So I know anyone who codes is underwhelmed by that post title. Of course it is and we all have known that for some time. But how do I convey that to people who are non-programmers? I found myself a couple weeks ago talking to a person at Cisco and saying that AI tools like ChatGPT are incredible at understanding my intent in code and helping me out, but I felt lacking in making a concrete example that connects to people who don’t live in arrays, lists, and hashes.
Well, today I have an easy low-hanging fruit example to share. I was updating some code on my playoffpredictor.com site where conferences were hard coded in:
AI of course wrote the necessary code for me. Here was the prompt I used:
I want to replace the current hard-coded way of defining $conference and instead move it to reading the .json file and populating it from the file. please write the necessary code for me. The file path is /home/neville/cfbPlayoffPredictor/data/2024/fbsTeams.json.
For teams that pull as conference CUSA, Sun Belt, Mountain West, AAC, FBS Independent, I want those all to map to "G5" in the $conference array. I want the logic to be that if the team does not match SEC,B10,B12, or ACC then replace whatever the .json file has with "G5"
And here is the AI code output:
Here is what I mean by intent — no where in the prompt did I say anything about power 5 conferences. But it understands that and wrote the code that way. Stupid tools would just call it ‘filtered_conferences’ or some basic thing like that, but AI is smart enough to understand I want to separate out power 5 conferences and G5 conferences, even though I never used the words power 5.
Of course in 2024 with the destruction of the Pac12 there are now only 4 power conferences, so I edit the code to call it $power4 in my script. But the hard work is done by AI and I just do some fine tuning editing. This is a perfect example of how AI should be helping us in day-to-day mundane coding tasks.
Week 2 is in the books and for Auburn it is better luck next year. Ouch. Oh well, let’s see what we can learn from the computer model on playoffpredictor.com
The model went .615 (29-18-1) which was tied for 2nd out of 37 computer models for the week. Outstanding! And remember, this is with no preseason data of any kind. Just the results of the games played on week 1. Some of the more predictable results were Oklahoma beating Houston by 4 and Penn State beating Bowling Green by 7, when the spreads were -27.5 and -34 respectively. The computer model said -18 and -10.5, which were significant improvements on Mean Squared Error. Speaking of Mean Squared Error, the model went +142 and Absolute error of 3.3, which were dead last and next to last respectively out of the 37 computers. This is to be expected as other computers use player, team and preseason data. The model predicts no blowouts this early in the season, although we know there will be blowouts in week 1-4.
I don’t like this 12 team playoff. After spending last week updating the logic for 12 teams instead of 4 the computer sees these probabilities for teams making the playoff after 2 weeks of data:
Note the top likelihood is Syracuse, due to an ease of schedule. It wont last. I’d be surprised to see them still on top of the ACC by week 4.
Right now it says SEC gets 3.5 teams, Big10 gets 3 teams, Big 12 gets 1.5 teams, ACC gets 2 teams, and G5 gets 2 teams. I’d expect by season end it will be SEC 4 teams, Big10 3 teams, Big 12 2 teams, ACC 2 teams, and G5 1 team. I think the talk and season end is who is the 12th team, a 8-4 Missouri or a 10-2 Utah. Ugh. Who cares. What a horrible debate to have.
If you are on keppra as a medication for seizures, you should know that one sip of wine will make you die. In fact, more people die each year from mixing keppra and alcohol than die from defenestration.
This year I was fortunate enough to make one really good trade and hold a portion of it through fruition. Here I will document the trade and the way it has evolved over the course of this year.
Towards the end of 2023 I shaped up what my 2024 portfolio would include. I like liquidating everything at the end of a calendar year and re-buying what I like and believe in. For 2024 I decided I would put 6% of my speculation portfolio into 3 options, 2% each which worked out to about $6,000 each option. The 3 equities I decided to buy options on were NVDA, RIVN, and QQQ. Here is the the setup in NVDA coming out of Jan-Dec 2023:
It had a great 2023, tripling from 150 to 500. Sometimes last year’s winners are also this year’s winners — look at DELL and EMC in the late 90s.
