“Ashley has been using tried and true, low-tech, high-touch methods of recruiting new members. Meeting people one on one. Kindling relationships. Advertising and relying on people who may or may not be a match for Knox to sign up for her database. That kind of thing.” He waggled his eyebrows dramatically, looking like a vaudeville villain. “We, here among us, have some of the brightest minds in computing today. If we apply computing power to the problem and the search, we should be able to find a more accurate match quickly.” He turned to me. “Lazer, you have access to Knox’s dating profile?”
I nodded. “Dex is onto something. According to Ashley, there is such a thing as a perfect match, for all intents and purposes, a one hundred percent match.” I smiled at the thought. “It’s rare. Most people can be, and are, completely happy with near matches. As it turns out, Ashley and I are a perfect match. If we could find a perfect match for Knox, or a very nearly perfect match…”
“How close of a match is Ashley to Knox?” Dex asked. “Theoretically, all we have to do is beat that, at least by a large enough percentage that it’s obvious.”
I pursed my lips. “All the information is in the Pair Us database, including Ashley’s profile and Knox’s. She’s never shared with me how close a match they are, and until now, I’ve never wanted to know. Not a perfect match, I know that much.”
“We know there aren’t any perfect matches in Ashley’s match database, at least,” Jeremy said. “Once we have our baseline match between Ashley and Knox, we’ll know what parameters we’re looking for. How do we find that match in the wild?”
“And facilitate the meeting?” Cam said.
“The meeting?” Dex said. “I’m not sure. We’ll cross that bridge when we’ve found some viable candidates.” From his tone, he was clearly excited. “Public records. Public profiles. If we crawl the Internet, looking for single women who match Knox’s profile—”
“Can we do that?” Jus asked. “Compile an accurate matchmaking profile from their publicly available information? Has anyone attempted that before?” It was clear he was thinking aloud, already mulling over how to go about it.
“It might take some training, but an AI program could do it,” Cam said.
“When we find her, we invite her to become a client of Pair Us.” Cam looked thoughtful. His mind was clearly turning over the problem too.
I nodded. “We’ll convince her somehow. I’ll offer any incentive. That shouldn’t be a problem. I can be extremely persuasive.”
“Throw enough money at someone,” Jeremy joked.
“A good digital search and a proper AI algorithm should be able to turn up someone, hopefully multiple someones, in case there’s no chemistry for some reason,” Dylan said. “Matchmaking isn’t an exact science. It doesn’t follow a formula. There’s magic involved, just like in coding. Which is why I believe we can do it. We have the magic.” He looked at the others. “We have enough brainpower. Do we have enough time? What’s the ETA on this?”
“ASAP,” I said. “But there’s no deadline. I have until Ashley gets fed up with me for not committing to a wedding date. She’s already been dragging me to wedding fairs by the dozens.”
“There are dozens of local wedding fairs?” Austin said.
“There are more than you’d imagine.” Dylan shuddered. “I’ve been to my share. There’s nothing worse than a wedding fair. If you haven’t had the pleasure—”
“Yeah.” I joined Dylan in a hate shiver. “Tell me about it. And who said anything about only going local? Ashley dragged me to one in New York and one in Paris—”
“Can we get back to the task at hand here?” Jeremy held his hands up. “We’re wasting precious time. We have plenty of experience with matchmaking. We’ve all been through the process. We wrote the majority of Ashley’s matchmaking software and configured her database and search algorithms. We’re not uninitiated newbies. Our expertise in the subject matter will speed things along.”
“Lottie will help us if we have questions,” Cam said, referring to Ashley’s assistant and office manager. “She’s on our side. And she can keep a secret.”
“Keep Lottie out of this. The fewer people who are in on it, the better. We keep everything legal,” I said, interrupting the unstoppable. I didn’t have as much faith in Lottie’s secret-keeping capabilities as the others, not where Ashley was concerned. Lottie’s allegiance was with Ashley, not me. And there was no reason to put her in an awkward position.
