks' Law: Adding human resources to a late software project makes it later.
Every 12 years after Brooks' first edition, DeMarco and Lister addressed the theme from a different perspective in their editions of Peopleware.
Forty-four years after, we are still making the same mistakes, just cloaked in the Agile name. So McConnell's new book addresses those issues in modern supposedly Agile organizations, with suggestions about what to do about them.
Meanwhile, Martin's book returns us to the roots of Agile, literally back to the basics to reiterate and re-emphasize them. Because many of them have been lost in what Martin Fowler calls "the Agile Industrial Complex," the industry that has grown out of promoting Agile.
Meanwhile, Martin's book returns us to the roots of Agile, literally back to the basics to reiterate and re-emphasize them. Because many of them have been lost in what Martin Fowler calls "the Agile Industrial Complex," the industry that has grown out of promoting Agile.
The first three books are easy reading. McConnell's is roughly equivalent to two of them put together. It also forms the root of a study tree of additional resources, outlining a very practical and pragmatic approach.
There are clearly some tensions and disagreements between the authors and the way things have developed. Martin goes so far as to include material with dissenting opinions in his book.
Don't just read these once. Re-read them at least once a year. Each time, different details will feel more relevant as you make progress.
Problems
But as Brooks writes, there are no silver bullets. Relying on miracles is not an effective project management technique. This is a source of no end of misery for all involved with software.
As Sandro Mancuso, author of the Clean Code series book The Software Craftsman: Professionalism, Pragmatism, Pride (Yes! Read it!) writes in chapter 7 of Clean Agile, "Craftsmanship", "the original Agile ideas got distorted and simplified, arriving at companies as the promise of a process to deliver software faster." I.e. miracles.
A Pet Peeve (Insert Rant Here)
Ok, now that I have all that off my chest, on to the actual reviews.
Clean Agile, Robert C. Martin
Martin's premise is that Agile has gotten muddled. He says it has gotten blurred through misinterpretation and usurpation.
His purpose is to set the record straight, "to be as pragmatic as possible, describing Agile without nonsense and in no uncertain terms."
He starts out with the history of Agile, how it came about, and provides an overview of what it does. He then goes on to cover the reasons for using it, the business practices, the team practices, the technical practices, and becoming Agile.
An important concept is the Iron Cross of project management: good, fast, cheap, done: pick any three. He says that in reality, each of these four attributes have coefficients, and good management is about managing those coefficients rather than demanding they all be at %100; that is the kind of management Agile strives to enable, by providing data.
The next concept is Ron Jeffries' Circle of Life: the diagram decribing the practices of XP (eXtreme Programming). Martin chose XP for this book because he says it is the best defined, the most complete, and the least muddled of the Agile processes. He references Kent Beck's Extreme Programming Explained: Embrace Change (he prefers the original 2000 edition; my copy is due to arrive week after next).
The enumeration and description of the various practices surprised me, reinforcing his point that things have gotten muddled. While I was aware of them, I was not aware of their original meanings and intent.
The most mind-blowing moment was reading about acceptance tests, under the business practices. Acceptance tests have become a real hand-waver, "one of the least understood, least used, and most confused of all the Agile practices."
But as he describes them, they have the power to be amazing:
Martin has been talking about this for a while. He gave the talk in this video, Robert C. Martin - The Land that Scrum Forgot, at a 2011 conference (very watchable at 2x speed). The main gist is that Scrum covered the Agile management practices, but left out the Agile technical practices, yet they are fundamental to making the methodology succeed.
These are the XP practices:
There are clearly some tensions and disagreements between the authors and the way things have developed. Martin goes so far as to include material with dissenting opinions in his book.
Don't just read these once. Re-read them at least once a year. Each time, different details will feel more relevant as you make progress.
Problems
The problems in the industry that have persisted for decades can be summarized as late projects, over budget, and poor software that doesn't do what it's supposed to do or just plain doesn't work.
Tied up in this are many details. Poor understanding and management of requirements, woefully underestimated work, poor understanding of hidden complexities, poor testing, poor people management.
Much of it is the result of applying the Taylor Scientific Management method to software development. Taylorism may work for a predictable production line of well-defined inputs, steps, and outputs, running at a repeatable rate, but it is a terrible model for software management. Software development is not a production line. There are far too many unknowns.
In general, most problems arise because companies practice the IMH software project management method: Insert Miracle Here. With Agile, they have adopted the IAMH variant: Insert Agile Miracle Here.
