Dion Almaer

Software, Development, Products

Cultivating a Durable Championship Caliber Team

Manchester City just became the first team in history to win the Premier League championship four years in a row, with the chance to win the FA Cup this coming weekend. They are a dynasty, with 6 premiership wins in the last 7 seasons and many other trophies including the coveted Champions League.

I enjoy looking at sports as an analogy to business, and watching Pep Guardiola manage his team to success whilst making constant changes definitely hits home with what I have seen at my companies over the years (and what I haven’t seen!).

Long Term Success

I have seen two extremes when it comes to building a great team.

  • Extreme 1: Hire the best people and let them do their thing
  • Extreme 2: Build the right systems and the rest will follow

I have come to learn that the best long term results come from multiplying the two in certain ways.

When I look at what Manchester City have done for this long term success, it stems from a large number of ingredients, many of which are flywheels to each other.

Recruitment

They are constantly bringing in amazing talent into an already high quality and substantial squad. They never rest on their laurels here, with the example of Doku coming in right after Jack Grealish to have strong backup and competition on the left flank. Always Be Recruiting.

The Money Machine

Recruiting great players requires funds. The financial fair play system in the premier league is a joke, but requires that you are getting revenue in every possible way (sell those t-shirts!) as well as selling players wisely. Man City has the highest wage bill in the league, which means it has the best chance to have the best squad. How can you recruit top talent?

Setting The Bar

The culture has to drive everyone to be the best they can be, as individuals helping the overall team. Senior players need to show new players what good looks like, and how they need to work to reach it. Manchester City players work their arses off on the field. They don’t sit there with ego and think they can do anything else, which happens with some clubs and players who think they are the bees knees. 

The right mix of senior and junior is critical, and the changing room is where a lot of things get worked out. The manager doesn’t do all of the work, a lot happens through the senior players!

How is the bar set on or across your team?

Style Of Play

Teams have a “style of play”, and clubs such as Man City and Liverpool do a fantastic job of driving this though out all levels. When you have your academy driving this style into the youngsters, they have the best chance to break through into the first team. We saw this when Liverpool won the league cup this year with many of their academy players starting due to a huge number of injuries. 

How are you defining and driving a style of development throughout the company?

Individual vs. Team Tactics

Without a style of play framework you still need room for tactical tweaks depending on the individuals in the team and their strengths, as well as the opposition that you are up against.

The style of play is so strong, that many admire the fact that even when Erling Haaland and Kevin De Bruyne were injured, Phil Foden and Julian Arvarez fit right in to continued success. They are very ers.different players, and Pep tweaked the system to make sure the overall team was setup with these players in those positions. This is where the art comes in. 

How are you balancing a team that can flex as personnel come and go, and making sure that individuals bring their strengths?

Time to Peak

A season is long, and just as the best trainers have their horses peak for the big races, you need to think about keeping the team healthy over the long term, and knowing when you need to peak. For example, when I was at Walmart, we knew that Black Friday and the holiday period wasn’t going to move for anyone. ~80% of all revenue comes in that period, and thus we need to be ready for that time. Elsewhere, you may have Conference Driven Development or other deadlines that you feel you need to peak for. Manchester City famously makes sure that they are close enough to strike in April, and finish through the posts really strong. What is your cadence and how do you stay a healthy team?

Aligned to the goals

How do you stay hungry? After the third premier league how does the team get up for putting in all of the work that they know is required to start again? You need to align the purpose as much as possible. Does your team know why you are all gathered to do this work and why it is important?

Where I have seen things gone wrong

I have learned through mistakes and observations where one of the extremes has been ignored to ill effect.

All people, no systems

At Walmart, one of my regrets was how I didn’t make sure that certain systems were in place. This resulted in far too much hero culture, and when the heroes moved on, there wasn’t resiliency in place to be able to handle things. We hired great people, but didn’t have a system for the long term.

All systems, not thinking people

I am now seeing many mistakes when it comes to layoffs that are far too much about systems and ignoring the fact that the humans involved aren’t all equal.

I recently spoke to an engineering director who had 35% of their team laid off, but with the “good news” that they have the HC back but only for hiring L4s in India. They didn’t have a say in who was leg go, and shockingly it included some of the most productive members of the team with deep knowledge locked in their heads.

Instead of giving full ownership to a team in India, they now have to deal w/ managing with a team across many time zones. Penny wise, pound foolish. I am so curious why leadership is giving “Strat Ops” teams spreadsheets to normalize wrt HC.

I know of other leaders who play with config files that allow them to change the wingspan of a manager to reports ratio. No nuance allowed.

I am excited to make sure that at Augment we grow at the right pace, and work to have the talent density that allows smaller teams do more, and cut out communication costs and hierarchy that massive teams often cause. One of the reasons I am so excited for what we are building at Augment is that I really believe it can help keep teams small by allowing the conscious creatures the ability to do what works best for them, with help from our 24/7 available computer systems.

Durable Success = The Best Set Of People * The Right Evolving Systems

Introducing Augment: a company dedicated to empowering developers with AI

I’m incredibly excited to share that Augment, the company I joined to help empower developers, has come out of stealth.

