These books will explain better than I can. Assuming you come from a technical background like myself... and in a B2B SaaS context.
Sales is the process of helping others solve their problems and then showing how your solution is the best choice. As a technical person, we are actually best positioned to succeed in modern sales. The complex sale, what today's SaaS is, involves understanding their situation, teaching or offering insights that get at their true problem, helping them to construct the best path forward, and then showing how your company's solution helps them get their best.
Sales and marketing are highly coupled, along with customer service and other post sale ops. There are funnels or channels for how people find your business, progress through the sales cycle, and eventually become paying customers. Marketing is the long-term, front running process to create awareness. Sales is the in the moment process of filtering potential customers and guiding them through the funnel to a closed sale. Post sale operations Ensure the success and lasting relationship with your customers. All three are critical to a healthy, successful, and sustainable business.
Copy on your website isn't necessarily specific to sales or marketing. Every interaction the customer or user has with your company is part of branding, marketing, sales, and overall success. The key here is that you want to consistent message and that message should speak to the customers dreams goals and aspirations. What happens with technical founders often, is that they talk more about features and technical specifications than the benefits of the product from a customer's point of view. here you want to spend as much time as you can with your users especially early on. They will inform you how they think about your company what you sell and give you the language to use in your copy whether for marketing sales or documentation.
I highly recommend you pick up these books they will open your mind as they did mine to sales as a very different thing from what we know in popular media. If you have the mindset that sales is largely pushing like a used car salesman, then these books will give you a fresh perspective on the reality of who is most successful in a B2B sales situation. It's not so difficult to learn sales as a technical person, in fact it's far easier than the other direction. so worrying now about feeling confused and lost at this point, if you do your learning you'll be capable of crushing it in sales.
Get the books, read them, your understanding will increase and confusion decrease.
Both kinds of sales are "sales" as there is not just one kind. What you will see is that the popular media ("regular") sales is not actually regular, that there are also different types of sales people, and so on.
Basically your exposure and sales vocab are still underdeveloped, so reading some books will aid you greatly.
That's the spirit! Books are super cheap knowledge. When your done with those, email me and I can point you towards more for your new questions that will come up.
Hey, no, I have build a website with free mathematics resources for university students.
I am getting good traffic and now I am looking for monetization options that would be non-invasive to the project (for example. I don't want crappy, non-relevant adds).
I also studied CS on polish university and I feel we had the best of both worlds:
Initial programming courses were electives, where you could choose between more basic or more advanced "intro to programming" course. Basic had python, while advanced had c and c++.
Similarly logic classes were in basic and advanced groups and it was easy to choose the group you want and switch groups during course.
In fact, I was the guy who came for CS degree after never doing great at math or CS in high school and it reaaaaaally helped me to get up to speed with the others.
I am a polish native speaker and only after I have met my french-speaking girlfriend, I realized how insanelly difficult my language is, for all the reasons you have mentioned.
There is so much comments about whether the proposal is good or bad. But for me, without making usability tests, there is just no way to know if it's better.
For me proposal for redesign without any experimental data presented is just an invitation to endless speculation.
It's funny how my experience is exactly reverse. Since I joined startup I learn much less, since we can't afford experimentation and there are no other front end devs here, so I don't get a chance to learn backend stuff, since someone has to do front end part.
I also hoped to learn some business stuff, but most of it happens behind closed doors between founders and investors while you code boring crud application.
I've been back and forth between startups and corporations. I think I know what you mean in technical terms; that corporations use more advanced (rigorous) processes and tools and so it feels like you're learning more (it feels more precise/correct) - That said, I think that a lot of the stuff that you learn in big companies are anti-patterns when you consider the big picture; a lot of the time, you learn technical solutions to problems which don't really need to exist to begin with.
For example, one reason why many corporations push really hard on having 100% unit and integration test coverage is because they have such high employee turnover that they can't rely on their engineers to maintain their own code; corporations have to assume that engineers who work on their projects are completely unfamiliar with the code - In this case, automated tests are the only way to maintain the integrity and stability of the code base. The time cost of maintaining all these trivial unit tests is ignored (even though the cost is actually very significant; not to mention that these tests lock down the code and thereby discourage refactoring and experimentation).
Corporate processes are designed around the assumptions that engineers don't care and can't be trusted. This is a very inefficient approach to building software.
Personally, I'd rather my project have code with 0% unit test coverage written by a team of involved engineers than code with 100% test coverage written by a team of indifferent engineers.
