AI isn't the future. It's the system running quietly behind the scenes — sorting, routing, deciding. At Lotterdy, we don't glorify algorithms. We explore how they blend in real businesses, under real pressure, with real stakes. No fluff, no trend-chasing — just sharp insight into what works.
Whether you're rebuilding workflows, streamlining a team, or trying to make tools talk to each other without swearing at them — this is your space. Written by those who do the work, not just talk about it.
We don't write about perfection. We write about friction — the kind that emerges when systems stretch beyond their limits. These aren't post-mortems. They're close-ups of what automation really feels like in the wild: messy, unpredictable, and full of insight. Those aren't hypotheticals. Each case reveals something useful — even if it's just how to survive what's.
An ops team changed the name of a file in a shared drive. It broke a downstream data sync that had no documentation. The result? Silent failure for six days. We break down how brittle systems often hide in plain sight.
We don't write to impress algorithms — or humans, for that matter. We write to untangle. The world of AI and automation is flooded with big claims, sleek demos, and little patience for nuance. Lotterdy is for those who prefer slow clarity over fast confusion.
Each article is built from conversations with engineers, operations leads, and product thinkers who've been burned by bloated systems — and rebuilt leaner. We believe insight grows where reflection meets friction. So we stay close to the ground, and write only what we'd want to read mid-project, mid-mess, mid-real-life.
In Lotterdy, thinking becomes a habit.
NVIDIA's CEO insists every role will change—100%—as AI takes over routine tasks and empowers people to shift into more cognitive roles. This isn't just optimism; he emphasizes prompt engineering and analytical skills as the future of knowledge work.
Mechanize's CEO is working on automating software engineering itself—reinforcement learning agents trained to handle code, tests, deployments. The goal? A decade-long path toward bots that optimize even their creators' workflows.
A surgical robot, guided by layered AI systems, successfully removed a pig's gallbladder with 100% success in repeated trials—allowing human-level adaptability in tool-switching and error correction. Clinical trials? Possibly within the decade.
HSBC is piloting AI agents (via startup CasualLens) to handle up to 80% of data and analytics-heavy tasks—part of a broader effort to save $1.5bn annually while redeploying staff into higher-value roles.
We don't chase headlines — we follow weak signals inside operations, product backlogs, or messy team boards.
Many insights come from off-the-record chats with engineers, PMs, and automation leads who speak plainly, not for LinkedIn.
Before we publish, we imagine: would this help someone stuck mid-problem? If not, it's not ready.
We test quietly. Feedback loops from readers shape what stays, what gets scrapped, and what becomes a deeper series.
Lotterdy isn't a feed. It's a slow-growing circle of builders, thinkers, and fixers who care more about what works than what trends. Engineers figuring out automation edge cases, operations leads rethinking workflows, product owners trying not to drown in dashboards — this is who we write for, and who writes back.
Some send quiet feedback. Some suggest topics. A few have turned comments into full-blown essays. It's not a community by design — it became one by necessity.
130+ recurring readers from logistics, SaaS, manufacturing & consulting
15+ engineers & analysts have contributed their own use cases
40% of our traffic comes from internal team shares — not social platforms
First newsletter issue: opened by 73% — mostly at 7–9 AM on Tuesdays
Reader contributions shaped 4 of our last 7 articles
