The Challenge of Synchronizing Distributed Systems
When I was in college and used to do programming in my first year I dealt with many problems. Learning through the process and eventually developing an ick for it. I did it because that’s what everyone was doing. Now, when I think about those days (2019-2023) while talking to my old friends I realise important lessons it taught me through the process and concept. Here’s a simple example: In software engineering, particularly within distributed network systems, there is a well-known concept called “data consistency.” When a platform is built across multiple servers or nodes, these individual components must constantly communicate to ensure they are all operating on the same set of facts.
There are generally two ways this communication happens. The first is a direct, synchronized approach, often referred to as “strong consistency.” In this model, when a piece of data is updated, the entire system is locked for a fraction of a second until every node acknowledges the change. Everyone reads from the exact same page, at the exact same time.
The alternative is “eventual consistency,” often facilitated by intermediaries like message brokers. In this model, a node sends an update to the broker, which then gradually routes the information to the other nodes. While this allows the system to keep moving without pausing, it creates temporary gaps in reality. For a brief window, Node A might hold one value, while Node B holds another. If a user queries the system during this gap, they receive mismatched information.
When complex operations depend on precise data, eventual consistency introduces friction. If the nodes are not communicating directly with one another, the system spends an inefficient amount of computing power simply trying to reconcile differing states of information. Disjointed communication channels inevitably lead to latency.
The conclusion drawn by system architects is straightforward: when the stakes are high and precision is required, relying on intermediaries or asynchronous updates creates a “split-brain” scenario. To move forward efficiently, the system requires a single source of truth and direct synchronization.
At Auxano:
This architectural challenge closely mirrors the mechanics of VC negotiations, particularly in the later stages of finalizing an investment.
Recently, we have been evaluating an AI-native analytics platform. The initial phases of our evaluation proceeded systematically and efficiently. We engaged in several productive discussions with the founder, which allowed us to understand the core vision and operational mechanics of the business. We reviewed the necessary operational data to evaluate the company’s baseline health and growth trajectory.
Given the technical nature of the product, I spent time analyzing the underlying tech architecture to understand how the AI models were integrated and scaled. Finally, we conducted multiple calls with their current customers. The feedback was positive, indicating that the platform functions well and provides tangible value to its users.
Having established a solid foundation of diligence, we progressed to the critical stage of discussing the investment modalities. It was at this juncture that the communication structure shifted.
Instead of a unified, direct channel, our communication began occurring in silos. Certain discussions took place directly with the founder, while other updates and counter-proposals were routed through a fundraising intermediary. Because the flow of information was divided between these two separate channels, a communication mismatch naturally developed. Just as a software broker can introduce latency into a system, the siloed back-and-forth created a temporary gap in shared understanding. A point made to the intermediary might not be relayed to the founder with the exact same nuance.
To be clear, the presence of an investment banker is by no means disruptive; they are a vital part of the ecosystem. Much like specialized nodes in a broader network, bankers play a crucial role in processing complex financial mechanics, structuring terms, and providing valuable market context. The friction arises not from their involvement, but from a lack of defined routing rules for our conversations. There are specific modalities such as long-term product vision, cultural alignment, the operational nuances of their AI models and all the technicalities that are almost always best discussed directly with the founder. Conversely, detailed structural terms, valuation benchmarking, and the mechanics of the investment are often most effectively navigated with the banker.
The objective is not to bypass the intermediaries, but to streamline the flow of information. When the communication architecture is thoughtfully designed, every stakeholder understands exactly what type of discussion flows through which channel. By establishing clear boundaries and regular synchronization points for these conversations, we ensure that both the founder and the banker are operating from the exact same source of truth. This organized approach ensures that everyone has a clear, accurate view of where the deal is moving, ultimately leading to a much smoother path to consensus.
The primary takeaway from this phase of the deal is the importance of “strong consistency” in human negotiations. Once a deal reaches an advanced stage, relying on fragmented communication channels inevitably extends the timeline. Achieving consensus requires bringing all nodes such as the founder, the investors, and any advisors to operate from the same source of truth.
Author,
Tanmay Gajbhiye