Tied up in this are many details. Poor understanding and management of requirements, woefully underestimated work, poor understanding of hidden complexities, poor testing, poor people management.
Much of it is the result of applying the Taylor Scientific Management method to software development. Taylorism may work for a predictable production line of well-defined inputs, steps, and outputs, running at a repeatable rate, but it is a terrible model for software management. Software development is not a production line. There are far too many unknowns.
In general, most problems arise because companies practice the IMH software project management method: Insert Miracle Here. With Agile, they have adopted the IAMH variant: Insert Agile Miracle Here.
But as Brooks writes, there are no silver bullets. Relying on miracles is not an effective project management technique. This is a source of no end of misery for all involved with software.
As Sandro Mancuso, author of the Clean Code series book The Software Craftsman: Professionalism, Pragmatism, Pride (Yes! Read it!) writes in chapter 7 of Clean Agile, "Craftsmanship", "the original Agile ideas got distorted and simplified, arriving at companies as the promise of a process to deliver software faster." I.e. miracles.
A Pet Peeve (Insert Rant Here)
One of the areas of disagreement between various authors is the open-plan office. The original Agile concept was co-locating team members so that they could communicate immediately, directly, and informally, at higher bandwidth than through emails or heavy formal documents. It was meant to foster collaboration and remove impediments to effective communication.
Peopleware is extremely critical of the open-plan office, and I couldn't agree more. The prevailing implementation of it is clearly based more on the idea of cutting real-estate and office overhead costs than on encouraging productive communication. The result has all the charm of a cattle concentration feedlot, everyone getting their four square feet to exist in.
Another distortion of the Agile concepts embraced by management at the cost of actual effective development. That might make the CFO happy, but it's a false economy that should horrify the CTO.
Those capex savings can incur significant non-recurring engineering costs and create technical problems that will incur further downstream development and support costs. And that just means more opex for facilities where the engineering gets done, because the project takes longer.
You're paying me all this money to be productive and concentrate on complex problems, then you deliberately destroy my concentration to save on furniture and floorspace? It's like a real-life version of Kurt Vonnegut's short story Harrison Bergeron. What does that do to the product design and quality? What customer problems does it create, with attendant opportunity costs?
I turned down an excellent job offer in 2012 after the on-site interviews because of this. I was bludgeoned by my impression of the office environment: sweatshop. They probably thought of me as a prima donna.
McConnell also recommends against this, referencing the 2018 article It's Official: Open-Plan Offices Are Now the Dumbest Management Fad of All Time, which summarized the findings of a Harvard study on the topic. The practice appears to me to be the office-space equivalent of Taylorism.
Peopleware is extremely critical of the open-plan office, and I couldn't agree more. The prevailing implementation of it is clearly based more on the idea of cutting real-estate and office overhead costs than on encouraging productive communication. The result has all the charm of a cattle concentration feedlot, everyone getting their four square feet to exist in.
Another distortion of the Agile concepts embraced by management at the cost of actual effective development. That might make the CFO happy, but it's a false economy that should horrify the CTO.
Those capex savings can incur significant non-recurring engineering costs and create technical problems that will incur further downstream development and support costs. And that just means more opex for facilities where the engineering gets done, because the project takes longer.
You're paying me all this money to be productive and concentrate on complex problems, then you deliberately destroy my concentration to save on furniture and floorspace? It's like a real-life version of Kurt Vonnegut's short story Harrison Bergeron. What does that do to the product design and quality? What customer problems does it create, with attendant opportunity costs?
I turned down an excellent job offer in 2012 after the on-site interviews because of this. I was bludgeoned by my impression of the office environment: sweatshop. They probably thought of me as a prima donna.
McConnell also recommends against this, referencing the 2018 article It's Official: Open-Plan Offices Are Now the Dumbest Management Fad of All Time, which summarized the findings of a Harvard study on the topic. The practice appears to me to be the office-space equivalent of Taylorism.
Ok, now that I have all that off my chest, on to the actual reviews.
Martin's premise is that Agile has gotten muddled. He says it has gotten blurred through misinterpretation and usurpation.
His purpose is to set the record straight, "to be as pragmatic as possible, describing Agile without nonsense and in no uncertain terms."
He starts out with the history of Agile, how it came about, and provides an overview of what it does. He then goes on to cover the reasons for using it, the business practices, the team practices, the technical practices, and becoming Agile.
