David Weinberger's presentation in Disorder: Feature or Bug? at Supernova 2007 was like watching a great rock singer deliver a passionate performance you just know is destined to be a classic. How good was it? The IRC channel went dead. That's the conference equivalent of everybody waving their lighters in the air. Um. Well, you just had to be there. I can't find a video. Anybody have a bootleg?
Anyway. David's now posted a new essay well worth reading, Delamination Now!. Also, well worth acting on. Money quote: "[T]he carriers are playing us like a violin."
Monday, July 9, 2007
Sunday, July 8, 2007
There she blows! (The Moby Dick Theory of Big Companies)
Having spent some time in the belly of the whale[1], I can testify that the decision making process of a large company is indeed a chaotic system even when seen from the inside. The variables that control decisions are very well hidden.
The Pmarca Guide to Startups, part 5: The Moby Dick theory of big companies
[1] In the same whale as pmarca in fact, though in a somewhat different location along the alimentary tract.
The Pmarca Guide to Startups, part 5: The Moby Dick theory of big companies
[1] In the same whale as pmarca in fact, though in a somewhat different location along the alimentary tract.
Saturday, July 7, 2007
35 views of social networking
35 Perspectives on Online Social Networking: One fewer view than Hokusai's Mt. Fuji series. Just as much diversity.Friday, July 6, 2007
A FULL INTERACTIVE SHELL!
iPhone SERIAL HACKED, FULL INTERACTIVE SHELL:
IT GIVES YOU A FULL INTERACTIVE SHELLNice.
I REPEAT, A FULL INTERACTIVE SHELL
Thursday, July 5, 2007
Fireworks, Social Compacts, and Emergent Order
Yesterday the family went to see the 4th of July fireworks just outside the Google campus, in Charleston park. Great park, lots of friendly helpful people, the kid had a blast running in the water fountain, and he saw his first fireworks show. It was great!Then, we left (quickly, to avoid the crowds) and immediately got snarled in traffic. Of course everyone was leaving at the same time so we expected it to be slow, but we were literally not moving for a quarter of an hour. After a while we figured out that we couldn't move because other cars kept joining the queue ahead of us from other parking lots. Around this time, other people started figuring this out too and started going through those same parking lots to jump ahead. This solution to the prisoner's dilemma took about 30 minutes to really begin to cascade: Everyone else began to drive through parking lots, under police tape, on the wrong side of the road, cutting ahead wherever they could to avoid being the sucker stuck at the end of the never-moving priority queue. (Full disclosure: I drove across a parking lot to get over to the main road where traffic was moving, but violated no traffic laws.)
I wonder how the results would have been different if the people involved could communicate efficiently instead of being trapped incommunicado in their cars. I bet every single car had at least one cell phone in it, many with GPS. Imagine an ad hoc network based on cell phones and GPS, communicating about traffic flow -- nothing more complicated than speed plus location and direction, and maybe a "don't head this way" alert. It'd be interesting to try.
Sunday, July 1, 2007
Theory P or theory D?
Which
theory fits the evidence (Raganwald):
Theory P adherents believe that there are lies, damned lies, and software development estimates. ... Theory P adherents believe that the most important element of successful software development is learning.
Maybe I'm an extreme P adherent; I say that learning is everything in software development. The results of this learning are captured in code where possible, human minds where not. Absolutely everything else associated with software development can and will be automated away.
Finally:
To date, Theory P is the clear winner on the evidence, and it’s not even close. Like any reasonable theory, it explains what we have observed to date and makes predictions that are tested empirically every day.
Theory D, on the other hand, is the overwhelming winner in the marketplace, and again it’s not even close. The vast majority of software development projects are managed according to Theory D, with large, heavyweight investments in design and planning in advance, very little tolerance for deviation from the plan, and a belief that good planning can make up for poor execution by contributors.
Does Theory D reflect reality? From the perspective of effective software development, I do not believe so. However, from the perspective of organizational culture, theory D is reality, and you ignore it at your peril.
So this is a clear contradiction. Why is it that theory D is so successful (at replicating itself if nothing else) while theory P languishes (at replicating)? Perhaps D offers clear benefits to its adherents within large organizations -- status, power, large reporting trees... and thus P can't gain a foothold despite offering clear organization-level benefits.
But I suspect that it's simpler than that; I think that people simply don't really evaluate history or data objectively. Also, it may be difficult for people without the technical background to really how difficult some problems are; past a certain level of functionality, it's all equally magic. The size of the team that accomplished a task then becomes a proxy for its level of difficulty, in the way that high prices become a proxy for the quality of a product in the marketplace for the majority of consumers. So small teams, by this measure, must not be accomplishing much, and if they do, it's a fluke that can be explained away in hindsight with a bit of work.
Somebody should do a dissertation on this...
Theory P adherents believe that there are lies, damned lies, and software development estimates. ... Theory P adherents believe that the most important element of successful software development is learning.
Maybe I'm an extreme P adherent; I say that learning is everything in software development. The results of this learning are captured in code where possible, human minds where not. Absolutely everything else associated with software development can and will be automated away.
