Responses to Cutter Consortium's E-Business and Technology survey indicate that the number and size of e-projects are growing rapidly; the average duration was 11 months, and typical staffing levels were 20-40.

Forget most of the hype you've read or heard about intelligent robots and artificial intelligence (AI) since the release of Steven Spielberg's movie A.I.: Artificial Intelligence.

There will be a lot written about the fact that the US Appeals Court for the District of Columbia Circuit vacated the decision, made last year by Judge Thomas Penfield Jackson, to break up Microsoft. Aside from the circuit court being upset with Judge Jackson for talking to the press, in essence telling them how upset he was with Microsoft, the decision focuses on three things:

Many organizations have come to the conclusion that outsourcing can decrease costs and improve internal and external levels of service. They also believe that outsourcing noncore activities enables them to concentrate on what they do best and that outsourcing therefore is a desirable way to encourage organizational success.

The first wave of wireless applications will focus on business intelligence, according to Cutter Consortium.

For computer scientists, software engineers, and almost anyone else who works in the IT industry, talking about artificial intelligence (AI) is roughly akin to talking about religion or politics: everyone seems to have a very strong opinion and they tend to articulate those opinions in loud, strident voices.

One of the consequences of the dot-bomb explosion is confusion about what to do about e-business. Is e-business a flash in the pan? Where will e-business go from here? How can we use e-business in our company? Should we? These questions, and more, weigh heavily in many current business and IT strategy-planning efforts.

I'm impressed with the way IT people are thinking in broader and more businesslike terms than in the past. I attribute this to the rise of e-business and the success of enterprise resource planning (ERP) applications, among other things.

The recent slowdown of the dot-com area has given many people plenty of time to reconsider software practices and principles. What went wrong? What could we have done differently? How did so many smart people fall into something that wasn't going to work?

Automated software test tools have a high disappointment rate. After an initial flush of excitement of recording test scripts, the tool often becomes "shelfware," and testing returns to the old manual methods. The keys to successfully implementing an automated test tool are preparation, training, and realistic expectations. Here are answers for some of the common pitfalls and misconceptions.

Simplicity should be simple -- shouldn't it? Unfortunately, simplicity isn't always simple, and sometimes it's down right difficult.