And above is the entry trade into NVDA.
My reasoning for this trade was that I like this setup. I have been blow away by AI and ChatGPT and GitHub CoPilot. During the fall I spend a decent amount of time coding for my website and app for playoffPredictor.com. To say that AI made my coding so much better is a gross understatement. You simply can’t do this development on Intel processors – it has to be GPUs and NVIDIA. So there is my conviction. Also, look at the 2023 performance of NVIDIA. There is the huge gap up from 300 to 400 in May when they announced earnings, and then really ‘UNCH’ for the rest of the year. Well, I guess going from 400 to 480 is 20% which is far from 0%, but for a speculation stock this volatile that is growing earnings by 10X over last year- yeah 20% is pretty much unchanged. I like stories like that which are due for a total repricing, not just a change in price based on what you could have bought it for yesterday.
Here notice the date and the amount. Ideally I would have made this trade on 1/2, but instead it is on 1/9. Sometimes I get nervous on these trades and just want the price to fall a bit further. If I would have made this trade on 1/2 and done $6,000 – the price was 50 cents, so I would have bought 120 contracts instead of 30. Hmm…. @#%#$^#%&. Oh well can’t live in the past. And there is no way I would have thrown $6k at such a nonsense idea. I mean 50% in 10 weeks on a $1 trillion company is nuts.
To speak to that nuts, planning my trades in December I never wanted NVDA at 750 strike and 3/15 expiration. I actually was planning on 600 strike and 4/19 expiration. But the problem was it was just too expensive. On Jan 2 the 600 call for 4/19 was trading for $10. I waited the first week of January to pull the trigger and the price got down to $8, but that’s still too expensive for me. I like to buy options that are about 0.20 cents to 0.50 cents as a rule when I’m swinging for the fences. I was watching the price the first week of January and hoping to get a better price. But the price kept going up, and by Monday 1/9 the 600 calls were trading at $20. So I said what the hell and threw down $4,500 on 30 contracts at a much higher strike of 750 for about $1.50 each. I’d rather have 30 contracts instead of 5 contracts any day. My thinking is that you can get rich at 100+ contracts and just have a good return at <10 contracts. And it is a good thing I did not end up buying the 600 strikes. They would be worth ~ $300 each contract now which is 300/10 = 3000% A 30 bagger. Very good — but as it turns out not as good as the 750s
So here is what NVDA and the call has done 2024 year to date:
In a perfect world yes this was a .38 cents to 223 opportunity: 223/.38 = 58,600% or a 586 bagger! Imagine turning $2,000 into $1,000,000…
Well all January NVDA went up and the call went up, straight from $1.50 to $5 by the end of January, and then a quick run up from $5 to $25 in the first 3 trading days of February. Very nice I turned $5k into $15k and then suddenly from $15k to $75k was quite happy (ecstatic). I decided to celebrate by purchasing an Apple Vision Pro that came out on Feb 2. So I sold my first 2 calls on Feb 5th for $25 a contract ($5,000 credit, covered my initial investment. Everything else was now house money).
After February 5th it got much more interesting. Earnings were to be released Feb 20, and wall street was all abuzz with this earnings report. I felt it could go up into earnings, but I was playing with real money now. I’d never spend that kind of money on an out of the money option into earnings, but I didn’t have to spend that money — it just grew into that valuation.
My next move was on 2/12. By that time NVDA was trading at 720, getting really close to the 750 strike. Generally I sell an option when it goes from out of the money to at the money. This time I did not really want to sell, I wanted to see where this ride would go, so I decided to sell an upside call against my call position. Normally people sell upside calls against share ownership positions; it is called a synthetic dividend. But this was a little different. Essentially I turned by 750C into a 750/930 call spread. I sold 28 contracts at 930 strike for the same expiration of 3/15. My reasoning was that I was now guaranteed $20k of profit, even if NVDA tanked. Nice!
