Chris Fischer

Wolf of
Williamsburg

We’ve all heard of The Wolf of Wall Street. Williamsburg is not Wall Street.

I spent most of my tech career living and building in this neighborhood. I watched it change, and changed right along with it, while staying curious enough to chase every crazy idea that came along. Success was always more about the journey and the stories than the big payday.

This page is the timeline of that. Every company, side project, business, property play, hustle, and ridiculous commercial idea I’ve tried. The ones that worked, the ones that failed, and the ones that never made it past a conversation.

Right now I’m the co-founder and CPTO of Goodword, an AI relationship management platform. I’m also continuing Wolf Works, my growth and AI advisory practice, and launching Wolf Works Labs, an incubator and accelerator for early founders who need someone to build their MVP and help them raise financing.

Wolf of Williamsburg in a black beanie, shirt and tie, black trousers and simple shoes, holding a steaming coffee

The endeavors.

The jobs, the companies, the side projects, and the things I keep coming back to. A lot of these were happening at the same time.

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48 stories / Data & AI. Newest first.

  1. Please List Our MCPGoodword's Claude connection was working. Getting it into the MCP directory meant another submission and review queue.
  2. Unofficial Means BetterAn informal meetup built around live Claude demos needed hosts, and my name ended up on the list.
  3. Claude Found the Right PersonA relationship question inside Claude became a live test of whether Goodword's MCP connection could find the right person.
  4. All My AI Tools, One DoorI had too many AI tools, too many separate connections, and one web portal trying to put them behind the same door.
  5. Contacts, ConnectedA broken connector was keeping selected Goodword contacts out of the team's research system, so I repaired the path.
  6. One List, Too Many ToolsAn opted-in email list needed a reliable trip from Google Sheets through cleanup and into Goodword's working CRM.
  7. What Should I Do Next?Goodword could find useful context, but the harder product question was what it should suggest somebody do next.
  8. Do Not Sort AirtableA routine list cleanup produced one blunt rule: do not edit imported Airtable records while the table is sorted.
  9. Zapier, Meet the TerminalA few signup automations turned into an experiment with running and managing Zapier workflows from the command line.
  10. CSV or Google Sheet?One working list needed two exits: a plain CSV file and a Google Sheet people could use immediately.
  11. What If the App Knows Nothing?Loop's first alpha scope turned a relationship-management idea into hard questions about imports, context, closeness, and what a brand-new user would actually see.
  12. Eight Weeks, Then LoopI left a new full-time CPTO job at Pinata to cofound Loop and start building an AI professional-networking product from scratch.
  13. We Were Calling It LoopA relationship digest, a pile of prototype prompts, and a designer kickoff turned a loose RelateAI idea into something we were calling Loop.
  14. Sorry for the Long DelayApply had licensed art, partner payouts, and more than a year of reporting I needed to get squared away.
  15. No Apps Available to TestThe first weeks at TRX included an App Store approval, an empty TestFlight screen, a first digital operating review, and a new commute to Newport Beach.
  16. Averages Won't WorkA clean churn chart hid the real questions about who was exercising, who was renewing, and whether the product had become a habit.
  17. Pack Up And Price UpApply Stickers had a bright yellow financial model, a two-to-five-dollar fulfillment problem, and a lot of COVID assumptions to test.
  18. Every Rep Leaned LeftA 16-by-400 workout looked fast and consistent, but every repeat showed the same small pacing mistake.
  19. No Code, Still InCyral asked me to advise on database security. I wanted the work, but first I sent Aaptiv a plain conflict check.
  20. Runner to Runner :)I wanted old NYRR data for a Prospect Park Track Club side project, so I emailed the runner who built RunGraphs and asked for his scraper.
  21. Sixty People, Two Hundred ThousandAaptiv had reached about 60 people and 200,000 paying members. I was recruiting, reviewing Peloton, and logging searches that returned nothing.
  22. Seventeen CSVs LaterI turned Aaptiv activity data into seventeen queries covering the path from the home screen to a completed class.
  23. Four Buttons, Somehow ImpossibleLoft 2.0 had smart bulbs, a mounted television, and new audio, but the custom light-and-shade remotes took an entire day to find.
  24. Can We Just Kill It?Two low-value Reonomy features needed different shutdown plans because one was written into contracts and the other still had a few users.
  25. Sunday at Noon, AutomaticallyThe manual Mixpanel usage check became a weekly CSV report that would arrive automatically every Sunday.
  26. Address In, Property ID OutA custom address translator was nearly ready to connect a customer's loan system with Reonomy's property data.
  27. Scala Goes to LAReonomy was finishing a rebuilt data-processing pipeline for Los Angeles while I looked for temporary help to expand the ingestion team.
  28. The Numbers Did Not MatchMixpanel and Intercom disagreed about Reonomy usage, so I spent a day comparing them and built a manual plan we could trust for now.
  29. CTO, Ironman FinisherA short 2015 bio tried to fit startup leadership, Shutterstock's IPO years, Reonomy, and endurance sport into one paragraph.
  30. Everyone Ships CodeAt the 2013 OpenStack Summit, I explained how Shutterstock provisioned virtual machines and physical servers through one automated system.
  31. Zero Under-Replicated BlocksFour new Hadoop data nodes pushed an important storage health metric all the way down to zero.
  32. 110 Days to GoA storage rebalance was about ten percent complete after twelve days, with an estimated 110 days still to run.
  33. More RAM. Again.A January hardware plan counted the memory modules needed for Shutterstock's search and database servers.
  34. No OutageA week after postponing the work, Shutterstock moved its main databases to Boston without taking the site down.
  35. Still HereThe whole operations team was still provisioning a new data center, so the next database cutover could wait.
  36. Boston Takes the TrafficThe web servers had moved. Next came the part customers could actually hit: production traffic.
  37. The Graph DroppedA speed release aimed at distant users landed, and the first measurements moved in the right direction.
  38. Get AggressiveI wanted to move the MogileFS conversation from research toward the real Shutterstock and Bigstock libraries.
  39. Three to Six-ThirtyThe site stayed up through an overnight database and search problem whose cause was still unclear.
  40. Data Server IssuesIssues around the data servers had contributed to a recent outage, so I asked for a conversation that day.
  41. Replication LagReplication lag had shown up again, and I wanted systems and development looking at it together.
  42. Fun ShizMogileFS, Xen, deployment graphs, and a weekend in the office sounded like a good time.
  43. I Love BIND FilesI set up PowerDNS with a MySQL backend because database records were easier to automate than hand-edited BIND files.
  44. Tmptrash FirstThe GetGlue logs needed to leave the servers without disappearing before I knew the S3 copy was good.
  45. Off EC2 in Twelve MonthsPeek had more than fifty compute nodes in Amazon, and I was already pricing the first half cabinet for our own equipment.
  46. Nike+ at the GymA 24 Hour Fitness email passed along a Finish Line offer for the Nike+iPod running kit.
  47. Deadmau5 Won Most of ItThe first Beatport Music Awards turned a year of store sales and six weeks of public voting into 19 winners.
  48. Nineteen Ways to WinBeatport opened voting for its first Music Awards, using 2007 store sales to build the nominee list across electronic music.