Up in the air

We are in a phase where planning becomes quite difficult. ChatGPT has started a capitalistic AI war. Microsoft swept in to shepherd commercialization. Google is on the back foot for now. Amazon will launch something I have no doubt. ChatGPT style tech would make Alexa viable by solving the fractal conversation problem. 

The players are moving, immense amounts of capital has been unleashed. But for us on the outside it’s a difficult time. You can’t really plan for the future. Because the technology is advancing rapidly and is already transforming jobs in various industries.

GPT-4 has been in the news, but Midjourney has quietly advanced to the point where it is transforming job tasks in the graphic design industry. I read a complaint by a graphic designer this weekend describing how his job has become more prompt engineering than graphic design. Instead of needing to draw things he and his peers can now use AI image generation and then clean it up in photoshop. 

Video created by demonflyingfox using MidJourney V4.

In 2022 I ordered physical versions of two AI generated images that I thought were incredible examples of what AI could do. In 2023 these images are somewhat quaint. AI image generation can do so much more now. 

We don’t really know where things are going. How do you prepare exactly when the potential paths are so divergent? 

Some people claim AI will replace programmers. Others say we will never not need people to dig deep into the technical details. Personally, I lean towards the second. If AI coding hasn’t peaked yet we will likely see a 1000x increase in the amount of code being written. ChatGPT is quite good at explaining things but will it be useful at explaining interactions between multiple programs it has written? We can’t know at this point. 

Image of a line going exponential. Credit to Luke Muehlhauser who created and watermarked this image.

We are in the straight line at the far right now. We’ve discovered something about meaning in these large language models. A mapping between language and image, and mappings between language and language. It’s not AGI, but much like Deep Blue its obviously eclipsed human capabilities in some way. 

Neal Stephenson’s ‘The Diamond Age’ is a book I was intrigued by in my younger years. In it a girl is given a AI powered book which acts as her tutor from a very young age.  Much like that fictional book ChatGPT likely will become every child’s tutor going forward. Much like the iPhone, you won’t be able to buy a better one. Children have already used ChatGPT to make homework and writing assignments obsolete. The education system likely will not survive this advancement. 

The sum total of human knowledge has been put into this machine. Everyone who ever wrote anything is part of it. Buckle up. Don’t panic. Hold on. Let’s see what happens next.

Agile has gone from ‘people over process’ to ’no process’

In practice ‘agile’ means ‘we have no process in place and each team does whatever random thing the manager wants to try next’. Sometimes that is SAFE sometimes its SCRUM, usually it’s a combination of different things. This isn’t necessarily a bad thing, but there are trade offs. 

The first is standardization. If every team follows a different process it’s difficult to understand what is going on at a management level. Which teams are productive? Which teams are in downward spirals? If you don’t have a standard to judge against you can’t find out. 

Secondly, away team work is much harder. Working with a team that uses the same development process, pipeline setup, programming language and frameworks is easy. On the other hand working in the code base for a team which uses a different language, framework, architecture, etc is very difficult. Not supporting away team work severely limits your ability to integrate internal software components.

Thirdly, Estimates are not possible in this kind of environment. Since the process changes constantly historical data becomes useless. In response to this most companies don’t even keep historical data. The main use for estimates is ensuring that ‘burn down’ charts follow the 45 degree angle managers love. 

https://www.estimating.dev/there-is-no-team-calibrating-teams-vs-individual-estimators/

Subjective expert predictions are a valid form of estimating software tasks. But if you don’t have historical data to calibrate against estimates devolve into gaming the system. 

When you change how estimates are made, when tickets are considered done and the sprint cadence every 3-6 months there is no way you can have cross company data on productivity. The lack of process empowers management to obfuscate the productivity of their teams. The pursuit of the best process gives technical organizations a great excuse as to why they have no idea if their processes have improved over the last two years or not. 

In this type of environment all judgements have to be made based on subjective gut feelings and corporate politics. You don’t know which VP’s processes are better than the other because neither has any accountability. You don’t know which technical department is more efficient because neither the estimates or logged hours can be trusted. 

‘We’re being agile’ has become the excuse to follow whatever process you want. Instead of ‘people over process’ it has become  ‘no process’. 

When creating processes (mechanisms) its important to consider who benefits

A business process is any procedure that is done manually by employees. In the software engineering environment this includes everything from code reviews to standup and 1 on 1s. 