Of course I capped my upside at $180 per contract, but 180*28 is $500,000 – so I settled for a max profit of $500,000 with $20,000 guaranteed.
On 2/18 and 2/19 NVDA fell from 730 to 670. Earnings was on 2/20, and people wanted to lock in gains before earnings. That was somewhat painful. On paper each day I lost $30k or so. Basically all those gains to $75k gone, back to $20k total return. On earnings itself I did not watch at all. I texted my son an hour after close asking “Are we eating at the Ranch or at Taco Casa tomorrow”. His response “somewhere in-between”. My pulse quickened. After earnings it was back to $750 and I took the whole family to the Ranch for dinner the following evening. It was the feast of unrealized profits! Over the past 24 hours I had made $100k on paper. Other may be used to that, but I was not.
Now here is where I normally would sell the whole position. Earnings are done. The strike price has been met. It is too risky to risk everything and theta decay will kill you now. But I decided this time to just sell 8 contracts at effectively $31 each. And let’s see what happens with the other 20 contracts.
Now here is a trade I regret. From 2/23 to 2/28 NVDA drifted down from 820 to 775. Getting close back to the 750 strike I had a fit of paper hands and sold 5 more contracts on 2/29. I guess I just wanted to guarantee $60k in profits, so I sold.
The next trade was to buy back 2 of the 930 calls. from 3/1 – 3/4 (2 trading days; Friday and Monday) the price jumped from 800 to 880 and I suddenly realized taking out the 930 calls would be possible and then I’d be forced to sell. I just did not want to sell until expiration. I could have bought back all remaining 15 930 calls on 3/1 for $2k, but I didn’t and the price shot right back to the premium I collected in the first place.
Next I decided I wanted protection. I bought put options (expiring that Friday 3/8, 1 week before my call option expiration) so that I locked in $50 per contract no matter what. The only thing that could hurt me was if it closed Friday above 800 and then opened Monday below 800. I felt comfortable with that risk (it was trading 880 at that time). Sure enough these expired worthless, but that $760 spent helped me sleep at night.
Over 3/6 and 3/7 the price kept shooting up and was bumping right against 930. Well if I was still short the 930 I would have to sell, I mean at that point it is only risk with no reward as the 930 and 750 will both have a delta of 1. Only possibility is price goes below 930 and I lose more money on the 750s (still deep in the money) than the 930s (back to at the money). So I panicked and started buying back the 930 calls. Remember that $20k premium collected? Well, here was $12k just to buy them back. I was now long 15 contracts at 750 and short 6 contracts at 930.
Well on 3/8 open it broke through 950 and I sold 5 more contracts. I like to sell at market open, but I was on the Guardians of the Galaxy ride at EPCOT, so I had to finish that first. I sold the 5 contracts just outside the gift shop at 9:35am. I also bought back the last 930C contract. I kept thinking to myself the Guardians ride was tame compared to the NVDA ride. Why there is not a theme park with the whole theme of stock and options prices I have no idea — that is a wild ride! Total spread credit was $160 per contract.
On 3/12 I bought protection for 5 of the remaining 10 contracts for $4, financing it by selling upside calls at $1,000. I mean if I get $250 per contract I’m thrilled, and this guarantees a full $100 per contract. Of course both these expired worthless, except the insurance was nice this week as it drifted down on Thursday.
Thursday morning I went ahead and sold another 5 contracts at the open. Now I am locked into a minimum return for the whole trade. This trade is pretty similar to the 2/29 trade, done out of fear of loss or paper hands, same concept.
Friday morning is expiration day. Time to harvest what is left. But first I had to buy back the $1000 strike calls, else my account could be subject to infinite risk. Divorced from the big picture it was a good sale on its own – sold on Tuesday for $1,621 and bought back on Friday for $53. I guess if you think that way its a 30x return on your money in 2 days. Of course the catch is you have to tie up tens of thousands of dollars in shares or long options in order to make a trade where you sell premium in the first place. In a lot of ways it is not fair. $1,600 is a lot of money to most of the country and it is only accessible to people who already have means. I am sure someone reading this will be young and understand the concept, but be unable to execute it for themselves because they don’t have the money already, and that is a shame. I think Robinhood at least offers people money for loaning out their stock, even just a few dollars. That seems like a good start to me.
