Top Tech Investment Themes

Major investment themes that I believe are going to redefine technology (software) investing in the near future.

I’m still refining what writing means to me - I’d love to hear from you so please do comment below. Also, if you like what you read and feel others would do, please do let them know about this post!

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After a hiatus over the past few months driven by a huge number of changes personally, I’m back. I have been spending a lot of time thinking (in general!) but specifically about where software is heading, and which types of approaches investors should be focused on. I’m deliberately staying away from looking at any particular vertical sector and thinking more broadly about the themes that will redefine how the world operates from a tech perspective.

A Primer on Edge Computing – mc.ai

  1. The simultaneous abstraction of DevOps capabilities into software engineering teams for cloud native applications and alongside, the actual deployment of either an entire cloud native application (or separate elements of a cloud native application decomposed into separate services) in a ‘serverless’ fashion. Infrastructure as code / functions as a service. On a related point, the move towards optimizing the performance and reliability of cloud applications through edge based compute, supplementing centralised processing. 

Why does this matter?

  • With serverless infrastructure, can achieve meaningful savings on personnel (reduces need for DevOps by at least 50% on average based on personal experience) and bring developers closer to the infrastructure of deployment of their applications. This really helps with creating better applications and improves deployment practices (continuous integration and delivery of code). 

  • I have found that acquiring these types of skills are extremely motivating to software engineers as there is recognition that programmatic application deployment experience will be critical in the near future. 

  • Serverless deployment allows for smaller teams to develop and iterate products faster and more importantly, also forces the correct assessment of system architecture upfront so mitigates against technical debt. Cost of software development staff, their productivity and amortisation of technical debt are usually the biggest expenses in software development. 

  • Edge allows for more sophisticated data processing capabilities to be applied in smart endpoint devices, leading to better quality intelligence with lower overheads. 

  • Software design complexity is increasing given the move from monolithic software architecture to services or microservices architecture, leading to greater need to orchestrate the deployment of all the moving parts. 

Listed examples: Cloudflare, Fastly. 


  1. B2B organizations with software products / horizontal infrastructure layers that can service multiple infrastructure needs, have platform type capabilities and an engaged community of developers around them. 

Why does this matter?

  • Product development and release cadence tends to increase exponentially if software products can be built upon an existing platform, or if services can be reused or packaged together. This can only happen in rare circumstances where overall software architecture has been extremely well thought out and marketing and product teams work well together to iterate around client feedback / experiences.

  • CIOs / CTOs are inundated. At the same time, they are expected to optimise for quality and cost. Anything that simplifies their decision function will be something that they will gravitate to. Procurement management is a huge headache and with the proliferation of *aaS tools, rationalisation of vendors is a meaningful trend. Furthermore, if the vendor already has support from ground up, the decision process is even easier. 

Listed examples: Elastic, Snowflake, Jfrog, Cloudflare, Unity


  1. B2B, B2C or B2B2C platforms that have underappreciated capabilities to add on adjacent capabilities to further monetise their existing customers / or attract new customers. In particular focusing on platforms that are adding fintech capabilities. 

Why does this matter?

  • Consumer behaviour is becoming primed to engage with a limited number of counterparties, and do more with them. 

  • Financial services capabilities (distribution and/or origination) is one of the best ways to accelerate customer relationships. If done correctly, can be extremely high margin without a significant amount of contingent risks and lead to greater insights about customer behaviour. 

Listed examples: Alphabet, Square, Facebook, Tencent, Peloton


  1. The accelerating unbundling of public cloud services. 

Why does this matter?

  • Increasingly, companies are looking to reduce their reliance on a single cloud services provider to prevent lock-in. At the same time, the higher margin, value added services have largely been under-invested in and companies with specific focus on these problems can perform these functions far better. 

  • Given the scale of public cloud spend and ongoing migration to the cloud, this is a massive and growing market. 

  • Services tend to be non trivial problems such as network perimeter security, unique database provision, data analytics, performance monitoring and analysis. 

Listed examples: Too many to list but the likes of MongoDB, Elastic, Splunk, Datadog, Snowflake, Cloudflare.

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