An important concept is the Iron Cross of project management: good, fast, cheap, done: pick any three. He says that in reality, each of these four attributes have coefficients, and good management is about managing those coefficients rather than demanding they all be at %100; that is the kind of management Agile strives to enable, by providing data.
The next concept is Ron Jeffries' Circle of Life: the diagram decribing the practices of XP (eXtreme Programming). Martin chose XP for this book because he says it is the best defined, the most complete, and the least muddled of the Agile processes. He references Kent Beck's Extreme Programming Explained: Embrace Change (he prefers the original 2000 edition; my copy is due to arrive week after next).
The enumeration and description of the various practices surprised me, reinforcing his point that things have gotten muddled. While I was aware of them, I was not aware of their original meanings and intent.
The most mind-blowing moment was reading about acceptance tests, under the business practices. Acceptance tests have become a real hand-waver, "one of the least understood, least used, and most confused of all the Agile practices."
But as he describes them, they have the power to be amazing:
- The business analysts specify the happy paths.
- QA writes the tests for those cases early in the sprint, along with the unhappy paths (QA engineer walks into a bar; orders a beer; orders 9999 beers; orders NaN beers; orders a soda for Little Bobby Tables; etc.). Because you want your QA people to be devious and creative in showing how your code can be abused, so that you can prevent anyone else from doing it. You want Machiavelli running your QA group.
- The tests define the targets that developers need to hit.
- Developers work on their code, running the tests repeatedly, until the code passes them.
Holy crap! Holy crap! This ties actual business-defined requirements end-to-end through to the running code. It is a fractal-zoom-out-one-level application of Test Driven Development (and we all thought TDD was just for the developer-written unit tests!).
It completely changes the QA model. Then the unit and acceptance tests get incorporated into Continuous Build, under the team practices.
There are other important business practices that I believe are poorly understood, such as splitting and spikes. Splitting means splitting a complex story into smaller stories, as long as you maintain the INVEST guidelines:
- Independent
- Negotiable
- Valuable
- Estimable
- Small
- Testable
Splitting is important when you realize a story is more complex than originally thought, a common problem. Rather than trying to beat it into submission (or be beaten into submission by the attempt), break it apart and expose the complexity in manageable chunks.
I never knew just what a spike was. It's a meta-story, a story for estimating a story. It's called that because it's a long, thin slice through all the layers of the system. When you don't know how to estimate a story, you create a spike for the sole purpose of figuring that out.
Almost as mind-blowing is his discussion of the technical practices. Mind-blowing because much of this whole area has been all but ignored by most Agile implementations. Reintroducing them is one of the strengths of this book.
Martin has been talking about this for a while. He gave the talk in this video, Robert C. Martin - The Land that Scrum Forgot, at a 2011 conference (very watchable at 2x speed). The main gist is that Scrum covered the Agile management practices, but left out the Agile technical practices, yet they are fundamental to making the methodology succeed.
These are the XP practices:
- Test-Driven Development (TDD), the double-entry bookkeeping of software development.
- Refactoring.
- Simple Design.
- Pair Programming.
Of these, I would say TDD is perhaps the most-practiced. But all of these have been largely relegated to a dismissive labeling as something only the extremos do. Refactoring is seen as something you do separately when things get so bad that you're forced into it. Pair programming in particular is viewed as a non-starter.
I got my Scrum training in a group class taught by Jeff Sutherland, so pretty much from the horse's mouth. That was 5 years ago, so my memory is a bit faded, but I don't remember any of these practices being covered. I learned about sprints and stories and points, but not about these.
As Martin describes them, they are the individual daily practices that developers should incorporate into every story as they do them. Every story makes use of them in real-time, not in some kind of separate step.
TDD follows the outline I listed in Review: Test Driven Development for Embedded C, James W. Grenning.
Refactoring builds on the TDD cycle, recognizing that writing code that works is a separate dimension from writing code that is clean:
- Create a test that fails.
- Make the test pass.
- Clean up the code.
- Return to step 1.
Simple Design means "writing only the code that is required with a structure that keeps it simplest, smallest, and most expressive." It follows Kent Beck's rules:
- Pass all the tests.
- Reveal the intent (i.e. readability).
- Remove duplication.
- Decrease elements.
Pair programming is the one people find most radical and alarming. But as Martin points out, it's not an all-the-time 100% thing. It's an on-demand, as-needed practice that can take a variety of forms as the situation requires.