> For example, one reason why many corporations push really hard on having 100% unit and integration test coverage is because they have such high employee turnover that they can't rely on their engineers to maintain their own code
I'm in a similar situation as yours and have switched between big corporations and startups and now at a big co again. I used to have the opinion that unit tests are a time sink, but what changed my mind was the iteration speed unit tests gave me. Without them, to test that my code actually worked, I would either deploy to a test environment (or prod in the worst case) and if it didn't work, then that just meant a longer feedback loop. What I realized after starting to have solid unit tests was that I catch issues much earlier in the pipeline and when I finally release code to test, it works 99% of the time. The only time I've had bugs in test env was because of some implicit assumptions in my mocks in the unit test. If you think about it, that lets me iterate faster by pooling in lots of changes and releasing with confidence.
I think its natural to be biased towards testing in a real environment as opposed to unit tests, as it is more rewarding to see your code work and do what its supposed to do versus seeing it work in a stubbed out environment.
Unit tests to me are more about iteration speed and release confidence, than about corporations not trusting engineers (which is also true).
I would only write unit tests for very complex classes whose logic cannot be simplified into something readable.
Personally, I rarely introduce bugs at the unit level, almost 100% of my bugs are related to how classes/functions interact with each other - I find that bugs at the unit level are easy to track down (and often they will be caught by integration tests anyway).
I prefer integration tests because they traverse more code paths and don't need to be updated so often.
The main complaints I hear about integration tests is that they're slow and brittle but this is only the case if they rely on external microservices (or external data stores) and if test cases aren't properly isolated from each other. I use integration test cases as part of my development flow.
(disclaimer: I've worked at two mega corps and a startup and generally favor my experience at the second mega corp so far)
I think your example points out a factor, but not the only factor and probably not the biggest factor. You can also say that startups don't live long enough for their code to grow organically from their original, pristine design and develop deep seated code "cancer" like mega corp code does. Also, even without turnovers, some features just go through enough code modified by enough engineers that Murphy's law happens and things break in creative ways that E2E tests catches or could have caught. And finally, just because I remember my code today doesn't mean I'll remember it in a year or two... I don't assume that my coworkers have perfect memory either.
I couldn't agree more, I've just left a start up for a traditional company purely because here I have opportunities to learn. It comes down to the culture of the company a little bit, for example this place likes it's devs to do R&D/experimentation to scope out opportunities to add value to the business. The point remains though that such a thing just wasn't possible at the startup I was at, there wasn't time.
And another anecdote. Not necessarily “startups” but everytime that I work for a small company, I get to do everything. I’ve learned a lot from working st small companies and small IT departments at larger companies.
I would never have had the experience I have from front end, back end, databases, cloud architecture (I’m one of the AWS admins) from netops, devops, to development and to work directly with C-level people.
yeah, quite similar situation in my experience too. Usually you need to implement features ASAP, so rarely you have time to do it properly, so you cut corners , implement it , and move on to another burning task just to meet deadlines for next investment round or something like that.
This is said so often and yet for me personally gym helps only very temporarily - just after workout I feel great, but the next day anxiety might kick-in again.
There is a fill-up effect (what you describe) and a build-up effect (repetition on the long run).
It's like a capacitor discharging[0], so at first you have to recharge it often† to not go under the anxiety threshold, but with time it holds more charge, and charges better, so it discharges much more slowly thus reaching the threshold much less often, if at all.
† Part of why it may be important to workout for shorter times/intensity, but more often.
The research we have says exercise is moderately better than doing nothing, unless you only include good quality research in which case the benefit is harder to see.
Thanks for posting this. The conclusion on that page is:
> Exercise is moderately more effective than a control intervention for
> reducing symptoms of depression, but analysis of methodologically robust
> trials only shows a smaller effect in favour of exercise. When compared
> to psychological or pharmacological therapies, exercise appears to be no
> more effective, though this conclusion is based on a few small trials.
My personal take is that the big things to note are:
1. Reducing symptoms of depression is not the same thing as treating depression.
Thus, if you exercise and it works for you to reduce the symptoms, you aren't "better," you just aren't feeling as depressed. This is valuable in its own right, as the symptoms of depression can interfere with you seeking actual treatment... But it is not helpful if you think you're better, stop exercising for some reason, and fall back into depression again, possibly with a side-order of pessimism that nothing seems to work.
2. Exercise is not more effective than psychological or pharmacological therapies.
Although they say there are only a few trials to establish this, I personally feel it's quite safe to assume that it is not more effective, and as per 1 above, that it can be harmful to take an "either/or" approach to exercise and other therapies. Until someone shows me research saying that exercise in conjunction with therapy is worse than therapy alone, I personally try to do both.