Finally, this morning I sold 3 contracts at open and in the afternoon at 2:45pm I sold the final 2 contracts. That open price ended up being the low of the day. Oh well. And I was going to buy that ivory backscratcher.
All totaled, it comes to $291,000 on a $4,500 investment, or a 6,500% gain, a 65 bagger. You only need a few of these in life to catch the options bug permanently. Do I wish I had held on the whole time, I mean it could be more like $600,000. While the answer is of course, I don’t think I would have had the mental energy to do this all the way to $600k. For that matter you could have bought the 950C expiring 3/15 for 0.05 cents on Jan 5th, and it would have been worth $50 on March 8 – a full 100,000% return – 1000x on your money. Turn $5k into $5M. You could have also done that with MSTR in February. I wish I would because houses on the beach are not cheap and I could use an extra 1 or 2 million if they are giving it away, but oh well. That kind of thinking is a trap. It is impossible to buy the low and to sell the high.
Here is one of the profit and loss bubble charts while it was trading at it’s high. Normally that percentage you are happy at 20% and 30%. The thing says %15,000. Just unreal.
Could I have done better? Yes, but. Common strategies that people use is to roll up (higher strikes) and potentially out (further calendar date) options as they go from out-of-the-money to at-the-money. If I would have done that and say harvested 50% each time while going up in 50$ chucks, I’ll bet I could have made a lot more money (I’ll have to compute that when I get back from Spring Break to see exactly how that would have worked out). But there is no way I could have done that, mentally. That would have meant selling $80,000 of options on 2/22 and then buying $40,000 that same day, like 3/15 800C. That would have been hard. I mean even though the money fungible and holding is the same as selling today and buying it tomorrow our human caveman brains can play with house money of $80k MUCH easier than playing with fresh $40k. I mean, I just would not throw that kind of money at an option expiring in 3 weeks. That’s irresponsible. People who can master that part of their psyche and not fall into that trap I am sure are fantastic options traders, but I have not conquered that hurdle yet.
Did I make mistakes? Yes. Here you have to separate true mistakes from just price anticipation, which is unknowable. Looking back at this I made 2 mistakes:
On 2/29 when I sold the 5 contracts I should have also bought net new options at ~800 expiring 3/22. I should have used 10k of the 20k for that. That guarantees $50k on the trade, but you have to get longer on weakness if you believe in what you are doing, not just flatter.
On 3/8 I should have sold everything. In my speculation account I have a rule – everything must be harvested 1 week before expiry. In my view options with less than a week is gambling and belongs in my timing account, not my speculation account. Now, of course that was the high that Friday morning, but that is irrelevant. I have to have the discipline that everything in the speculation portfolio must have an expiration >1 week out. This would mean that the protection I bought should also have been through 3/8, not 3/15. Unfortunately this was a $100,000 mistake (ouch)
In the end I think you need some conviction to stick with a trade like this. There is no way I would stick with it if I thought NVDA would not become larger than AAPL and MSFT, which I think it will this year. Now after that, it certainly can be cut in half. But if the thesis is that every single CPU in every computer and phone is dead in the AI world, yeah that is a big market. As for now, well it is spring break and I am headed to Mexico. Cashing out this week. No crazy options positions on vacation!
I have decided how I am going to vote for in the 2024 presidential election. I realize people don’t care about my political views, but I document them for myself and my family every four years. That’s as political as I’m willing to get!
As I write this on Feb 4, a Biden vs Trump rematch looks inevitable. Trump has won Iowa and New Hampshire by 50+ points, and only one other candidate is still running, Nikki Haley, and she is losing in her home state of South Carolina by 60 points. Is Trump v Biden round 2 inevitable? I guess not, I guess one or both of them could pass before November, but short of that I don’t see how it is not Trump v Biden and the necessary delegates locked to mathematically seal it by the end of March.