Compliance with processes involves education, incentives and punishments. People need to know about the process to follow it. And if you don’t attach incentives to the process, negative or positive, people won’t feel a need to follow it. 

A common cycle I see is that management will think of a new process which could solve a problem the development organization is facing. They then declare the new process and are surprised when later on no one is following the new process. 

When designing new processes it’s important to consider who benefits from the process. Additionally, it’s helpful to contrast who benefits with who is required to implement the process. Are the same people benefiting from the process as the people expected to implement the new process? 

Your job as management is to create and enforce the business processes the team follows. Typically, this is best done with buy in from the team but the buck stops with middle and senior management. So it’s important to review what processes you tried to implement and how it went. 

What pain points did we try to address with new manual processes this year? How clearly did we define the new process we wanted to implement? Did the team follow the process as expected? Who’s pain point did the new process address? Was it the development team? Was it the product team? Was it the management team? 

Typically, people do not need incentives to follow processes which benefit them. But getting people to follow processes which do not benefit them is much more difficult. 

Take the example of sprint burn down charts. These charts provide utility to project and management team members. But they rely on the engineering team members to update tickets consistently. 

The conflict comes In because burn down charts provide zero benefit to engineers but all the work to support them has to be done by engineers.

This creates a dynamic where engineers are always incentivized to reduce their time commitment to updating tickets while management is frustrated that nobody is updating tickets.

You can of course make updating tickets the primary job task for engineers to fix this issue. But then instead of developing features, updating tickets becomes the primary job responsibility for the engineering team. Not what you want in a development organization.

The problem is that you have a fundamentally extractive business process. You need some group to take on extra work duties to improve the situation for another group. Having good reporting on the state of development tasks is an important thing for engineering organizations. But when designing processes to achieve that goal it is important to think about the process in the correct context. 

Being one sided is not a bad thing in general. Businesses are fundamentally about generating profit. If we need an extractive process to make money then it is justified in the context of the business. 

However, ideally we want to avoid these kinds of processes. We want to create processes which align the value produced with those doing the work. Because people enjoy following processes more when there is something in it for them. It makes their jobs easier and as a manger it makes your job easier because you don’t need to police whether people followed the process. 

I’m excited to announce Sledgeconf 2023: architecture success stories.

For the next sledgeconf we will focus on software architecture success stories. 

What does architecture success mean? Software architecture is the way we structure our software programs. A successful architecture enables us to support user requests, integrate improvements all while making it easy for the engineers working on the project. 

A bad architecture has to fail in some major way. It might have simply not worked once it was built. It might have made it hard for maintainers to fix bugs. it might have been too expensive to operate. 

They say that all happy families are alike, but at Sledgeconf 2023 we ask “Are all happy architectures alike?” 

If you have a software architecture that worked that you be willing to speak on let us know! We are looking for speakers for Sledgeconf 2023!

Tentative date May 12th 2023

https://sledgeconf.dev

Trying a new language won’t solve your development problems. 

I’ve had a conversation where someone proposes trying a new language like Go or Scala or Typescript for new development several times. Typically, the argument is that we have problems x, y and z with our current language and they would all be better under $new_language. The arguments are always things like x has better performance, y has better typing, z is more functional. 

There is no free lunch within modern programming languages. There are no opportunities to switch to a new language without paying new costs. Java requires a lot of boiler plate and is very heavy weight. Typescript is async by default and has non-reliable typing. Go has a litany of problems (tool chain, exceptions, generics, etc) downstream of Google making all the serious decisions for the language. Rust is very strict and gives you excess performance you can’t use. 

Switching between any of the modern languages means trading some benefits for some negatives. Unless you have a serious problem with your current language you are unlikely to gain anything. 

An exception is switching from Ruby, or Python to something like Java or Go. Then you would gain a lot of performance. But first ask yourself whether any of your services max out a single server. Are you even using instances larger than your laptop? Can the performance problem be solved by a refactor and re-architecture in the same language? Re-writing is time consuming and if your team already knows Ruby a re-architect in the same language will usually be faster and produce better code. 

Programming languages have trade offs. Switching is an expensive process. It always takes longer and costs more than you expect. And after it all by switching languages you are just switching old problems for new problems.