Shure: In an AI-code world, communication becomes a system dependency
A lot is written right now on the subject of developer productivity; everybody wants to know whether programmers will experience the boosts that AI-coding tools promise… and they want to know what how that thrust will manifest itself in the workplace.
One woman who has a lot to say on this subject is Susy Liem, vice president of product management for collaboration and conferencing products at Shure, the company known for its high-quality audio and video hardware and software products.
Day to day, Liem is focusing on enterprise collaboration and software-driven workflows and she guest writes for the Computer Weekly Developer Network here.
Liem writes in full as follows…
Software engineering is moving fast.
From AI-assisted code generation to automated testing and autonomous agentic workflows, these tools are reshaping how developers operate, compressing timelines and enabling lean teams to deliver at scale.
Yet, as organisations race to embed AI across the software development lifecycle (SDLC), one truth keeps surfacing: AI alone doesn’t improve developer productivity. Its real ROI depends entirely on the quality of human alignment behind it.
Communication is not a soft skill
AI accelerates execution; I see it every day with my team. But faster delivery doesn’t automatically translate to better business outcomes. Software engineering is inherently contextual. When human communication breaks down, individual velocity turns into collective friction.
To get the most out of AI, organisations must stop treating communication as a soft skill and start treating it as a core engineering capability, backed by the right collaboration infrastructure.
Developers today use AI across the entire lifecycle, moving well beyond basic autocomplete into increasingly autonomous, multi-agent development. Work that once required large engineering squads can now be executed by a handful of engineers in a fraction of the time.
AI increases systemic complexity
However, this speed introduces a paradox: AI increases systemic complexity. These AI tools depend on a precise, shared understanding of intent. When team communication is siloed, the volume of code increases while overall alignment drops.
Work produced at high speed in one context clashes with assumptions made in another. Instead of increasing productivity, teams end up in exhausting cycles of rework.
The insight is clear: The bottleneck isn’t the speed of code generation. It’s the bandwidth of human alignment around that code.
Communication as a system dependency
Research from IDC1 shows just how important collaboration has become in the age of AI:
- 95% of organisations expect disruption within the next two years.
- 71% of organisations acknowledge that collaboration is a key accelerator for the ROI of core tech investments.
- 44% of employees correlate the quality of communication to productivity and efficiency levels. Fragmented teams create bottlenecks and delay innovation.
In engineering, communication is a system dependency. When context flows clearly, misalignments are caught early, technical debt stays contained, and systems behave predictably. When it fails, productivity erodes despite fast execution.
AI raises the stakes because it magnifies our inputs. A small misunderstanding at the prompt or planning phase can quickly compound into productivity losses that are far harder to fix downstream.
The tax of fragmented workflows
Shure VP Liem: Software engineering is inherently contextual. When human communication breaks down, individual velocity turns into collective friction.
Most development environments are scattered. Context is spread across synchronous meetings, chat threads, ticketing systems, code repositories, and documentation. The way we work today has fractured core agile rituals; daily stand-ups are split between in-person brainstorming and remote participation, leaving critical decisions uncaptured.
The result? A continuous “context tax” on your engineering teams.
Developers spend valuable time hunting for missing constraints, reconstructing past decisions, and fixing preventable errors. As AI agents become more embedded in workflows, this fragmentation becomes more costly. AI lacks the human capacity to infer intent. If the data, documentation, and discussions feeding these systems are fragmented and inconsistent, AI’s output will be too.
Without a communication layer built to preserve shared context, even the strongest teams will see their AI gains swallowed by administrative overhead.
Connecting context across the SDLC
This is where communication technology becomes a real differentiator.
Strong collaboration platforms serve as a repository of record for design intent, engineering decisions, and operational context. They bridge the gap across every phase of the workflow, from stand-ups and architecture reviews to incident response and post-mortems.
When communication infrastructure falls short, the business pays for it in delayed releases, technical debt, and missed market signals. When it’s working, the benefits compound:
- AI systems work from accurate, high-fidelity inputs.
- Cross-functional dependencies remain transparent.
- Teams operate from shared understanding rather than fragmented assumptions.
Our multi-agent future
As we look toward the future, the definition of “collaboration” is expanding. Developers won’t just collaborate with each other. They will manage ecosystems of AI agents that interact with both humans and other machines.
In this environment, ambiguity is the biggest risk. Humans can read between the lines. AI can’t. It requires explicit, structured, and continuous context. The technology infrastructure supporting these interactions must be robust enough to keep workflows both efficient and auditable.
The organisations that win won’t be the ones generating code the fastest. They’ll be the engineering leaders who treat collaboration infrastructure as a foundational part of their technical stack, making sure human alignment keeps pace with artificial velocity.
That’s not just a competitive advantage. It’s the new standard.
1 IDC InfoBrief, sponsored by Shure, Collaboration: The ROI Amplifier: Delivering Immediate and Lasting ROI in a Connected Work, doc #EUR253683525, September 2025