So I have written on Trump before. He is a narcissist and an asshole. Well, lots of politicians are, but unlike other politicians who smile for the camera and then stab you in the back, Trump just stabs you in the front. He rubs people the wrong way. I get it. But my mom always said to judge him on policy, which she did before turning on him after Jan 6, mostly because I think she just loved me and Shelli and knew her views were opposed to ours at that time. Trump at least has an agenda — America First (really we all know it’s Trump first, and he is running this time to save his own hide from financial ruin and prison but past that you can at least give me ‘America Second’). America First is a solid guiding principle. At least he has one. Biden’s guiding principle is ‘I’m not Trump’. While true, that mode of leadership does not make our country more prosperous, our cities and streets safer, or generally do much of anything except keep the status quo. With an America First guiding principle, Trump holds people accountable and fires and replaces them as needed. He did that so many times with cabinet secretaries and staff during his first term that it became impossible to count. And sticking to America First he tried to re-ignite manufacturing in America. But places where he tried and failed like Wisconsin became disillusioned with him. I get it. We tried, we had enough, we wanted some calmness in Washington and elected Biden.
We learned some things in 2016-2020. Trump can be president and we will not have nuclear war. The stock market won’t collapse in a Trump presidency (interestingly go back and look at the fist 2 days post-election results in 2016. During that Wednesday-Thursday November 5-6 the NASDAQ and all kinds of companies favored by liberal tech elite (AAPL, MSFT, AMZN, DIS) all got drubbed – losing 5-10%. At the same time main street America companies (like JNJ, PG, X) all gained 5-10% and started rocketing north). There is a Trump Bump. Even foreign countries (like EU Europe) where Trump is hated and feared they at least respect that he fights for his countries interests (like backing out of Paris accords, moving the Embassy to Jerusalem).
Biden has been adequate. I have respected his choices, like re-nominating JPoW. I also think he has succeeded in what I wanted him to do, which was turn down the charged political atmosphere that we had in 2020. He has done that, but that alone is not good enough to deserve another 4 years. Biden will be in his mid-eighties, and that is just too old to risk again.
But that was 2020. 2020 is past and done, the election this fall is about 2024-2028. I am going to follow the advice of my mom and judge Trump by his actions, not his words or personality. Specifically, I am going to judge him by his one real decision before the election, the selection of his VP candidate. Vivek Ramaswamy is a smart, polished Washington outsider- all things Trump values. He is also brown skinned and Hindu. So much MAGA support comes from fundamentalist Christian — does Trump have the guts to select Ramaswamy and force that thinking on the white MAGA group? If he does that I’m voting for Trump in 2024. Note, I did not vote for Trump in 2020 or in 2016, so this would be a first. If he picks someone besides Vivek, I will likely not vote at all this cycle, or throw my vote away again on a 3rd party candidate like I did in 2016. It is sad, but so are the choices we have. Hopefully 2028 will offer better choices.
So the final 2023 CFP rankings have come and gone, and I reflect on the model performance. There are 3 different ways we can look at what happened — computer best teams, computer most deserving teams, and playoffPredictor.com method with committee bias.
Computer best teams involves carefully looking at margin-of-victory and using that to deduce the best teams. Close wins are punished (a 1-point win gives an m=-0.8) and blowout wins are rewarded (35-points and greater wins give an m=+0.5). This is detailed in the full method. I know it works because results are well correlated with other computers (who churn though *much* more data than I do), and I have excellent results — I finished the 2023 regular season at around 52.3% ATS, which was 6th (out of 28 computers) and 2nd (out of 17 computers) that picked all games this season. From a best team perspective — meaning bet on these teams in Vegas to win on a neutral field, here is what we have after week 14:
Teams that were ultimately selected by the committee as the 4 “committee best” are highlighted in yellow.
