tinix
Principal/Staff-level engineer and systems architect with 20+ years of experience.
Technologies: Python, Go, Scala, PostgreSQL, Redis, AWS, GCP, distributed systems, event-driven systems, ETL/data platforms, observability, performance engineering.
Recent work has focused on: - distributed data and workflow systems - healthcare data integration - event-driven and domain-driven architectures - performance profiling and optimization - concurrency, multiprocessing, and large-scale data processing - PostgreSQL, Redis, S3, AWS infrastructure, observability, and CI/CD - RFC/ADR processes, architecture documentation, and engineering standards
Previously at Veda, I redesigned a large data-processing system around pluggable storage and compute abstractions, reducing processing time by ~96% and infrastructure cost by ~30%.
I prefer small, composable abstractions, explicit interfaces, strong testing, good observability, and systems that are easy to reason about. I work comfortably across code, architecture, infrastructure, and performance.
Culture-wise, I'm looking for high technical standards, direct communication, meaningful code review, collaborative design, and an environment where senior engineers are expected to challenge assumptions and improve how systems are built.
Looking for Principal Engineer, Staff+, Systems Architect, or hands-on technical lead roles.
Having been slipped date rape drugs, I was keenly aware that something was going wrong up until I couldn't form new memories. Apparently I was still talking and acting kinda normal except I kept repeating myself. I couldn't form new memories and eventually blacked out. Thankfully some friends took me home. I couldn't even remember how to get into the car but I was carrying on weird conversations. Is it arguable that I was unconscious, while walking and talking? Maybe...
It's an interesting argument but I think it falls short.
the number of times I've been harassed by police for taking photos... even in small towns in the middle of nowhere people are paranoid.I got popped by our security team, they were convinced I had this malware because my machine attempted to connect to the checkmarx domain.
clearly a false positive but I still had to roll credentials and wipe my machine.
McKenna got deep into this...
At every relevant level, life relies on rotating and cyclic structures coupled through continuous material exchange. The objection to wheels in animals assumes that axles and wheels must be rigid, permanently isolated parts. Biology does not work this way. Instead of discrete components joined once and preserved unchanged, living systems implement rotation through structures that are simultaneously connected, repaired, and replaced.
Cells are full of rotary and quasi-rotary machinery. Flagella are true rotating motors with stators, rotors, bearings, and torque generation via ion gradients. ATP synthase is literally a wheel-and-axle device, converting rotational motion into chemical energy and back again. The fact that these devices operate at molecular scale does not make them conceptually different from macroscopic axles; it shows that evolution favors rotation precisely where continuous repair and material flow are required.
At larger scales, joints function as constrained rotational interfaces. Hips, shoulders, knees, and vertebrae are axles embedded in living bearings, lubricated, rebuilt, and reshaped throughout life. Bone remodeling, cartilage regeneration, and synovial fluid circulation solve the very problem claimed to prohibit wheels: permanent connection combined with continuous maintenance. The difference from artificial machines is not the absence of rotation, but the absence of rigid separability.
Even limbs themselves behave as compound wheels. Gait cycles convert linear muscle contraction into rotational motion around joints, then back into translation. Tendons wrap around bones as belts around pulleys. Muscles do not rotate indefinitely, but unlimited rotation is not a requirement for a wheel; it is a requirement imposed by certain human machines. Biological wheels rotate as much as function demands, then reverse, exactly as many engineered systems do.
The claim that active wheels require exotic motors overlooks that biology already uses fields and flows. Ionic gradients are electric fields. Blood pressure, osmotic pressure, and gas expansion are fluid-based actuators. Electric fish demonstrate macroscopic bioelectric control, and insect flight shows that indirect actuation can drive cyclic motion far from the muscle itself. The distinction between electromagnetic motors and biological motors is one of implementation, not principle.
What evolution did not produce is a detachable, externally replaceable wheel, because life does not outsource maintenance. Instead, it internalizes repair, redundancy, and gradual replacement. From this perspective, an animal is not a wheeled vehicle lacking wheels; it is a dense hierarchy of axles and wheels whose boundaries are soft, whose materials are alive, and whose motion is inseparable from their growth and repair.
Life did not fail to invent wheels. It dissolved them into itself.
> By default, copilot utilizes Claude Sonnet 4. We also support GPT-5 via an environment variable. Run COPILOT_MODEL=gpt-5 copilot to launch in GPT-5 mode. Or on Windows, run set COPILOT_MODEL=gpt-5 before running copilot.
Still, cool website, I enjoyed a few articles there even if this one was very short.
It's not even a multiple CPU board...
This is indeed a pretty standard (and weak) ARM server build.
