Deeper - Abigail Mac - Work Week 30.11.2019 -
Abigail Mac, known for her striking features and charismatic personality, entered the adult film industry with a bang. Her ability to convey emotion and connect with her co-stars has made her a favorite among fans and directors alike.
9:00 am – All‑hands Sync
We opened the week with a 45‑minute all‑hands where the CTO laid out the why behind Deeper. Our current analytics dashboards give us numbers, but they don’t explain the why behind those numbers. Deeper’s mission? “Give every product team a narrative, not just a spreadsheet.”
10:30 am – Vision Board Workshop
I facilitated a hands‑on vision‑board session with designers, engineers, and product managers. Sticky notes flew across the wall, ranging from “Emotion‑based user journeys” to “Real‑time sentiment heat‑maps.” By the end of the session we had three concrete pillars:
2:00 pm – Data Deep‑Dive
I spent the afternoon with our data engineer, Maya, pulling the last 90 days of event logs from the data lake. We discovered a nasty timestamp drift (some events were recorded in UTC, others in local time). A quick schema fix saved us a potential week of mis‑aligned analysis. Deeper - Abigail Mac - Work Week 30.11.2019
Takeaway: A strong vision needs a solid data foundation. If the numbers are off, the story will be too.
🚀 Week in Review – Abigail Mac @ Deeper (30 Nov 2019)
This week we shipped the Insight‑Engine beta, cut our sprint cycle from 5.2 days to 3.1 days, and reduced post‑release bugs by 75 %. The live demo to our exec board earned $1.2 M in additional funding and locked in a bold Q1 roadmap. Abigail Mac, known for her striking features and
What made it happen?
• Early user interviews that shaped feature priority.
• Pair‑programming with data scientists—cut integration time by 2 days.
• Daily mini‑demos that kept the whole org aligned.Proud of the team’s grit and grateful for the stakeholder trust. Onward to predictive insights! #ProductLeadership #DataDriven #TeamWork
9:30 am – Remote Test with External Teams
We invited two external product teams (one from a fintech startup, another from an e‑commerce platform) to run through the prototype. Highlights: 2:00 pm – Data Deep‑Dive I spent the
11:45 am – Design Iteration
Based on feedback, I added:
2:00 pm – Aha! Moment
While polishing the export feature, I realized we could let users choose a tone (formal vs. conversational). The same insight could read:
Result: A simple toggle that instantly personalizes the output for different audiences (executives vs. engineers).
Early days but already fun to play with. I can see the potential and wish them luck.
“beta” though? bit early to call it that isnt it?
Interesting project, but I can’t help but think they’re setting themselves up for failure by not using more mature and stable upstream projects like GNUstep and Darling. Instead, they seem to have opted to use the remnants of Cocotron because “I prefer BSD/MIT/Apache-style licensing” (quoted from https://airyx.org/faq/). The problem, if you have a look at their Github project, is that Cocotron never implemented many of the more advanced Cocoa APIs and instead just calls NSUnimplementedMethod(). There are whole classes with no implementation. I guess this would allow you to compile software, but it most certainly won’t allow you to actual run any of it.
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