The good news was that the guys were intrigued by the idea of outwitting Knox and excited by the challenge of the coding. My biggest hurdles had been jumped. Nothing could stop them from proceeding now. I’d thrown down the gauntlet. They’d have to satisfy their curiosity and see whether the job could be done.
“Legal, schmegal. As long as we don’t get caught. If a tree falls in the forest and no one hears…” Austin winked.
He was one of the world’s top cybersecurity experts. He was the cat burglar of the digital world, able to sneak in and out of sites, grab what he wanted, and disappear without leaving a digital fingerprint. If there was a back door or a security hole, he’d find a way to sneak in. He raised his eyebrows hopefully.
“With all the privacy issue concerns,” I said.
“On the net, privacy is an illusion,” Austin said. “Just saying. But we’ll do our best to stay with what’s public.”
“Most of us still belong to dating apps and sites,” Cam said. “They’d be the place to start. We can crawl them pretty easily and pull from all public profiles. Then augment with AI and broader searches.”
“This might even result in a new business model for matchmaking and a way to take over the matchmaking market space completely,” I said, thinking aloud.
Dex rubbed his hands together. “There’s nothing I like better than a good life manipulation for the person’s own good, and ours.” He focused his gaze on me. “You’re the boss, Lazer. What do you say? Are you going to turn us loose on this task?”
2
Lazer
Sometimes it was damn awesome and scary hanging with the guys and watching them work. Their tech skills were frightening at times. They were brilliant, each on their own. But when they operated as a team? They were a well-oiled machine with a common brain. Good thing they were white-hat hackers. I’d hate to see what would happen if an agency for evil ever turned one of them.
Before calling in rich because of the dating app I funded, Austin had worked as a cybersecurity expert on government contracts. He knew his way around a firewall. The other guys each had their own strengths.
I was the only business major among them. Don’t ask me how I found myself hanging with these techie nerds in college, which was where I met everyone but Justin and Dex. I should have been hanging with the cool business crowd. These men were more fun. Because I had none of their skills, I was easier to impress with their tech prowess than the others.
They whiteboarded and flowcharted the task. Asked me dozens of questions to help them on their quest and to assist with the artificial intelligence learning code they intended to write and use. Assigned tasks and roles. Made a plan of attack.
This was a game to them. I was the overseer, the dungeon master of sorts. Mission control. Fortunately, I have a good head for running operations. Also fortunately, as previously mentioned, my friends had learned a lot about matchmaking from their experiences as Ashley’s clients, which helped as they wrote code to look for match compatibility.
Dex had never been a client, but he was particularly adept at psychology and personality profiles. He got to work applying modified criminal-profiling techniques to profile women and refine searches for matches.
I gave them all the information I had on Knox Emerson. Fortunately, Ashley had a comprehensive file on him in the Pair Us database, complete with her notes on why each of Knox’s dates hadn’t worked out.
I’d never broken confidentiality before, but I gave the guys temporary access to Knox’s files, telli
ng them they were operating under a nondisclosure agreement of the strictest kind, making a verbal contract with them that I was “hiring” them as contractors for this task. If we were going to succeed, we needed Knox’s dating personality and compatibility maps, his list of preferences, dating fails, feedback from women he’d dated, that kind of thing.
It was lucky for us that Knox had filled out his profile with military precision. His résumé was impressive. What he’d listed as what he was looking for in a potential spouse exactly matched Ashley. Had that been intentional?
“First up, we need our baseline,” Jus said. “What are we looking at in terms of the number to beat?”
Ashley had been secretive and cagey. Nowhere in her files or Pair Us’ database was a direct comparison of her profile to Knox’s. But the men had designed the software. They ran a comparison of the two profiles while I held my breath, unsure why I was so nervous.
