"Your Highness, the people have no bread"
Marie Antoinette: "Let them eat cake"
"Mr Millionare, small businesses are struggling to make ends meet despite 80hr work weeks."
DHH: "Let them relax by flying their private planes"
935 karma · joined November 17, 2010
Marie Antoinette: "Let them eat cake"
"Mr Millionare, small businesses are struggling to make ends meet despite 80hr work weeks."
DHH: "Let them relax by flying their private planes"
My point is that entry level employees are typically just doing what they're told to by someone considered an expert. This low level work in any field provides context for what is important to learn and why. I think it would be better to obtain this context first, and then take a step back from the day-to-day rat race to fill in the "foundational" knowledge needed to become a true expert.
College would then be like a mid-career sabbatical. When the sabbatical is over, you're ready to be in charge of the big decisions. eg, Be a carpenter for 15 years then go to architecture school.
Wouldn't all of these be better career tracks:
- Soldier in the army, then military academy, then military command.
- Work at an alderman's office, then get a degree in political science, then run for office.
- PHP developer for a marketing firm, then CS degree, then technical cofounder at a startup.
The only programs I know that capitalize on this is are some MBA programs that are geared toward middle-management types trying to get into upper management.
I wouldn't necessarily encourage you to directly sell detailed info about your users to marketers as it may very well annoy your customers, although there is probably a market for it.
At the very least, bringing in a consultant to do some data mining to find patterns that correlate to actual revenue may help you with all your other concerns.
Once you feel confident you know who is really spending money and why, an inside sales person to cultivate a list of potential customers is probably fairly cheap and may lead to a real uptick in sales. You seem uniquely situated to hire someone like that through your own service.
While writing this comment, I keep being reminded of Groupon. The last time they raised an obscene amount of money, the investors kept talking about (1) their sales army that had a relationship with thousands and thousands of small businesses and (2) sales data for all those businesses. You could read up on them to see if you get any ideas.
My bad experience came when I was the first employee (not founder) at a VC backed startup. I was originally a developer but was promoted to be the technical liason in sales. My job was to sell the incomplete product. We went back and forth between government and enterprise sales while I was there. The company is still around but is doing something completely different now.
In the interest of not burning any bridges, I'll only say that when we would bid on contracts, every vendor from big guys to the other pre-product startups were stretching the truth beyond what I consider simply being optimistic about delivery schedules and ROI.
So yes, I do know what I'm getting into. My plan this time is to build a product that has obvious value to the customer on day 1, and leave selling by 'hustle' to someone else.
I'll just continue to toil in obscurity; self-respect intact.
In other words, I wonder if these graphs are just tracking general sentiment, and would look the same for any site.
As far as I can tell, it seems that lots of people are interested in "this is where I see my niche going" posts for any industry or technology. The people who will end up at your site probably are already thinking about that niche, but they are probably your best bet for early adopters, anyway.
Maybe all that is obvious and old news. Like you, I find it hard to get excited about social media marketing so I'm just now begrudgingly experimenting with it. It's not a long term strategy, but it should be enough to build some traction.
And if you really want to spend money, a good copy editor for every word that ends up representing your product definitely gets you better copy much faster.
I had javascript off when I got there and didn't realize I was missing something until I read the parent comment.
Also - the service looks useful to someone like me who isn't much of a web designer but has a vanity site and a blog. I should say I am allergic to javascript bloat that slows down load times, so you'd need to keep speed your top priority for me to use it. I used to have adwords on one of my pages but took it off b/c it was the slowest thing on the page.
I know someone who recently interviewed with Google and he told me about the algorithms question he "got wrong." After he came up with a simple solution to a simple problem, the interviewer told him the better, googley-er algorithm, which was: a) far more complex and difficult to implement, b) had far more corner cases that would need unit tests, c) had more overhead in the expected case, but d) technically had a better big-O in the (extreme) worst case.
In other words, the interview was screening for people who have been to school but haven't ever built anything.
He writes a ton of book reviews on his blog (marginal-revolution.com), but half the time the review is "I probably won't be finishing this one."
Of course, when the prices are published things change (like if a supermarket sees that another supermarket raised their price for milk), but this type of a forum with sellers chatting about what to charge seems like a grey area.