With a lot of FUD around AI taking all of the knowledge worker jobs, including those of developers, I believe it is important to get across the counter argument:

“Don’t fire Kevin for Devin just yet. Augment Kevin with super powers!”

Me

If you think about what software engineers actually do and what AI excels at, you should reach the same conclusion. It’s easy to anthropomorphize AI tools, especially when you’re chatting with them and considering their portrayal in science fiction. With that in mind, I believe in creating systems that resemble J.A.R.V.I.S more than HAL.

As we develop these systems, it’s essential to remember that humans and computers have unique strengths. The real magic happens when humans take charge, supported by ever-present, fully connected computer systems.

By doing so, we can not only improve life for developers individually, but also empower teams and organizations to accomplish much more with reduced toil and communication costs.

I’m passionate at doing my part to help here, and I want to share my journey to Augment with you.

Seeing the future of software development

I love programming. Whenever I write some code, it tends to be a good day. There is something about the creative process that ends with something tangible that is good for my brain. Any platforms, tools, or services that allow me to stay in that certain flow of development become favorites. There is an art to taking an idea, breaking it down, and making progress.

The longer I am on the path to running code that works – or getting effective help back onto the path when it isn’t working – the better I feel.

On the flip side, whenever I am doing something that feels like toil, or I feel really stuck, the worse I feel.

There have been a couple of times when I saw how AI technology could dramatically help:

  • I worked with a research team inside X at Google who built models (in the pre-LLM/transformer days) that could help the highly skilled SWEs keep up with the constantly evolving monorepo. This was often very boring work, ripe for a computer to help.
  • I worked on a project at Shopify that uses LLMs to bridge the complexity of GraphQL for developers wanting to integrate with merchant data. This quickly taught me lessons, such as:
    • It’s easy to show a cool (somewhat contrived) demo
    • It’s hard to build something great that works at scale in the real world
    • One LLM isn’t the answer for all use cases
    • It’s not just quantity… quality data matters
    • Having a system that can really do well wrt evaluations is vital as you iterate

Projects like these gave me the evidence to see how software engineering is going to radically change in the future, and pairing AI technology with developers will be the driver.

Meeting the Augment team

I was sold on the opportunity that this AI wave could allow us to help developers in new expansive ways. I started to explore, and this exploration lead me to chatting with a couple old friends, Luke Wroblewski and Sam Pullara who are building companies at Sutter Hill Ventures, a pretty unique VC firm.

Luke and Sam grinned as I spoke about my desire to build for developers with AI, and quickly introduced me to the founders and team behind Augment.

I met Guy Gur-Ari, the co-founder leading the research efforts at Augment. He had already assembled a team of AI researchers and engineers who had many years of expertise with ML and how it can be applied to code. This was important to me, as I had found that to build something truly great, you need the ability to make changes across the entire stack. You want to be able to change the engine along with the other parts of the car!

Igor Ostrovsky, the other co-founder and pioneer of Augment, also gave me a lot of faith that we had the broad technical expertise to pull this off at scale. His proven track record with distributed systems as Chief Architect of Pure Storage, developer focused work at Microsoft, and his deep dive into AI as an entrepreneur in residence with SHV was inspiring.

Then I discovered that Scott Dietzen had joined as CEO. I first met Scott at the birth of enterprise Java, where he was CTO at BEA WebLogic, my favorite app server of choice.

As I met the broader team, I had a strong feeling that this was a team with the focus, experience, and skill to take a shot at building the best AI platform and ecosystem for developers.

The team had gone deep in building foundational technology that is needed to solve the meaty problems that developers have, especially at scale. These include building a system that:

Has an expert understanding of large codebases

There are solutions out there that feel like you have access to a system aware of core technology. They have a solid understanding of programming languages, and popular frameworks.

When using Augment, we want you to feel like you are working with the joint intuition of your most seasoned engineers at the company, and those with deep expertise on the dependencies that you use.

Any suggestions need to reflect the APIs and coding patterns in your company’s code so your team can use it on your actual day-to-day work.

Produces running code

The custom AI models and infrastructure are tuned for code and coding use cases avoiding frustrating hallucinations and focuses on improving code quality… not just productivity.

Operates at the speed of thought

There were many search engines before Google, but I remember trying it for the first time, and seeing how the experience was a step change. The quality of the results were next level AND the speed to return them felt different.

Working with LLMs can be a lil… slow, which massively degrades the experience and can keep knocking you out of flow.

The team had built a fast inference — 3x faster than competitors — built on state-of-the-art techniques, including custom GPU kernels, and I felt the difference in the experience.

Supports multiple developers & teams

Software development is a team sport. There are so many areas where technology can help scale and improve the use of best practices across a team, help you learn a complex codebase, and get new engineers onboarded faster.

The scale of computers allow a system to attend to do much more, and they are available 24×7.

I have learned the power of small teams. We have seen with early customers that the shape of teams can change when you deliver the right capabilities. If we can enable smaller teams to do more, and for teams to do more in parallel, we result in better software and happier devs to boot!