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The uncomfortable truth about exercise is that a large number of people with mood disorders self-medicate their symptoms with endorphins. When that is used as an alternative to therapy, it may be harmful.
Just my 2c: consider vigorously walking for 30-90 min per day every day you do not go to the gym. This is safe (walking is generally low impact on your tendons) and can extend the duration of the feel good effect.
What would be your advice for older (25+) people who want to get into science? Is it even possible? Or should I just accept that the train has left and focus on something else? Can you develop your math/logic/critical thinking skills at that point?
How about if you never excelled at these topics in school? Is hard work enough, or do you think some people are born with these talents?
Sure, inborn talent matters. Hard work matters. And what about the less-appreciated converses of those two qualities: namely, acquired talent and inborn propensity for hard work? :-)
We could also mention drive to seize opportunities, judgment in picking the right problems to work on, social skill to get potential collaborators excited about those problems, and of course luck. And probably 200 other things I forgot. They all matter.
Maybe the key is, instead of struggling against the profile of abilities that fate handed you, to find a subject or problem that's an optimal fit for that profile. Had Darwin been forced to spend his life as a mathematician, Godel as a biologist, or Einstein as an experimentalist, you would never have heard of any of them.
Practice makes perfect. Some people are born with the ability to learn some topics faster than others but over time hard work will always bear results. You can learn math/logic/etc the same way any college student learns.
The brain is able to change well into adulthood ("neuroplasticity"), and that includes mathematical/scientific/abstraction centers. There are plenty of folks who didn't get a great start in STEM, but through hard work and dedication, they pushed through the inherent frustration in learning STEM.
While some people might be born with a proclivity for these activities, I wouldn't say any individual could not get into science. For the truly uninitiated, check out Planet Earth, Blue Planet, or Cosmos. For the novices, check out your local astronomy club, ask scientists you know to explain their work to you, and don't be afraid to ask follow-up questions. Get into reading science articles in the popular press, and use those to find links to the real research articles, which will be VERY hard to read for beginners. Feel free to skim those, look at graphs/charts/evidence, and read the abstract/conclusions rather than the intro/methods and the whole thing. Finally, check out some MOOCs or local community classes/continuing education.
Good uplifting answer. But it is for what can lead to a hobby, rather than a career. Even certificates from MOOCs won't lead to a job in science, researcher or not.
Even certificates from MOOCs won't lead to a job in science, researcher or not.
That depends on how tightly you define "science". If you mean "science in traditional academia, working for/at a major research university or research consortium" then you are almost certainly correct. But if you expand the definition to include the corporate world, and roles that maybe aren't pure research, then I would argue that you can get a job doing science with less "paper credentials" than one might expect.
Whether or not that would/could apply to anything related to QC, I'm not sure, as I don't work in (or even really near) the QC domain. But to pick one example: in terms of machine learning / AI, I've definitely seen it. But maybe AI/ML is an exception to everything else just because it is (at the present) such an empirical / observation / experiment based domain.
Outside of all of that is the notion of "create your own job". If you want to be a researcher in Field X, start a company related to Field X and hire yourself. And, no, I don't intend that to be a glib answer, and I certainly acknowledge that it A. isn't easy, and B. is probably harder / easier in some domains than in others.
I don't think you can't, but you have to be aware of the demands graduate school makes on students, including working long hours on course work first and then actual research. If you are older with more commitments, it's just harder to commit to. It can also be pretty isolating, especially given that most of your fellow graduate students will be a bit younger than you (as well as being quite immature, as many have never had an actual career and come straight from college). By the way, what I've explained isn't great, it's terrible, but it's the system that exists now.
Of course, this is just a warning, just be aware of what you're getting into.
I should add, professors who advise you to go to graduate school have a financial incentive for you to go to grad school if either 1) you will be their students (you are a means for them to get grant money and it helps inflate their credentials, not to mention you will be their cheap labor) or 2) they are currently your professor in undergrad or taught you previously (you going to graduate school also helps up their credentials).
Even barring these possibilities, professors who have tenure or tenure track positions just by virtue of statistics are extremely lucky: many smart people write their theses and do substantial work, but there are a small number of actual positions relative to the number of PhD's awarded. For example, in Physics, I think there are may be dozens of openings in the US every year while there are thousands of newly minted PhD's per year, and the majority of good positions as you can imagine go to graduates from a handful (O(1) number) of schools, anything below the top 10 is significantly less well poised for tenure track professorships. Thus, you have to take a professor's advice with a grain of salt, for they're potentially influenced by survivorship bias.
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