As has been the case each year since this venture begun, Avanceé looks at what has been shared, contemplated, and experimented towards in the past 12 months. Similar to previous years, bits will be light and brief, though pointing to what might be coming next is also par-the-course.

Previous year reviews can be read at the following links:

• 2022
• 2021
• 2020

Much about this year could be grouped into the themes of “instigating more research and experiments” and “agility in the face of uncertainty.”

Research and Experimentation Investments

Regarding Avancee’s research and experiments, there’s been a significant increase in the investment in various hardware and software assets. Part of this is due to the resonance behind machine learning and augmented/artificial intelligence across the IT space. Part of it also due to re-finding some old sea legs around edge tech and experiences.

In terms of hardware, those investments have looked like:

• Brilliant Lab’s Monocle (link)
• Everysight Maverick Developer Edition
• XReal Air (link)
• Flipper Zero (link)
• TapXR wireless keyboard

Even managed to evolve the NFC Ring’s use a few times.

Major lessons from the hardware investments has been a need to increase various levels of technical knowledge around implementation tactics, regulatory risks, and the nature of an internet that’s (naturally?) pushing beyond the confines of browsers, applications, and visual-first modalities.

Leveraging and learning about LLMs has actually been a neat wrinkle in the adoption of some of this. Assuming that LLMs as a research assistant might be the better shape of how hardware-oriented projects continue to find themselves of positive ROI here.

The evolution of crowd-funded hardware seems to have found a niche in this exploration. Some, while still using crowd-funding methods/sites, find leveraging local manufacturing, 3D printing, and even smaller international partners, have taken lessons from the stoppages of 2020 to heart - making small batches of hardware in a more resilient manner, and perhaps giving a lens to what larger companies are doing at scale. Avancee hasn’t jumped into these blind, there’s some definite risk. But, for what has been acquired, and what is yet to be delivered, there’s some excitement towards the various canvases compute is turning into.

In terms of software, there’s been increased attention to or the addition of:

• OpenAI’s ChatGPT and Developer Tools
• XCode
• GPT4All and several Local LLMs
• Microsoft’s Power Automate
• Microsoft CoPilot
• Nostr Protocol incl. apps such as Damus, Snort, etc. (link)
• Decentralized Identities & Protocols
• spatial interfaces and gestural input (Apple’s VisionOS sparked old bits)

Lessons from the hardware are weird. There’s excitement of open source and large company innovations and methods. There’s lots happening. On the other side of that is software. There’s lots happening, but it’s more like a simmering pot of something which might not look anything like the ingredients within.

For example, right now, there’s a distinct blend of “software which expects you to speak its language” (Python, C, Swift, JavaScript, etc.) and “software which as you to refine your own languages” (low and no-code approaches, prompt engineering found in GPTs, etc.). Both are more than capable to make a main course, but what’s able to be created is still up to the imagination of the caster/programmer. That said, the text-heavy emphasis of much of this is something of a discouraging development - we are back to the style of spells and DOS prompts, rather than something a bit more fanticasical IMO.

As mentioned in the hardware section, the alignment of learning new applications and services alongside a local or connected LLM will be a wrinkle to further pursue. Modeling one or several LLMs in this fashion might reveal some inherent weaknesses in one’s own data models, just as much as it would display insights across various applications and a potential fragility to auditing what software is doing when the model or its transformer is IP.

Agility As Currency

The other shape of this year has sat around a significant amount of work in a fractional executive role, embedding humane design behaviors and realizing agility beyond the ceremonies and processes of a project management framework. That’s not to say that practices, doctrines, and eventual behavior change are not a part of what has happened, only that there’s more to agility than these characteristics. The focus to outcomes manifests in the shape of what’s been learned.

In one shape of the observations and lessons of the past year, am firmly more entrenched in the inability for edge technologies and behaviors to make any impact until they either threaten some state of mind, or they offer a significant benefit and opportunity that doesn’t change how that person is viewed within their peer group. For example, offering an automation to improve the bandwidth available during status meetings makes sense, right up until it challenges a (or several) person’s view of the value of the meeting and its ability to make decisions widely known. Introducing technologies and behavior changes encounters this ripple effect outside of the tool or even the imprinted asset itself.

Therefore, some patience, and longer-term measures are needed when agility is needed, but those who have to own it have a longer road to ownership of it.

In a similar view, simplifying the workspace and technology stack continues and challenges what many might consider as “necessary skills” in order to do what is thought of as “work.” The pace at which persons are able to capably use services like CoPilot and ChatGPT are no different than the last decade’s adoption of low/no-code workflow and process management tools, or even the decade previous’ asynchronous and collaborative tools. While it seems the speed to adoption and applicable use is faster - it is not. It is the relevant value, and speed to understand “necessary skills” or “necessary skillful use” which is the hurdle. And many persons are finding they have a signifiant hurdle with sensemaking in light of such movements. While there are a few ways around building this sensemaking muscle individually and corporately, few have the discipline to see it through. Business transformation will be cause of and casuality to an inability to comprehend change - and make sense of the roads to come.

Avanceé’s posture pushing edge technologies has certainly improved understanding the fidelity of what can be achieved with gestural and spatial tool integration. Going forward, these will be more explored - and challenged - as these tools not only disrupt the workspace (iPadOS, Muse, etc.) and the research platform (macOS, GPT4All, etc), but extend it towards a shape of working and connecting which has been used and embraced long before the inception of this initiative. It is assumed (prophesied) smaller teams will also look to take advantage of such lessons, while larger companies will look to invoke more skunkworks projects for learning the pitfalls and accessibility constraints of gestural interfaces before they are met with wider adoption and training.

Speculative Continuances

Have made a “mostly” decent point of not trying to plan out the upcoming year too far. There’s much which happens when coaching and fractional leadership come into play. And yet, there’s a shape of what-can-be permeating a prospective view forward.

No doubt that all things around machine learning, language models, platform decisions, and regulations around the creation, storage, and transformation of data models will be part of the narrative. What is expected to also jump into this is a struggle between those who are able to wield these items to augment themselves into capable arguments for these tools, and those who might wield machine learning’s applications just enough to realize they might already be where many of the transformations portend to be.

Humane, Apple, Dot, and other spatial computing devices will arrive out of the storybooks and movies and into the hands of many before the middle of 2024. There’s gated optimism for the excitement to ignite some rethinking of the purpose of “productivity computer.” But, just like the previous paragraph regarding ML, there will be a struggle between those who will find an ease in a spatial or (nearly) invisible computing construct, and those who will find such efforts highlight where they don’t want to be, or already are but were not ready to launch into that use.

Lastly, there’s always a hope to expand and contract here. As a single-person operation, there’s necessary energy given to what can be handled at one time. Some positive conversations over 2023 provide some hope for efforts in ’24 which might allow Avancee to impact more than direct connections, but not at the cost of time, expense, or quality. Staying tuned here would be the posture advised - or, one can always engage directly and re-engineer your complexities for the future you have been shaped for. Your call. For this space, Avancee means to always be pushing forward.

Thank you for your audience and attention to Avanceé this year. 2024 is advancing, and we look forward to exercising agility and affinity to help current and new clients re-engineer complexity.