You can get the same CPU M128-30 with 128 3ghz cores for under $800 USD.
You can throw two into a Gigabyte MP72-HB0 and fit it into a full tower case easily.
That'd only cost like $3,200 USD for 256 cores.
RAM is cheap, and that board could take 16 DIMMs.
If you used 16 GB DIMM like OP that's only 256 GB of RAM, in a server, it is not that much... only one gig per core... for like $500 USD.
Maybe for a personal build this seems extravagant but it's nothing special for a server.
a grill lighter or modified milty zerostat can easily inject faults, albeit more manually and less precision than one of these timed devices. but it's also an order of magnitude or two cheaper...
That kind of absolutism misses the point of why serverless architectures like Fargate exist. It might feel satisfying, but it closes the door on understanding why stateless and ephemeral workloads exist in the first place.
I get the frustration, but dismissing a production architecture outright ignores the constraints and trade-offs that lead teams to adopt it in the first place. It's worth asking: if so many teams are using this shit in production, at scale, with real stakes, what do they know that might be missing from my current mental model?
Serverless, like any abstraction, isn't magic. It's a tool with defined trade-offs, and resource/process isolation is one of them. If you're running containerized workloads at scale, optimizing for organizational velocity, security boundaries, and multi-tenant isolation, these constraints aren't bullshit, they're literally design parameters and intentional boundaries.
It's easy to throw shade from a distance, but the operational reality of running modern systems, especially in regulated or high-scale environments, looks very different from a home lab or startup sandbox.
Fargate isn't just ECS and plain containers.
You cannot use shared memory in fargate, there is literally no /dev/shm.
See "sharedMemorySize" here: https://docs.aws.amazon.com/AmazonECS/latest/developerguide/...
> If you're using tasks that use the Fargate launch type, the sharedMemorySize parameter isn't supported.
if you're running in something like AWS fargate, there is no shared memory. have to use the network and file system which adds a lot of latency, way more than spawning a process.
copying processes through fork is a whole different problem.
green threads and an actor model will get you much further in my experience.
Yes, the answer is yes. lol
see: physics, biology, economics, sociology
more granularly: cellular automata, phase transitions, trophic cascades, scale-free networks, swarm intelligence, the list goes on...
all of this was modeled theoretically before it was observed.
turned the car into a motorcycle.
here's an article with a photo for anyone who's interested: https://archive.is/y96xb
it doesn't seem that surprising to me.
vs
I also recommend "The Sense of Style"--knowing how to wield punctuation and grammatical structure is critical for clearly and successfully articulating your ideas--and I use semicolons, colons, and parentheticals heavily (but en dashes and em dashes are great too).
I find that dashes are great for conversational style flowing sentence structure, but sometimes they can become too long and tiring to the reader.
Remote: Preferred (remote most of my career, comfortable with occasional travel)
Willing to relocate: Not ideally, but open for the right opportunity (would require relocation support and elevated comp)
Technologies: Python, AWS, GCP, Linux, Redis, SQL/NoSQL, event-driven systems, distributed architecture, domain-driven design, CI/CD, observability, data pipelines, cloud-native infrastructure, high-performance computing, AI/ML, and way more (check out my resume).
Résumé/CV: https://gordo.zeneval.com
Email: [email protected]
Principal Systems Architect and Engineer with 20+ years of experience leading architectural transformation across startups and enterprise. I specialize in building distributed, event-driven systems and frameworks that reduce complexity, accelerate teams, and scale cleanly.
Recent wins include:
Reduced code volume by 99% while adding new functionality
Cut processing time by 96% through pipeline re-architecture
Lowered infra spend by 30% via performance tuning and optimization
Slashed deploy times by 75% with build concurrency and IaC improvements
Halved migration effort by automating brittle legacy refactors
I'm a systems thinker and strategic enabler. I wear many hats: architect, engineer, mentor, advisor, and have reported directly to CTOs, CEOs, and Directors of Engineering. I've built reusable frameworks, abstracted chaos into clarity, and embedded architecture as a shared discipline. I help teams move fast without incurring a future they can't afford or scale.
I prefer high-leverage roles in infra, platform, data systems, or technical strategy. I have deep health tech experience, but I'm generally open to other industries (NO adtech, NO crypto, NO AI/ML nonsense)
Targeting $300K+ total comp. If you're burning >$1M/year on cloud infra, I'll likely be able to save you that, and then some. If you're offering less than 250K base, don't waste my time please.
did you switch out the client or something? maybe the problem is not using pluggable adapters? is your business logic coupled to the particular database client API? oof.
I know the cluster clients are different (been there, done that) but hundreds of hours, seriously? or was that just hyperbole?