Articles, papers, and resources I find valuable. Curated weekly.
This week felt more practical than flashy. The strongest pieces were about what happens after the demo: building agents faster, giving them access to messy old systems, and keeping security and workflow context tight once they start acting on their own. The other theme kept showing up too: the contact center is getting pulled into the rest of the stack instead of living in its own silo.
This is the clearest look I saw this week at what agent building turns into after the first pilot. Regal is trying to collapse a four week setup cycle into a chat driven workflow, which matters a lot if your backlog is dozens or hundreds of automations deep.
Good reality check on computer using agents. The useful point is not that they replace APIs. It is that they can handle the ugly swivel-chair work between apps that still slows contact centers and back office teams down.
Strong argument that conversation platforms are becoming the better source of truth than the CRM itself. Even if you do not buy the whole thesis, it is a useful way to think about where customer context will live once AI agents start doing more of the work.
Worth reading because it treats AI security like an operating model problem, not a compliance box. If agents can act, reason, and touch customer data, boards are going to care about logs, access, and oversight a lot sooner than vendors want to admit.
Twilio is making a smart bet here. Embedding contact center functions inside the apps teams already use is a cleaner answer than forcing another heavyweight desktop into the stack, especially once AI handoffs start bouncing between humans and bots.
Simon did the nerdy work nobody else was going to do and turned Anthropic's prompt history into something you can actually inspect. If you build or operate agents, this is a useful reminder that model behavior changes in the instructions as much as in the weights.
This week kept circling the same issue from different angles: control. No Jitter had the clearest version of it, arguing that clean data pipelines and tighter operating discipline matter more now than raw model excitement. CX Today stayed on the governance side with consent and observability, which feels right given how many teams still cannot explain why a bad customer interaction happened. And on the voice side, Telnyx and Zoom both pointed to the same next step: conversation data is getting wired directly into agent systems, fast.
This gets to the part a lot of AI coverage skips. If the data pipeline is messy, the model does not matter much. Good read if you want a blunt explanation of why enterprise comms AI projects stall after the pilot.
We are past the "should we use AI" stage. The harder question is who gets to tune it, measure it, and stop it when it drifts. Solid framing for the teams now dealing with production reality instead of conference demos.
Consent is one of those topics everyone claims to handle until an auditor asks for proof. This piece is worth reading because it treats consent as an operational system, not a checkbox buried in legal copy.
Useful if you are tired of dashboards that tell you something broke but not why customers felt it first. The core idea is simple: tie network, app, and agent signals back to the actual customer experience.
This is one to watch if you care about the plumbing behind voice agents. Telnyx is making a direct pitch around latency and cost, which is where a lot of voice AI projects either feel magical or fall apart fast.
Zoom turning meeting data into something Claude can actually work with is a bigger deal than it sounds. The interesting part is not the connector itself. It is that meetings are becoming structured input for downstream agent workflows.
The agentic AI story stopped being theoretical this week. NiCE Cognigy's Nexus event had practitioners talking about production deployments, not roadmaps. Salesforce showed the real engineering problem: you can't get an LLM to follow a structured business process 100% of the time, so they built deterministic if-then scaffolding around it. Meanwhile Oracle shipped coordinated agent teams inside Fusion Cloud, and No Jitter covered what happens when employees start feeding meeting transcripts to consumer AI tools and no one has a response plan. Busy week.
Salesforce added a programmatic scripting layer to Agentforce called Agent Script — essentially if-then conditions that constrain what the LLM can do. The honest framing: LLMs can't be trusted to follow structured processes 100% of the time, so they wrapped deterministic logic around the probabilistic core. Good primer on the real engineering problem behind enterprise AI agents, not the pitch deck version.
NiCE Cognigy held its Nexus event and four analysts walked out with the same takeaway: agentic AI is in production now, not just in demos. The NiCE/Cognigy deal is looking like one of the few CCaaS acquisitions that actually made both products better. Worth reading for the Careington case study alone — shaving 45 seconds off a call funded the whole AI program.
The scenario: an employee pastes a meeting transcript into a consumer AI tool, and now that data lives in a third-party model. Most orgs don't have an incident response playbook for this. The piece treats shadow AI exposure as a data breach class problem, not just a policy violation — a framing shift that's overdue.
Vonage embedded voice and real-time AI directly into ServiceNow's CSM and ITSM workflows. The problem they're solving is real: voice has always been the odd channel out in omnichannel stacks, sitting next to the CRM rather than inside it. If you're running ServiceNow and Vonage, this is worth a look before the next contract renewal.
Oracle shipped coordinated agent teams inside Fusion Cloud — agents with defined roles, decision authority, and human escalation paths built in. The architecture difference from copilots: these agents can actually change records and progress workflows, not just suggest next steps. The governance piece (human override, exception surfacing) is doing a lot of work here.
Gartner says 40% of agentic AI projects will get cancelled by 2027. This piece argues the failure mode isn't model quality, it's silo architecture — each AI tool optimizing its own metric without contributing to shared intelligence. The four-layer framework (and the 'Silo Paradox' construct in particular) is worth the read if you're designing contact center AI and not just buying it.
Meta killed Horizon Worlds this week, which nobody is crying about, but the CX industry should at least acknowledge what it quietly built with VR before moving on. Meanwhile the mobile UCaaS space is getting interesting: dual-persona eSIM plays from NetSapiens and Crexendo are moving past the separate work phone era. And Jon Arnold raises a point worth sitting with: the same AI that's supposed to fix enterprise communications is expanding the fraud surface at the same time.
Meta's Horizon Worlds shuts down June 15 after burning $80B. The tech press is filing this under 'hype cycles that didn't survive reality,' and they're not wrong about the consumer play. But inside the contact center, VR found a real job: agent training. Gartner's 2022 prediction that 25% of people would spend an hour a day in the metaverse by 2026 looks embarrassing now. The enterprise training use case actually held.
The dual-persona phone idea is getting real: a business eSIM and a personal line on the same device, with enterprise controls only touching the business side. NetSapiens ships this as 'Extend,' Crexendo has a similar play. The technology works. Whether IT teams will actually manage eSIM provisioning at scale is a different question.
Jon Arnold covers an angle that doesn't get enough airtime: as AI makes it easier to synthesize voice and automate calls at scale, the fraud surface expands with it. Enterprise comms vendors are selling AI as the solution to communications problems. It's quietly becoming the source of new ones too.
UniFi pushed MLO-STR (Multi-Link Operation, simultaneous transmit/receive) to the UDB switch via firmware update. MLO is the Wi-Fi 7 feature that matters most in dense environments — bonding multiple bands simultaneously instead of switching between them. Small community post, but if you're running UniFi gear this firmware is worth grabbing.
Informatica (Salesforce-owned) deepening its Microsoft partnership means Azure and Salesforce Data Cloud are getting tighter integration for enterprise data governance. Worth watching for anyone running AI-driven CX on either stack — data quality upstream determines a lot about what AI agents can actually do downstream.