IANAL, but please be cautious.
But Ocaml has so many features that two programmers can write in such different styles that it might as well be a different language. A team of maybe 5 people with a good attitude could probably work on the same code base. The same is true for lots of new languages like scala and clojure and even ruby.
Knowing what I know now, if there's a project that's going to have more than 10 people working on it, I'd hesitate to use anything except Java or C#.
1) Regarding the fact that at any given time, there is knowledge that people have that hasn't been encoded in a form usable by the optimizer: I think this can be addressed by generating a set of decent designs with machine learning (on the pareto front, if you will) and then providing user interface tools to allow the humans to pick the designs that best handle the knowledge that wasn't optimized against. These user interfaces will often have to be quite elaborate but that's a tractable problem.
2) When working with Genetic Algorithms, and any machine learning technology, really, my experience has been that the first results only show what is wrong with the problem setup. The designs that are returned by a genetic algorithm are invariably nonsense at first and the then it's a matter of playing whack-a-mole as the optimizer exploits inaccuracies in the problem statement, a fix is made, a new exploit is found, repeat. This is often viewed as a deficiency of genetic algorithms but in my opinion the fact that the metrics being used can be gamed is valuable information that needs to be addressed as early as possible.
Finally, I understand my original comment came across as somewhat naive. If we ever get to a point where we can design physical products, I am imagining starting with something along the lines of a mechanical pocket watch, or maybe a nice desk chair. Airplanes are gonna be last.
The problem is more about software engineering and project management, in my opinion. What would we replace CAD systems with if we could? What does the IDE look like when everyone is trying to encode their expertise in such a way that the final design is determined by a machine learning algorithm? That is, it's conceptually easy to imagine those final iterations being done by a machine learning algorithm, but how do we do that?
But in general, the problem involves doing pattern detection between possible designs and their quality metrics. When the whole thing is in software the designs can be verified ahead of time. For instance, you can create a language for designing airplane wings, and then the optimizer can generate potentially good designs, they can be verified to be manufacturable, and then they can be fed into a virtual wind tunnel to figure out if the design performs well. They can also be scored by things like weight and cost to manufacture. Let the optimizer iterate a few thousand times and you're really doing a machine learning problem where the blueprints and the quality metrics are the data set.
Many of the problems such as parts that don't fit and supply chain problems could be solved by current machine learning techniques. Too bad Google and Facebook hire all those people and sets them to work optimizing ad placement.
The clearest example is mapping a RAID server (multiple disk drives, with some technique for splitting up the data to achieve high reliability) into a contract backed by multiple cloud computing providers. A 3rd party company could sell high reliability contracts by buying up cheap low reliability contracts and applying a RAID technique.
Cloud providers and hardware companies could also look at the price curve of different types of performance/reliability contractts in long term options contracts (eg. 1 hour of 1Ghz processor delivered 18 months from today) to plan for future demand.
It's a bit dated now, but I once took a stab at writing this up when I was trying to pick a startup idea. Amazon S3 came out shortly after this was written and changed the assumptions considerably: http://bit.ly/dWIpqC
This is where I will shamelessly plug my startup, DesignByRobots. The overview of the technology is here: http://designbyrobots.com/2011/01/17/first-post/
If I was a V.C., I would dismiss any founder that answered the "what is your exit strategy?" question with anything other than a middle finger. A good V.C. would see it as the V.C.'s job to convince the founder to sell at the right time.
But regardless of the specific probabilities of any one startup getting sued, I still have a problem with a system where the government will harass you into bankruptcy on behalf of an incumbent corporation if that corporation decides they want you out of the way.
It's like a landmine in the middle of a football field. I probably won't be the one who loses a leg but it's enough of a threat to think about seeing if there's a better field to play on.
I've been working on a rather ambitious piece of software and I'm definitely worried that I'll get sued into oblivion over some minor user interface feature before I ever really make any money off it. I've lived all my life in the U.S. but would entertain the idea of leaving.
In fact if I'm going to leave my home town I feel like I might as well go someplace more exotic than Silicon Valley or New York. IP laws and other business concerns would definitely be an important criteria if I got serious about it.