All right, that wasn’t exactly true. I had an inkling—according to Ashley, Knox reminded her of her late husband Ruck. The two had been best friends and very similar. Ashley had never shared with me just how close a match she and Ruck had been. I hadn’t wanted to know, and she was wise not to tell me. In this case, my imagination had a limit. It was foolish to be jealous of a dead man, a dead hero, no less. But emotions are what they are.
I did know, for a fact, that Ruck was not a perfect match with Ashley. Which meant Knox wasn’t either. But if he was a ninety-eight or ninety-nine percent match? How much of a difference was there to that? Couldn’t a person be completely happy with a ninety-nine percent match? Was that within the tolerance for error?
Justin’s face lit up. “Ninety-two percent.”
“Hell, that’s barely an A percentage.” Dylan fist-bumped Justin.
“We have eight percent to play with, men.” Dex chewed the edge of his lip. “Not a mega percentage, but definitely doable.”
I let out the breath I’d been holding. Put in school grade terms, Knox was only an A-match. I was an A+. All right. I could live with that. “We have our baseline. What are you guys waiting for? Get to it.”
“Whip cracker,” one of the guys mumbled.
“I’m not that kind of billionaire,” I quipped.
After conferring about a few more details of the job, the guys began writing macros that performed their assigned task.
“This is like being back in the office,” Jeremy said.
“Yeah.” Dylan’s fingers flew over the keys of his laptop. He wore a look of concentration. “And my macros are still bigger than yours.”
“Bigger isn’t always better,” Jeremy shot back. He was the shortest, slightest, and smallest of the group. He was our skinny jeans guy. And sensitive about his physical stature, probably because the rest of us ribbed him endlessly.
“What women have you been talking to?” Dylan said without looking up. But he was smiling to himself. The others sniggered.
We pulled an all-nighter on Friday, working in the conference room I had at the lodge. Conference room sounds uncomfortable. Not mine. Mine was plush and filled with sofas and recliners, the usual, but latest top-end audiovisual equipment, and the best, and most stylish, ergonomic tables and chairs on the market, including a few that were custom made. It was like old times in college back in the engineering lounge, only more luxurious.
As a business major, I’d never had as much homework as the rest of the guys. In fact, once I was a junior, I didn’t even have class on Fridays. The guys, however, never seemed to have enough time to get all their programs, labs, projects, and assignments done. There were times when if I wanted to hang with them, my only option was to sit by and watch while they worked.
When I pulled all-nighters back then, it was more of a support gesture. And so I could drink beer and game while they worked. Irritated the hell out of them, especially when I graduated and almost immediately out-earned them. Then it was payback time for me from fate. Time to make up for those lack of all-nighters in college. In the business world, I’d had, and continued to have, plenty of them. The world of high finance and startups is not the faint of heart or forty-hour-a-weekers.
In college, I’d been the only one of us who could make a decent—by which I mean at least edible, even by college standards—breakfast. I could make toast and scramble eggs. Now I had a five-star chef who cooked for me and a staff to set it out. At eight on Saturday morning, the staff set out a buffet of salmon omelets, mountain huckleberry pancakes, fruit, hand-cut hash browns from fresh Idaho potatoes, and assorted breakfast pastries made by my personal pastry chef. And at the request of my friends, the most caffeinated coffee on the market—blonde-roasted caffeine plus. As contradictory as it is to common perception, the darker the roast, the less caffeine in it.
If you’re a coffee aficionado, i.e. if you live in Seattle, you know your caffeine levels of all blends and roasts of coffee as surely as you know your own name. This was essential so you could pace your caffeine intake after too many coffee meetings. And appropriately dose yourself in the right proportions against the gloom of too many rainy days.
God love Seattle and the Pacific Northwest, but we were home to the only rainforest in the Northern Hemisphere and a well-deserved reputation for gray days.