Includes strong IP protections

Your company’s source code is precious. Augment was designed from the first line of code for tenant isolation, with an architecture built to protect your IP.

Try Augment

Joining Augment has already been a blast. Moving at startup speed with a great crew all focused on helping developers is a dream come true for me. I feel very fortunate to have the opportunity to go after this problem space with a small (but growing! Join us?) team.

We are heads down delivering on our promise, working closely with early access customers, who have been a key part of our product development thanks to their fantastic feedback (thank you!).

We are furiously working our way to a public product launch that we can’t wait to share.

Until then, if you are interested in kicking the tires early, please sign up for the waitlist!

Building AI Dance Partners (and your role as a good lead!)

tl;dr LLMs give computers new abilities to be better partners for us humans, and if we build the right systems we can transform how we work together. I have learned some lessons on the building side, but also on how to do more as an augmented human to get the most out of this new world!

A dream stirred me from my sleep. I found myself on the set of ‘Dancing with the Stars,’ but with a twist: my partner was not human, but a robot. As I lay there, half-awake at 3am, I pondered the meaning of this mechanical ballroom dance. Then it clicked… it was a metaphor for the work I’ve been deeply immersed in at the close of 2023: creating computer systems that augment human capabilities, giving developers and their teams superpowers in software delivery.

The Dance

I’ve always believed in the power of combining the best of both worlds: human creativity and computer precision. The best user experiences have always weaved brain and tool, these days including those that are digital.

LLMs have changed the game in that precision has a brand new capability: a new layer of intuition that we can tie to. A way to combine my Systems 1 and 2 brain with a mesh of combined thought. Back in the dream, my subconscious was painting a picture of the ideal partnership where the human mostly leads, and the machine follows in a tightly choreographed back-and-forth. Just like picking up a tool such as PhotoShop, it can still take time to master the steps, and the dance changes as the capabilities change. How can we best use the strengths and weaknesses of each partner so that they work as one?

Crafting the Perfect Partner

I’m currently iterating on a dancer that developers can shape into the best partner possible. Speed and skill are crucial. A slow computer is like a dance partner with two left feet, disrupting the flow and making collaboration frustrating. Skill, on the other hand, is about quality and finesse—leading without stepping on each other’s toes, sharing knowledge to maintain the rhythm.

The Car and the Engine

I was excited to join a Sutter Hill Ventures startup for many reasons, and my expectations have been very much exceeded. Not only do we have a solid financial backing that allows us to really focus on building a game changing product and business, but the support that the Sutter Hill team has is special. I get to work with my favorite UX person there is. The enterprise sales playbook is ready to run. And on and on.

The team itself (founders, CEO, and everyone else!) is not only world class, but there is a strategic bet that I strongly believe in for building the absolutely best product. The heart of the team has AI researches who deeply understand every part of the stack.

It’s one thing to build a car using someone else’s engine; it’s another to be able to fully tinker with that engine or even build your own.

In 2023 we have learned so much as a community. First we had the transformational moment when developers got to poke at what could be done with OpenAI APIs (and then so many more). There was the prompt engineering, RAG’ing, and pushing the boundaries of what’s possible.

Embracing Constant Change

The model tier is just the beginning, and going from demo to a production system requires a world of work to be done around it.

New models and research are popping up on a daily basis, so how do you filter out what could be helpful? How do you determine its utility for your specific needs? How do you ensure your data is accurate and current? Are your evaluations truly reflective of quality, or are you just fitting the last piece of a puzzle?

Metrics

Measuring what matters here is hard. For example, with coding tools, I often see discussion around the amount of codethat is created, or the Completion Acceptance Rate, but when you watch this play out in practice with your users you realize…. wait a minute…

Do we want to always be creating code if it’s adding entropy into the system? If that code is iffy, and if the human can’t tell, then maybe we are adding problems. And, wouldn’t it be nice if we maybe could… delete code and simplify?

For completion acceptance, I can get very different results by changing the system to vary the amount of code that comes back, or the latency, and many of the habits that you build with the developers. The habits have been really fun to watch. Seeing cohorts that start by waiting for the system to do things vs. communicating more and moving quickly.

And when I do side by side comparisons, I see the huge difference where one system can have a hire acceptance rate that ends up with code that doesn’t run. Don’t I really want to be tracking time to running code that is high quality?

Here’s to 2024

We are somewhere in the journey that is akin to constant improvements that we can see with other tools such as Midjourney.

I’m grateful for my team’s collective ability to build everything needed for the ultimate coding dance partner. We are building the platform that enables the building of this partner, to iterate on it, to take in the innovation from open source and our own research, and man I’m having a great time doing it.

I can’t wait to share it with more of you. If you’re a developer who spends most of your day coding, enjoys giving feedback the moulds a product, and are interested in getting early access, I’d love to hear from you.

Happy New Year, and may this become true!

NOTE: Of course, this article was written by both Dion Almaer and the dancer within Type.

The right thing to do, is the right thing to do.