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Software Factories for Real Engineers - rlscorner - 10-29-2026

[Image: 6618de08be54578e1d88103b5c7cb367.jpg]
Software Factories for Real Engineers
Released 10/2026
By Matt Pocock
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 38 Lessons ( 2h 58m ) | Size: 1.6 GB

Use your Real Engineering skills to ship code at scale and maintain a self-improving codebase

Let's talk about the real promise of AI coding, and how you and your engineering team can cut through the hype to do more of what Real Engineers actually care about: building better software.

The simple truth about coding agents is that they're entropy-generating machines. Even in tiny code bases (even in one-line changes), the agent can produce garbage. They don't think, they don't have judgment, and so it's so easy for agents to produce rubbish. even really smart, powerful agents, even with the latest harnesses.

This is why there will always be work for engineers: systems are big and complicated and messy and human, and coding agents by default can only chew on the problem you place in front of them and they can only see the narrow little window of what they're working on. They can't "get the big picture" unless you give it to them.

So, if you just sit down and start using a coding agent, you inevitably find yourself in an unpleasant position

You're a Bug Catcher: you find your role reduced to code review and bug-finder
You're a Babysitter: you spend all day juggling terminal windows and switching context, correcting and giving feedback live, as it happens
You get Brain Fry: You end your work day feeling like spreadable goo
Not to mention the waste of time and tokens.

And slop. Slop is always a problem.

But there's good news

Quality, reliability, and waste (of time, tokens, and brainpower) are engineering problems.

And that means you can find engineering solutions to each of them.

Even better, we don't need to start from scratch. We can look at decades of the best engineering thinking (the rules and practices that work with huge human teams, like DDD, deep modules, tracer bullets) and adapt them to build a system that actively helps you by anticipating problems, solving emergent ones, and cleaning up after itself.

Classic Concepts + Coding Agents
Earlier this year, I was thumbing through the classic programming books where these battle-tested ideas originated. Books like The Pragmatic Programmer, Working Effectively With Legacy Code, A Philosophy of Software Design.

I found myself nodding along, and realized that while everyone was saying we need to throw out the old rules because "AI changes everything" these classic engineering concepts were exactly the solutions to slop.

With these ideas fresh in my mind, I found it was entirely possible to.

Automate low-end tasks
Delegate well-spec'd work to a system you can trust
Assign your coding agent to chew through tickets, and come back to clean code and informative PRs for your review
Spend more time on the strategic thinking that really matters
Tackle optimizations and refactors your team could never find time for before
Increase your and your team's codebase and domain knowledge
Make your large, complex, evolving codebase the best it's ever been
In the real world: with a team, with brownfield codebases, and with a budget.

In other words, you can build a working Software Factory.

One where you can elevate your role

Without a factory
Bug Catcher: your role is reduced to code review and bug-finding
Babysitter: you juggle terminal windows all day, correcting the agent live
Brain Fry: you end the work day feeling like spreadable goo
With a Software Factory
Strategic Thinker: your time goes to the strategic thinking that really matters
Skillful Delegator: well-spec'd work goes to a system you can trust
Real Engineer: you wrap up the day relaxed and satisfied
It's not easy or obvious how to get to this level. It's certainly not a feature of coding agent harnesses: /goal simply will not get the job done.

And most of the folks who talk about closing thousands of tickets in a month work at AI labs or companies with unlimited tokens. It seems like even when it works, it's still a fantasy.

But this is an engineering problem. And you're an engineer.

I've already helped thousands of engineers like you apply a Real Engineering approach to AI coding, achieving excellent quality using my Real Engineering Loop. And this is a fantastic approach for new projects, exploratory work, and highly complex moving parts.

But it's not necessary for more mundane stuff like stacks of tickets. That's where a Software Factory approach can really shine.

I've built and battle-tested a working Software Factory.

And in my brand new 2-week cohort course, you'll learn how to do it for yourself.

Code:
https://rapidgator.net/file/3f8deef58f250b31d30617ee5159da8b/Software_Factories_for_Real_Engineers.part2.rar.html
https://rapidgator.net/file/8a94b5417f9334d70cf6e97ad3fac674/Software_Factories_for_Real_Engineers.part1.rar.html

https://nitroflare.com/view/AB7236CBD0C3F40/Software_Factories_for_Real_Engineers.part2.rar
https://nitroflare.com/view/CA48EBF3B357FDE/Software_Factories_for_Real_Engineers.part1.rar