My coffee was custom-roasted in small batches at a local roastery. Some people might call us coffee snobs. We preferred the term “coffee aficionado” and were unashamed about it. We each had our favorite origin coffee and roast, caffeine level for the occasion, and brewing method, all backed by science and data. And frequently debated whose was best. We’d pulled many all-nighters together here at the lodge and had come to a tenuous common agreement about the best coffee for the job. I knew to order our all-nighter bean and roast ahead of time.
My friends were determined to keep working until they solved the puzzle and found a match that we could manipulate into falling in love with Knox and vice versa.
The parameters were simple, but, again, not easy. We needed a single, completely unattached woman in the twenty-five to thirty-five age range. Ideally, she should be in the Seattle metro area or nearby surrounding areas. Long distance was harder, though not impossible, to do. And she needed to be a better match than ninety-two percent, according to all the compatibility markers and tests we had—better than Ashley.
I hoped she existed. Was there really someone for everyone?
Depending on your point of view, you could call me either crazy, or very much in love and caring, for wanting Knox happily in love and out of my way. I could have ruined him. I had the money and power to do so. I could have married Ashley and had him flying around her like an annoying gnat. But I didn’t need that annoyance. So this was what it was.
Jeremy and Dylan had bots crawling the web with set parameters, looking through all the publicly available information for anything that would help us find this mythical woman. They combed through social media profiles and online dating sites, compiling profiles and match percentages.
Jus got the idea to run a check on their AI software by comparing the profile of Knox, which their software determined, to his profile on file with Pair Us. He and Dex ran it several times before calling me over.
“Something’s wrong,” Jus said. “Look at this.” He pointed to his computer screen. “Knox’s Pair Us profile, compared to his online profile that our programs compiled, doesn’t match within the margin of error. There’s a substantial variance.” He looked up at me from his seated position. “You’re the matchmaking expert. What are we doing wrong? Have we mis-calibrated a parameter?” He walked me through the thinking in their program development.
“It looks spot-on to me.” I was genuinely puzzled and as frustrated as the rest of the guys.
Work came to a halt while everyone took a look at it and the team worked through the logic. If there was a problem with the thinking, no one could find it.
“You have our Pair Us profiles, too,” Cam said. “Let’s run a check on ourselves and see how close our AI c
omes to matching our profiles. I give my permission to use me as a test case.”
Dylan, Jeremy, and Austin agreed to be guinea pigs too. And I was game.
When Jus and Dex ran the software on our profiles, it generated nearly identical matches from publicly available data to the profiles we’d filled out for Pair Us and the personality tests we’d taken.
We were stumped. Work couldn’t continue until we figured it out.
Dex sat, thinking, fingers locked in front of his face while the guys took another look at the software. “Fuck,” he said out of the blue. “Sometimes the obvious answer is the answer. Knox has played you and played you good.”
We turned in unison to stare at Dex.
“What do you mean?” I asked.
“It’s obvious—he intentionally faked his profile to guarantee he was a match for Ashley. That’s my guess. Amend that—I can’t determine intention. It may have been subconsciously. If I had to guess, though, I’d say intentionally. He wanted her to see how perfect he is for her. He knew his late buddy was a close match for Ashley. He knew how his friend would have answered the questions and did his best to answer as Ashley’s late husband would have. That’s my guess.”
I swore beneath my breath. “He played Ashley?”
Dex shrugged. “It’s the only rational, logical explanation. Played might not be the right word. Knox was a soldier. All’s fair in love and war. That may have been his thinking.”
“No wonder it was so easy for him to resist the women Ashley sent his way,” I said. “They weren’t really matches for him. Not close matches, anyway.”
Dex pointed at me. “Bingo.”
I cursed again. Knox was a worthier adversary than I’d imagined or given him credit for. “He’s had Ashley feeling like a failure all this time. But she had no real chance of finding a woman who would turn his head.”
“You have to admit, if his goal was to fulfill his promise to his late friend, it was a brilliant move.”
I didn’t have to admit anything. But Dex was right.
Mr. Accidental Groom Page 2