Finally:
To date, Theory P is the clear winner on the evidence, and it’s not even close. Like any reasonable theory, it explains what we have observed to date and makes predictions that are tested empirically every day.
Theory D, on the other hand, is the overwhelming winner in the marketplace, and again it’s not even close. The vast majority of software development projects are managed according to Theory D, with large, heavyweight investments in design and planning in advance, very little tolerance for deviation from the plan, and a belief that good planning can make up for poor execution by contributors.
Does Theory D reflect reality? From the perspective of effective software development, I do not believe so. However, from the perspective of organizational culture, theory D is reality, and you ignore it at your peril.
So this is a clear contradiction. Why is it that theory D is so successful (at replicating itself if nothing else) while theory P languishes (at replicating)? Perhaps D offers clear benefits to its adherents within large organizations -- status, power, large reporting trees... and thus P can't gain a foothold despite offering clear organization-level benefits.
But I suspect that it's simpler than that; I think that people simply don't really evaluate history or data objectively. Also, it may be difficult for people without the technical background to really how difficult some problems are; past a certain level of functionality, it's all equally magic. The size of the team that accomplished a task then becomes a proxy for its level of difficulty, in the way that high prices become a proxy for the quality of a product in the marketplace for the majority of consumers. So small teams, by this measure, must not be accomplishing much, and if they do, it's a fluke that can be explained away in hindsight with a bit of work.
Somebody should do a dissertation on this...
Theory P or Theory D?
Which theory fits the evidence (Raganwald):
Theory P adherents believe that there are lies, damned lies, and software development estimates. ... Theory P adherents believe that the most important element of successful software development is learning.
Maybe I'm an extreme P adherent; I say that learning is everything in software development. The results of this learning are captured in code where possible, human minds where not. Absolutely everything else associated with software development can and will be automated away.
Finally:
To date, Theory P is the clear winner on the evidence, and it’s not even close. Like any reasonable theory, it explains what we have observed to date and makes predictions that are tested empirically every day.
Theory D, on the other hand, is the overwhelming winner in the marketplace, and again it’s not even close. The vast majority of software development projects are managed according to Theory D, with large, heavyweight investments in design and planning in advance, very little tolerance for deviation from the plan, and a belief that good planning can make up for poor execution by contributors.
Does Theory D reflect reality? From the perspective of effective software development, I do not believe so. However, from the perspective of organizational culture, theory D is reality, and you ignore it at your peril.
So this is a clear contradiction. Why is it that theory D is so successful (at replicating itself if nothing else) while theory P languishes (at replicating)? Perhaps D offers clear benefits to its adherents within large organizations -- status, power, large reporting trees... and thus P can't gain a foothold despite offering clear organization-level benefits.
But I suspect that it's simpler than that; I think that people simply don't really evaluate history or data objectively. Also, it may be difficult for people without the technical background to really how difficult some problems are; past a certain level of functionality, it's all equally magic. The size of the team that accomplished a task then becomes a proxy for its level of difficulty, in the way that high prices become a proxy for the quality of a product in the marketplace for the majority of consumers. So small teams, by this measure, must not be accomplishing much, and if they do, it's a fluke that can be explained away in hindsight with a bit of work.
Somebody should do a dissertation on this...
Theory P adherents believe that there are lies, damned lies, and software development estimates. ... Theory P adherents believe that the most important element of successful software development is learning.
Maybe I'm an extreme P adherent; I say that learning is everything in software development. The results of this learning are captured in code where possible, human minds where not. Absolutely everything else associated with software development can and will be automated away.
Finally:
To date, Theory P is the clear winner on the evidence, and it’s not even close. Like any reasonable theory, it explains what we have observed to date and makes predictions that are tested empirically every day.
Theory D, on the other hand, is the overwhelming winner in the marketplace, and again it’s not even close. The vast majority of software development projects are managed according to Theory D, with large, heavyweight investments in design and planning in advance, very little tolerance for deviation from the plan, and a belief that good planning can make up for poor execution by contributors.
Does Theory D reflect reality? From the perspective of effective software development, I do not believe so. However, from the perspective of organizational culture, theory D is reality, and you ignore it at your peril.
So this is a clear contradiction. Why is it that theory D is so successful (at replicating itself if nothing else) while theory P languishes (at replicating)? Perhaps D offers clear benefits to its adherents within large organizations -- status, power, large reporting trees... and thus P can't gain a foothold despite offering clear organization-level benefits.
But I suspect that it's simpler than that; I think that people simply don't really evaluate history or data objectively. Also, it may be difficult for people without the technical background to really how difficult some problems are; past a certain level of functionality, it's all equally magic. The size of the team that accomplished a task then becomes a proxy for its level of difficulty, in the way that high prices become a proxy for the quality of a product in the marketplace for the majority of consumers. So small teams, by this measure, must not be accomplishing much, and if they do, it's a fluke that can be explained away in hindsight with a bit of work.
Somebody should do a dissertation on this...
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