Who hasn't asked a coworker to look over some code with them to figure something out? Now expand that concept. It's the power of two-heads-are-better-than-one. Maybe trading the keyboard back and forth, maybe one person driving while the other talks. Sharing information, knowledge, and ideas in both directions, as well as reviewing code in real-time. There's some bang for the buck!
The final chapters cover becoming Agile, including some of the danger areas that get in the way, tools, coaching (pro and con), and Mancuso's chapter on craftsmanship, which reminds us that we do this kind of work because we love it. We are constantly striving to be better at it. I am a software developer. I want to be professional about it. This hearkens back to the roots of Agile.
More Effective Agile, Steve McConnell
McConnell has a very direct, pragmatic writing style. He is brutally honest about what works and what doesn't, and the practical realities and difficulties that organizations run into.
His main goal is addressing practical topics that businesses care about, but that are often neglected by Agile purists:
- Common challenges in Agile implementation.
- How to implement Agile in only part of the organization (because virtually every company will have parts that simply don't work that way, or will interact with external entities that don't).
- Agile's support for predictability.
- Use of Agile on geographically distributed teams
- Using Agile in regulated industries.
- Using Agile on a variety of different types of software projects.
- INTRODUCTION TO MORE EFFECTIVE AGILE
- MORE EFFECTIVE TEAMS
- MORE EFFECTIVE WORK
- MORE EFFECTIVE ORGANIZATIONS
It includes full bibliography and index.
Throughout, he uses the key principle of "Inspect and Adapt": inspect your organization for particular attributes, then adapt your process as necessary to improve those attributes.
Throughout, he uses the key principle of "Inspect and Adapt": inspect your organization for particular attributes, then adapt your process as necessary to improve those attributes.
Another important concept is that Agile is not one monolithic model that works identically for all organizations. It's not one-size-fits-all, because the full range of software projects covers a variety of situations. So the book covers the various ways organizations can tailor the practices to their needs. Probably to the horror of Agile purists.
Each chapter is organized as follows:
- Discussion of key principles and details that support them. This includes problem areas and various options for dealing with them.
- Suggested Leadership Actions
- Additional Resources
The Suggested Leadership Actions are divided into recommended Inspect and Adapt lists. The Inspect items are specific things to examine in your organization. I suspect they would reveal some rude surprises. The Adapt items cover actions to take based on the issues revealed by inspection.
The Additional Resources list additional reading if you need to delve further into the topics covered.
One of the very useful concepts in the book is the "Agile Boundary". This draws the line between the portion of the organization that uses Agile techniques, and the portion that doesn't. Even if the software process is 100% Agile, the rest of the company may not be.
Misunderstanding the boundary can cause a variety of problems. But understanding it creates opportunities for selecting an appropriate set of practices. This is helpful for ensuring successful Agile implementation across a diverse range of projects.
A significant topic of discussion is the tension between "pure Agile" and the more Sequential methods that might be appropriate for a given organization at a given point in a project.
The Agile Boundary defines the interface where the methods meet, and which methods are appropriate on each side of it under given circumstances. Again, Agile is not a single monolithic method that can be applied identically to every single project. As he says, it's not a matter of "go full Agile or go home".
There's a lot of information to digest here, because it all needs to be taken in the context of your specific environment. The chapters that stand out to me based on my personal experience:
One of the very useful concepts in the book is the "Agile Boundary". This draws the line between the portion of the organization that uses Agile techniques, and the portion that doesn't. Even if the software process is 100% Agile, the rest of the company may not be.
Misunderstanding the boundary can cause a variety of problems. But understanding it creates opportunities for selecting an appropriate set of practices. This is helpful for ensuring successful Agile implementation across a diverse range of projects.
A significant topic of discussion is the tension between "pure Agile" and the more Sequential methods that might be appropriate for a given organization at a given point in a project.
The Agile Boundary defines the interface where the methods meet, and which methods are appropriate on each side of it under given circumstances. Again, Agile is not a single monolithic method that can be applied identically to every single project. As he says, it's not a matter of "go full Agile or go home".
There's a lot of information to digest here, because it all needs to be taken in the context of your specific environment. The chapters that stand out to me based on my personal experience:
- More Effective Agile Projects: keeping projects small and sprints short; using velocity-based planning (which means you need accurate velocity measurement), delivering in vertical slices, and managing technical debt; and structuring work to avoid burnout.
- More Effective Agile Quality: minimizing the defect creation gap (i.e. finding and removing defects quickly, before they get out); creating and using a definition of done (DoD); maintaining a releasable level of quality at all times; reducing rework, which is typically not well accounted for.
