A LinkedIn post recently estimated how long it would take to convert the world's 800 billion lines of COBOL to Java. The post was well done — sliders, scenario modeling, a full SDLC phase breakdown. It also made the problem feel insurmountable.
The notion that AI makes migration trivially easy has done genuine damage.
Three levels of AI maturity for mainframe modernization
The wave of AI-driven code modernization tools is here.
Figure out orchestration, and the world is your oyster.
Finally, some downtime for holiday reflections about the state of affairs in mainframe modernization.
Mainframe modernization exemplifies the wicked problem: it resists precise definition, has no clear end point, and every attempted solution reshapes the challenge itself.
Systems are the living records of the people who built and maintained them.
Ingo Wiegand joins Mechanical Orchard as VP of Product.
“The continuum is that which is divisible into indivisibles that are infinitely divisible.”
Even on the way to that glorious outcome, lifting thine eyes from mere code conversion yields perhaps an even greater value: control in undertaking a highly uncertain task.
We must have some sort of way to measure value, especially, say, when making a multi-million dollar, possibly years-long commitment.
A good craftsman knows how to use a tool; a great one knows when not to.
It’s easier to have faith when things work in non-mysterious ways.
Quick: what’s the formula to calculate the volume of a cube?
Bolting GenAI onto a sub-optimal approach is like putting a jet engine on a Conestoga wagon.
Five predictions about legacy modernization in the year 2035.
Quality and malleability of software matter to everyone, but in the face of immediate demands (triage modernization, shortcuts for political expediency), they’re often an afterthought. Until tech disruptions—like AI—come along.
When it comes to modernization success, the objective is as crucial as the approach. End-goals that focus on stopping the pain or ticking boxes can only get so far… if they get anywhere at all.
This issue explores how software’s original purpose became recalibrated to just another cog in the production line—and how a path forward might lie in socio-technical design.
Like early attempts at human flight, successful digital transformation requires understanding the forces at play. Master those forces, and the sky’s the limit.
Three-fourths of all legacy modernization projects fail. How can Mechanical Orchard feel confident in the face of a record like that?
Modernizing legacy systems should begin with comprehension: in this vast monolith of tens of millions of lines of code, what does what? The more critical the system, the more important comprehension is.
Many companies view “digital transformation” as a chance for a gut remodel of a house. But systems aren’t static: they’re moving, living systems that, btw, are working.
In last month's newsletter, we discussed the difficulty of getting started with modernization projects despite the empirically low confidence level for success.
Following our successful Series A round, we’re proud to announce that we’ve appointed Edward Hieatt as Mechanical Orchard’s Chief Customer Officer.
“There is only one way to eat an elephant: one bite at a time.” Attributed to notables ranging from St. Francis of Assisi (whose elephant-related credentials are a bit suspect, tbh), to Desmond Tutu, the meaning is obvious: any task, no matter how challenging, can be tackled bit by bit.
Mainframe computers are still widely deployed. At the time of their adoption (in some cases over half a century ago), mainframes were cutting edge technology.
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