Design Perspective Intelligent Hybrid Software Platforms to Survive the Evolutionary Avalanche

By Lance Maurer, CEO

Image generated by AI

Engineering is supposed to be fun.

Developing solutions for tough technical problems with customers who have become friends while using collective brain power and modern technology is a rich and satisfying professional experience.

Yet, it often feels as though our technological gains are invariably met with a constant avalanche of change in the name of progress . This happens on both sides of the relationship, and often manifests as consolidation, budget cuts, organizational shifts, new technology and consumer trends, and an increasing pressure from stakeholders for teams to deliver more with fewer resources. Painful as it is, the truth is that consolidation is an unrelenting force in our industry-it will persist even after we all end up working for the Borg! This is simply one of many core natures of our universe; like the curious space dust that began clumping together 14 billion years ago, things will continue to merge and shift in strange ways through the eons every jungle survival story follows a similar pattern.

So if industry chaos is the norm, and jarring technology evolution is merciless, how do we design technology to retool factories that must operate efficiently through these dynamic changes?

In my professional Odyssey through two different industries (aerospace and now media tech), I have grown to accept the natural laws of merging chaos as foundational truths they have become part of the design process itself, necessary for complex machines to ensure longevity and for businesses to endure. It does not matter if you are the technology vendor or the customer applying it, understanding said ground truth is crucial to how the design and buying process should happen so that both parties thrive. Investment should be made in technology that is adaptable to change, with an attention to a 5-7 year horizon. When looking at technology to invest in (not only money, but time and trust), start with aligning these baseline truths does your business share core technology values with the vendor you are considering?

My view of the Media Supply Chain technology core values:

Making consistent, professional media is creatively, technically and financially challenging

Platforms should be hybrid, scalable, expandable, and affordable to provide maximum flexibility

Industry standards provide format direction, but consumption methods (e.g. 9:16) are shifting and tools need to be able to grow outside the current box

Output quality matters artifacts are avoidable

A.I. has great potential but should be handled with great care

Our industry is in a (relatively) high transformational period, which will likely continue for some time

After core values, the keys to adaptability over time:

Hybrid strategies thrive in times of high change

Toyota did it right. Their multi-pathway strategy-a calculated bet on hybrid engines-has proven to be the definitive answer for the current auto market, as evidenced by their surging sales figures. By prioritizing solutions that can work flexibly on prem and in the cloud ( hybrid ), we can bridge the gap between proven, dependable systems and the cutting edge, without exposing much risk. This balanced approach to planning and purchasing decisions is vital when nascent and untested new technologies are unleashed into the wild. Because the media supply chain is a complex engineering ecosystem, it requires more than just a leap of faith into the new; it requires an accepted foundation of what already works and alongside an ability to experiment and take advantage of new approaches as well.

AI strategies demand a similar hybridization approach for supply chain technology like image and audio optimization. The media supply chain tech stack should include several workhorse foundations of proven technology paths augmented by increasingly validated new tech (like AI) to work toward specific efficiency targets. Unless you have an appetite for risk in your R&D budgets, going all-in on AI for more complicated workflows like image optimization is a high-stakes gamble, as the tech is still evolving and companies attempting to create products are coming and going. Prioritizing iterative process AI over generative models makes sense because determinism offers set-and-forget reliability to free you up for the next task; conversely, when AI attempts to be clever through generation, it often introduces unreliably generated artifacts into workflows. This is why it is key to enable the trusted humans here because they know from experience where to look for gaps in these new tools, avoiding potential hazards; this tacit knowledge, or know how has not transmuted into the AI models

Technology is a tool for a great team prioritize the human process and supplement with great tech to deliver the best culture of technical growth.

Cloud infrastructure serves as a perfect case study for hybrid necessity:

The Baseline: Building on-premise (customer-managed infrastructure, private VPC, etc.) systems to handle the bulk of your standard workload remains a logical move given today's cloud economics.

The Burst: Public hyperscalars are an unparalleled tool for pants-on-fire surges or short-term projects it is more expensive, but highly predictable and relatively easy to navigate. An overnight delivery premium would cover its cost. In addition, a lot of great, experimental media technology calls it home.

The Future: While interconnectivity through cloud is undoubtedly the future for LIVE events, a purely software-defined, end-to-end, highly reliable 2110 cloud broadcast solution is still a few beats from total maturity. That said, compressed formats for lower tiered production works fine today.

By designing your public cloud workflow to handle only some fraction of your peak load, you keep the compl

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