- More Effective Agile Testing: using automated tests created by the development team, including unit and acceptance tests, and monitoring code coverage.
- More Effective Agile Requirements Creation: stories, product backlog, refining the backlog, creating and using a definition of ready (DoR).
- More Effective Agile Requirements Prioritization: having an effective product owner, classifying stories by combined business value and development cost.
- More Effective Agile Predictability: strict and loose predictability of cost, schedule, and feature set; dealing with the Agile Boundary.
- More Effective Agile Adoptions.
Requirements make an interesting area, because that is often a source of problems. The Agile approach is to elicit just enough requirements up front to be able to size a story, then rely on more detailed elicitation and emergent design when working on the story.
But the problem I've seen with that is one of the classic issues in estimation. Management tends to treat those very rough initial estimates as commitments, not taking into account the fact that further refinement has been deferred. So downstream dependent commitments get made based on them.
The risk comes when further examination of the story reveals that there is more work hidden underneath than originally believed. I've seen this repeatedly. Then the whole chain of dependent commitments gets disrupted, creating chaos as the organization tries to cope.
For example, consumer-product embedded systems are very sensitive to this. The downstream dependent commitments involve hardware manufacturing and the retail pipeline, where products need to be pre-positioned to prepare for major sales cycles such as holidays.
The Christmas sales period means consumer products need to be in warehouses by mid-November at the latest. Both the hardware manufacturing facilities (and their supply chains) and the sales channels are Taylor-style systems, relying on bulk delivery and just-in-time techniques. They need predictability. That's your Agile Boundary right there, on two sides of the software project.
IOT products have fallen into the habit of relying on a day 1 OTA update after the consumer unboxes them, but that's risky. If the massive high-scale OTA of all the fielded devices runs into problems, it creates havoc for consumers, who are not going to be happy. That can have significant opportunity costs if it causes stalled revenue or returns, or some horribly expensive solution to work around a failed OTA, not to mention the reputation effect on future sales.
What about commercial/industrial embedded systems? Cars, planes, factory equipment, where sales, installation, and operation are dependent on having the software ready. These can have huge ripple effects.
Online portal rollouts that gate real-world services are also sensitive to it. Martin uses the example of healthcare.gov. People need to have used the system successfully by a certain date in order to access real-world services, with life-safety consequences.
Both of these highlight the real-world deadlines that make business sense for picking software schedule dates. As software engineers, we can't just whine about arbitrary, unreasonable dates. There's a whole chain of dependencies that needs to be managed.
Schedule issues need to be surfaced and addressed as soon as possible, just like software bugs. The later in the process a software bug is identified, the more expensive it is to fix, sometimes by orders of magnitude. Dealing with schedule bugs is no different.
For example, consumer-product embedded systems are very sensitive to this. The downstream dependent commitments involve hardware manufacturing and the retail pipeline, where products need to be pre-positioned to prepare for major sales cycles such as holidays.
The Christmas sales period means consumer products need to be in warehouses by mid-November at the latest. Both the hardware manufacturing facilities (and their supply chains) and the sales channels are Taylor-style systems, relying on bulk delivery and just-in-time techniques. They need predictability. That's your Agile Boundary right there, on two sides of the software project.
IOT products have fallen into the habit of relying on a day 1 OTA update after the consumer unboxes them, but that's risky. If the massive high-scale OTA of all the fielded devices runs into problems, it creates havoc for consumers, who are not going to be happy. That can have significant opportunity costs if it causes stalled revenue or returns, or some horribly expensive solution to work around a failed OTA, not to mention the reputation effect on future sales.
What about commercial/industrial embedded systems? Cars, planes, factory equipment, where sales, installation, and operation are dependent on having the software ready. These can have huge ripple effects.
Online portal rollouts that gate real-world services are also sensitive to it. Martin uses the example of healthcare.gov. People need to have used the system successfully by a certain date in order to access real-world services, with life-safety consequences.
Both of these highlight the real-world deadlines that make business sense for picking software schedule dates. As software engineers, we can't just whine about arbitrary, unreasonable dates. There's a whole chain of dependencies that needs to be managed.
Schedule issues need to be surfaced and addressed as soon as possible, just like software bugs. The later in the process a software bug is identified, the more expensive it is to fix, sometimes by orders of magnitude. Dealing with schedule bugs is no different.
In his book on estimation, McConnell talks about the Cone of Uncertainty, the greater uncertainty about estimates early in the project, that narrows to better certainty over time as more information is available. Absolute certainty only comes after the completion. But everybody behaves as if the certainty is much better much earlier.
