The future of 10x Execution
Startups are one of the hardest things to build. If you’re reading this, you’ve been there - Most times it feels like learning to fly a plane while you're trying to build the wings. One of the reasons why many feel that way is because operators feel a strong need to take on everything and hardly delegate some of the core operational duties. Some of it is because many things need a founder’s touch - many times because there is no one with the skill-sets and the attention to detail to delegate it to.
I’m here to make a case that it does not have to be that way. This post is structured as a thesis and is estimated to be about a 5-minute read.
The hard things about hard things
Strategic execution in the modern world requires a multi-disciplinary approach.
Need: Founders and Operators need to be good at a lot of skill-sets/domains to navigate a complex business environment
Challenge: To be competitive, Operators today have to hire for these specializations from a competitive market Ex: Marketing / GTM, Account Management, Ad Optimization, Financial Modeling, etc
An Operator’s most valuable resource is their time, their time dictates what gets attention and what passes their bar for excellence.
Need: Company building especially at the early stages needs tactful allocation of one’s time especially when context switching costs are very high.
Challenge: Since time is limited, Operators today tend to focus on a very limited scope of items and then, at least in some cases delegate the rest, which usually produces uneven outcomes.
Being diligent about OPEX spend is top of mind for every Operator, however, we live in a world where you get what you pay for.
Need: Operators have to balance the now and the future when it comes to hiring and adding skills and capabilities to their team often with uncertainty about the future environment
Challenge: Good quality talent is expensive for a reason, they give you a leg up on your competition but also add to your opex. Often when it comes down to it - 9 out of 10 founders in the early stages choose to upskill and take on the task themselves.
A paradigm shift in how work is done
Talent is distributed around the world but opportunity is not.
In the last few years, remote work has become ubiquitous in how work gets done. This has also meant that there is now a diverse talent pool around the world that is not just a technical or back office resource but has also created opportunities for smart business background executors to apply their knowledge and skills to the best companies in the world. Given these resources exist in LCOL countries, the cost arbitrage is very attractive to employers in HCOL countries.
The advent of Generative AI
Within the last year advances in generative AI have managed to condense the knowledge of every piece of content created, every discussion had, and every public piece of code written into an interface that anyone can “talk” to - to get really deep insight about a problem or a subject. What this has done is significantly narrowed the gap between a generalist who has an understanding of the macro picture of a domain and someone who has developed deep skillsets with experience and training - after all, the answer is just a well-constructed question ( prompt ) away from being a good enough strategy. This technology is expected to become more accurate, cheaper, and integrated into almost every workflow in our lives.
The evolution of Generative AI and Knowledge Retrieval systems
Even with all the major advances in text, vision, and other modalities in Generative AI, there is still a long way for the technology to go - to be able to be accurate, trustworthy, and have the rigor of explainability for high-consequence decisions. While we truly believe that the world will be here one day, today’s systems are relegated to information systems that integrate within the world of internet-connected services Ex: Zapier, AWS, your favorite CRM etc. While advancements are being made here, there is a strong need for a well-rounded domain generalist to be the guardian of “alignment” and implement the physical aspects of execution.
Execution workflow 2.0
My co-founder and I have worked on several startups for the past decade - more have failed than succeeded, but the last one we launched and exited through 2019-2022 did feel very different given the seismic shift in how work was being done during and post the pandemic. Three things helped us get more done with less - with a lean team on a budget that wanted to move fast.
Affordable Remote Talent Options
Our team was 100% remote. We used remote talent across engineering, marketing, content creation, bookkeeping, and everything in between.
Challenges: Vetting talent and vendors was a long painful process, On-boarding / Off-boarding and training takes a significant amount of time if you do not have a framework in place.
Research & Delegation frameworks for async work assisted by Gen AI
We were forced to find frameworks for delegation that did not exist - because being in the same room - whiteboarding, strategizing, and agreeing on an approach was not an option. We had to find ways to delegate, communicate, trust, and verify in a remote setting. We heavily used generative AI in these specific areas.
Creating a task requirements document for almost any task that is delegated. This would lay the groundwork for the approach, methodology, and general discipline for us to get anything done methodically. Ex: Content strategy / Calendar. Generally, this would have taken a few days of research and cleanup to create this document whereas Chatgpt like tools with the right prompts do it in a matter of minutes.
Creating a framework to delegate Research and Execute tasks. This let us start with a hunch, a weak thesis, or a gut feeling and then delegate the research and execution to our team aided by gen AI to deep dive into a specific topic - where the team member who was well trained in prompt engineering would do the things that an internet-connected API just couldn't - like old-school cold call our customers to ask what products they used and preferred.
Challenges: Since remote was still a new concept we had to create frameworks around delegation, communication, accountability, and task management.
Automation and Generative AI as a part of our back-office workflow
When we delegated, we constructed the task in a way where either automation or human-in-the-loop automation was a requirement. This enabled us to create semi-autonomous workflows that enabled us to keep most back-office systems working. When generative AI got to the point where task automation was as simple as a clear definition in a written language, this became much easier, as even the burden of configuring automation tools was now taken away. This also enabled us to reduce "exception" events where automation programmed with canned logic would often fail - Ex: Where a customer had a unique support request.
Challenges: Generative AI is still a newer piece of technology that suffers from issues related to alignment, accuracy, explainability, and hallucination. Having the right human-in-the-loop mechanisms is a must-have for consequential decisions.
Putting all the pieces together
We soon realized that what we used internally at Ninesixteen with much success could be a force multiplier for operators at every level - to take their ideas, initiatives, and critical tasks and "fork" it so to speak to a generalist who can execute it aided by Gen AI
To realize this vision we built Assembly Industries
We created the framework and tooling to vet/recruit/onboard and train a highly skilled business generalist to be the 10X companion for operators in this new world.
We enable this resource with best-in-class AI tools to use strategic insights, data-driven methodologies, and most importantly the knowledge of existing best practices to help you execute on your vision.
All of this is packaged in a monthly offering, no long contracts, use as much as you want, one flat price.
We believe that the future of 10x execution lies in a well-rounded generalist in a particular domain who can read the larger picture and ask pointed questions and reason with a Generative AI / knowledge retrieval system to create strategic, data-driven decisions for many complex business and company-building situations.
Me and my co-founder essentially built and sold our last business which had a complicated mix of HW/SW implementation - with a team of generalists who were able to execute on our vision while we focused on strategy and company building. We think this is a pattern that many operators are already using or will start to very soon. We hope you build yours with one too !