We see that 2 of the 4 of the “committee best” are nowhere close to the “computer best”. The computer best top 4 includes 2-loss Oregon and 1-loss Ohio State. These teams were dominant — For example, Oregon beat top-25 Oregon State by 24 points, where Washington beat them by only 7. Computers and book makers agree — if Oregon and Washington were to meet a 3rd time this season Oregon would still be a very slight favorite. The fact that Washington beat them already twice has nothing to do with where the money would land. Oregon, Ohio State, Georgia — all really, really good teams.
Now, look at it from computer “most deserving” standpoint. Most deserving involves slightly punishing 1-point and 2-point wins, and giving slight advantages to blowouts of 25 points and again 35+ points. It is a formula that is well correlated to human polls with a end of season η around 1.2. Again, see the full paper. Most deserving in 2023 were:
The computer got it exactly right, including #4 Alabama and #5 FSU. But that is not the method I have used for 10 years. What I have used is a committee bias — basically see differences between the computer most deserving and committee best, and use the average of that to predict the future. That method cratered this year. 2023 final predictions were:
The model of computer most deserving + bias predicted #2 Georgia and #4 Ohio State. But these were wrong.
What happened?
Well, to put it bluntly, the committee lied. They lie every week from week 9 right through week 13. Week 14 (the final week) they just pick who they want. Take Georgia for example — the committee had them #2 in weeks 9-10, and #1 in weeks 11-13. Rece Davis even asked the CFP chair point blank before the Bama game “is Georgia unequivocally one of the 4 best teams?” Translation — they have already done enough to get into the playoff. The votes weeks 9-13 would say yes — the computer had Georgia as low as #9 in week 9 – they had not beaten anyone. Georgia only rose to #3 in the computer most deserving by week 13 because finally they had blowout wins over Tennessee, Ole Miss, and Missouri. But that bias was so strong– as high as .11 in week 9 and always above ~.05 that even with a loss to Bama, Georgia should have been one of the best 4 in the final poll. Else, the committee was lying all those weeks 9-13. I mean in Week 9 when Georgia was #2 behind Ohio State their best wins were Kentucky, Auburn, and Florida. Teams that would finish 7-5, 6-6, and 5-7 respectively. I mean they beat Auburn by 7 when New Mexico State beat Auburn by 21. If the committee knew something and elevated them to #2 back then, they sure sold Georgia up the river in the final poll when they acted like they never had UGA in the top 5.
So what to do going forward? I could simply change the formula to have no bias and simply use the computer most deserving, but that does not work all years. Look at this over the last 10 years:
To read this take an example from 2022. The computer most deserving after week 14 was Georgia, Michigan, Ohio State, and TCU. That was #1, #2, #4, and #3 to the committee (the committee had TCU #3 and Ohio State #4). With correction for bias the method produced #1 #2 #3 #4. All 4 teams correct and the order correct.
Look at 2023. Computer most deserving are #1 #2 #3 #4. But add in bias and you get #1 #3 #5 #7. Not good. Again, the committee lied.
But look at 2017. Computer most deserving are #2 #8 #1 #6 — bad. But add in bias and you get #1 #2 #3 #5. Not perfect, but good. 2017 was the year USF went 12-0, and the committee was never going to get them to the top 4 even though the computer most deserving had them at #3.
So, I’ll keep my method for the 12-team playoff the same next year, but use a grain of salt. The method is sound, the computer is accurate, but the committee lies.
The games have been played up to conference championship weekend. The committee has spoken 5 times. On Sunday they speak for a 6th and final time for this 4-team format. The computer has churned out the answers — and the model likes Ohio State and not Alabama or Texas if one or more teams slip up this weekend.
I don’t like it, but the committee has over-liked Ohio State all these weeks, putting them at #1 when the model has them usually #3 or #4. Even last week after the UM defeat they only went to #6 and the computer has them at #5, so small negative bias, not enough to make up for weeks 1-4.