It's clear from the variety of information in this book that Agile is not simply a template that can be laid down across any organization and be successful. It takes work to adapt it to the realities of each organization. There is no simple recipe for success. No silver bullets.
That's why it's necessary to re-read this periodically, because each time you'll be viewing it in the context of your organization's current realities. That's continuing the Inspect and Adapt concept.
Update Nov 10, 2019
My copy of Beck's Extreme Programming Explained arrived yesterday, and I've been reading through it. Here we see the benefits of going back to original sources, in this case on open plan offices. In Chapter 13, "Facilities Strategy", he says:
So it appears what caught on was the group open bullpen part, and what has been left out was the personal space part (and it's attendant value).
There's a continuous spectrum on which to interpret Beck's recommendation, with the typical modern open office representing one end (all open space, no private space), and individual offices representing the other (no open space, all private space).
There's a point on the spectrum where I would shift to liking it, if I had a private place to make my own where I could concentrate in relative quiet, with enough space to bring in a pairing partner.
Where I find the open office breaks down is the overall noise level from multiple separate conversations. It can be a near-constant distraction when I'm trying to work (hence the rampant proliferation of headphones in open offices).
Meanwhile, when I need to have a conversation with someone, I want to be able to do it without competing with all those others, and without disturbing those around me.
What seems to me to have the most practical benefit is optimizing space for two-person interactions, acoustically isolated from other two-person interactions. So individual workspaces with room for two to work together. That allows for individual time as well as the pairing method, from simple rubber-duck debugging to full keyboard and mouse back-and-forth.
Those are both high-value, high-quality times. That's the real value proposition for the company.
And in fact, that's precisely the kind of setup Beck says Ward Cunningham told him about.
Given that most developers now work on dedicated individual machines, through which they might be accessing virtualized cloud computing resources, the argument for a centralized bullpen with machines seems less compelling.
The open bullpen space seems to be less optimal, but still useful for times when more than two people might be involved.
This is clearly a philosophical difference from Beck's intent, but I think the costs of open plan offices as he experienced them, tempered by the reality of how they've been adopted, outweigh their benefits.
Meanwhile, his followup discussion in that chapter is fully in harmony with Peopleware's Part II: "The Office Environment".
Update Nov 10, 2019
My copy of Beck's Extreme Programming Explained arrived yesterday, and I've been reading through it. Here we see the benefits of going back to original sources, in this case on open plan offices. In Chapter 13, "Facilities Strategy", he says:
The best setup is an open bullpen, with little cubbies around the outside of the space. The team members can keep their personal items in these cubbies, go to them to make phone calls, and spend time at them when they don't want to be interrupted. The rest of the team needs to respect the "virtual" privacy of someone sitting in their cubby. Put the biggest, fastest development machines on tables in the middle of the space (cubbies might or might not contain machines).
There's a continuous spectrum on which to interpret Beck's recommendation, with the typical modern open office representing one end (all open space, no private space), and individual offices representing the other (no open space, all private space).
There's a point on the spectrum where I would shift to liking it, if I had a private place to make my own where I could concentrate in relative quiet, with enough space to bring in a pairing partner.
Where I find the open office breaks down is the overall noise level from multiple separate conversations. It can be a near-constant distraction when I'm trying to work (hence the rampant proliferation of headphones in open offices).
Meanwhile, when I need to have a conversation with someone, I want to be able to do it without competing with all those others, and without disturbing those around me.
What seems to me to have the most practical benefit is optimizing space for two-person interactions, acoustically isolated from other two-person interactions. So individual workspaces with room for two to work together. That allows for individual time as well as the pairing method, from simple rubber-duck debugging to full keyboard and mouse back-and-forth.
Those are both high-value, high-quality times. That's the real value proposition for the company.
And in fact, that's precisely the kind of setup Beck says Ward Cunningham told him about.
Given that most developers now work on dedicated individual machines, through which they might be accessing virtualized cloud computing resources, the argument for a centralized bullpen with machines seems less compelling.
The open bullpen space seems to be less optimal, but still useful for times when more than two people might be involved.
This is clearly a philosophical difference from Beck's intent, but I think the costs of open plan offices as he experienced them, tempered by the reality of how they've been adopted, outweigh their benefits.
Meanwhile, his followup discussion in that chapter is fully in harmony with Peopleware's Part II: "The Office Environment".