Right now the only path for Texas is Washington and Georgia winning, Michigan and FSU losing (about a 0.2% chance). The only path for Bama is Washington winning, Michigan and FSU losing (about 0.4% chance)
If the committee ends up agreeing with the computer I’ll be happy the committee did the right thing, but mad at the committee for being wrong weeks 1-5. Let’s see what happens. https://playoffpredictor.com
I am going to use my model and track prediction accuracy for beating Vegas for 2023. Picks will be tracked at predictions.collegefootballdata.com. 2 accounts will be used to track the model:
@PlPredict_all for all FBS games, and
@playoffPredict for high-confidence games per the model, additionally
@cfb_vegas_line for the Tuesday (opening Vegas line)
Definition of high confidence is >= 7.5 points difference between Vegas line and computer model. Only applies after week 2 (weeks 3 till end of season)
Model will not be updated within a week (picks locked on Tuesday)
u/nevilleaga is going to pick all games using the trailing 15 weeks of data (meaning if it is week3 using week 1-2 data from 2023 and using week 3-17 data from 2022
use @CiscoNeville to mess with any personal ideas. One example is looking at the line and predicting something close to the line skewed by the method. @CiscoNeville will do that by using actual 2023 game results plus one extra week of the line as results. So for example if the OU-Iowa State line is OU – 14, a game will be entered with OU 14 IowaSt 0 like it actually happened.
Results published here as comments
update 9/28/23 – I realize that for weeks 2-4 I used and m of best for eta, not m of best against the spread. For week 5 and forward I will be using m=ATS model 6, which goes from m=-0.8 for a 1 point 1 to m=+0.5 for a 35+ point win.
Below is a list of my most useful links on the Cisco Intranet that would be handy to get a generalist SE/SA up and productive. Of course most of these links will not work without access to the Cisco internal network via VPN, and they will not work without logging into Cisco (which is done at id.cisco.com)
Enterprise Agreement management portal – https://eaccw.cloudapps.cisco.com/app/#/ – Used to see the quotes your software sales specialist puts for EAs – knowledge worker counts, suites covered, etc.
topic – topic.cisco.com – Possibly the most important tool for any Cisco presales SE/SA. Look up every question ever asked and any answer ever given in any forum to product management or TMEs. Set data sources to “Newsgroup” to search PM/TME communications and/or “CSOne” to search all previous TAC cases. Leave the other sources unchecked.
TAC case query – https://cae-xmlkwery.cisco.com/main/casekwery.php – This is the one I like the most. There are several portals that will get the same TAC data, but this one organizes the information best.
CCW-R – https://ccrc.cisco.com/ccwr/? – where you can input a serial number and find info on ship date, who it was sold to, and if it is still under E-LLW or TAC support
CCO lookup tool – https://cdca.cloudapps.cisco.com/cdca/lookup.do – Lookup your customers CCO status, see what contracts they are associated to, and even add contracts to their profile, self-service (sometimes works). Try doing a search not on email address (takes too long), but on customer name using exact (not contains). Searching is case-sensitive, so “university of Oklahoma” returns nothing, but “University of Oklahoma” returns the records. If you want to look up yourself use it without the @cisco.com – for example “neaga”, not “neaga@cisco.com”
Smart account info via Cisco Software Central – software.cisco.com – First get access to your customers smart accounts by using the link for “Request Access to an Existing Smart Account”, then use Smart Software Manager to see their licenses, including products registered and pulling licenses.
My business reports – https://mbr.cloudapps.cisco.com – See product quotas and attainment for the region. See week to date or quarter to date numbers. Also hit dashboards->Bookings 360. Best way to see product bookings over the last 3 years by account. Hit advanced filters, change from “Sales Hierarchy” to either customer or BE.
Cisco Ready – https://rewarddash.cloudapps.cisco.com/#/sales/analysis/asset – How to find out what is at a customer. Use “Install Base” “Total Asset View”. Change the filter to get one account, and then click on the right and download to email/teams. Once downloaded, open the excel and select the data and move it to a pivot table.
